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shadowsong26fic · 6 years ago

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The Family of Spies AU

AKA ‘Shadowsong should not have unsupervised access to multiple fandoms at once: Exhibit A.’

I kid. Mostly.

Anyway, it’s that time again--time for an AU Outline! It feels like forever since I’ve done one of these. …and by ‘forever’ I mean the last one was the SPN/Person of Interest crossover back in January.

This one is, uh, also a fairly niche crossover. It’s inspired and helped along by @tigerkat, who introduced me to one of the two fandoms and whose Star Wars OCs I’m borrowing to make it work. (Also, one or two bits in here are more or less lifted from our IM conversations on the subject <.< So, you know, credit where credit is due!)

Basically, the short version is, I’ve been watching Nikita, and TigerKat and I have put together this whole extended family for Kallus and Zeb and one thing led to another, wires got crossed in my brain, and here we are.

Welcome to my Star Wars/Nikita fusion.

So, first, some relevant background:

In everything TigerKat and I developed, Alex and Zeb end up collecting/adopting four kids. (TigerKat, feel free to correct me on any details that are Off in any way!)

First kid they adopt is Mirah, shortly after the events of ANH.

Mirah is Human, and around three or four at this point; her parents were part of an extremely pacifist sect, of the kind where even defending yourself against someone trying to kill you is Not Okay. The sect was wiped out (probably not by the Empire, last I heard?) and Mirah was the only survivor; she watched her parents died right in front of her. Alex ended up there on an unrelated mission, and brought the little girl back to base.

Turns out, she’d gotten Attached and would not sleep without him close by.

(I mean. He’d gotten Attached as well but there is a Conversation to be had here, and he and Zeb haven’t actually had it yet, so…yeah.)

So, that’s how they get Kid #1.

Mirah later grows up to be essentially a mob boss/puts together a semi-legal syndicate. She doesn’t have a whole lot of faith in the law.

Second kid is Orryn, something like a year or two later, I think?

Orryn is a Donogh (species name subject to change; they’re basically like human-sized rabbit hobbits), and four or five years older than Mirah. His father and older brother were killed when he was born, and his mother eventually found her way to the Rebels after that. Donoghs tend to have very large families, so the fact that he’s an only child is a little Weird.

His mom is a friend of theirs, and when she dies, Alex and Zeb take Orryn in as well.

He is very Soft, both physically and metaphorically (like I said, rabbit hobbits), and like the sweetest kid you’ll ever meet.

(Mirah learns very quickly to weaponize her brother’s Sad Eyes. She’s very good at getting what she wants.)

The other three kids all end up taking Zeb’s last name; Orryn keeps his original one (his people are matriarchal and matrilineal).

He grows up to be a mechanic, and has a more typical family for his species with nine kids.

Third is Shamie, who’s roughly halfway between Mirah and Orryn; they get adopted a month or so before ESB.

I’ve written about them here; but the most important bits--

They’re Human, agender, and a former street thief/pickpocket. They help Zeb out when a mission goes sideways after his local contact fails to show up, and Zeb decides to keep them, because he really can’t leave them there for a long list of reasons. They’d been on their own for close to a year at that point, and were roughly eight or nine.

(The conversation where Zeb checks in with Alex about this is very entertaining, because he texts to confirm that a third kid is okay in the middle of a firefight. Alex is less than thrilled.)

Shamie and Mirah are basically platonic soulmates. There’s just a sort of click when the two of them meet.

They grow up to be a priest of a sun/fire deity.

Fourth is Hanula, better known as Hanny.

She’s a Lasat baby who they adopt a few months after Endor, after Zeb mentions to the elders on Lira San that he and Alex have been considering a fourth kid, maybe starting with an infant this time, and maybe someone of his own species this time…

Some time not too long after that, Hanula is placed in his arms and he’s told ‘good luck.’

She’s stabby, as in she likes to Stab Things as a baby (usually with, like, a fork), which later gets translated into cooking--she ends up as a Chef.

While she does turn up, of course, she’s not super relevant for this crossover, but she’s Delightful so I thought I’d share anyway XD

(There’s also Alex’s sister and her sons, plus, uh, the various grandchildren, but they’re also not super relevant to the crossover. I can share details about them if anyone’s curious, though.)

As a note, I’ve only seen like half a season of Nikita at this point; so while we’re starting from the same basic premise, I don’t really expect this to converge with actual future plot points like at all. So.

Also, as a result of that, this outline will probably also take on a certain resemblance to Alias and/or other similar Spy Dramas.

Anyway. So. Let’s get this show on the road.

Kallus takes on Nikita’s role in this--Death Faked For You; trained to be a super spysassin by a Shady Black Ops Group from his late teens/early twenties. Much like Nikita in her canon, he meets someone while on an extended cover assignment and falls in love.

Division is less than thrilled with this, and so arrange orders Zeb’s death.

(Obviously, this doesn’t take, because I am Not About That. But Kallus genuinely believes Zeb is dead, which is what pushes him to break free, much like Nikita’s reaction to Daniel’s murder.)

(Zeb also thinks Kallus is dead; he, of course, got picked up by the Ghost crew, but more about him later.)

Mirah will take on Alex’s role (which is why I started referring to Kallus that way, even though in my head and in this outline up to this point he’s mostly Alex XD).

Probably a blend of the two backgrounds--her parents/the sect she grew up in were taken out by Division; probably with the cover story that they were a Dangerous Cult, but the exact reason was more likely Profit or something. Since they mostly weren’t? At least not in the ‘need to be dismantled’ sort of way.

Kallus, like Nikita, was on hand and made sure that the little girl survived, but wouldn’t/couldn’t follow up since he was still a mostly-loyal Division agent at that point. He tracks her down after he breaks free, and they start working together.

She eventually talks him into the idea of her infiltrating Division, as that will better suit their plans to dismantle the organization.

(…really, most of this early part is not super different from Nikita and Alex. Mostly summarizing for anyone reading this who’s unfamiliar with the show.)

Shamie is an older/prior recruit; they’ve been here a few months. Their marksmanship is pretty much bottom of the barrel, so far as the current crop of recruits go, and their hacking skills could use some work, but they’re one of the best at hand-to-hand/other close-quarters combat, and they’re probably top third with explosives and other detail work. And they’re generally a pretty phlegmatic person. Not many of the other recruits keep cool under pressure as well as they do.

They’re probably fairly close to being evaluated and promoted to full Agent status when Mirah is brought in.

The two of them, as in their normal lives/timeline, immediately click. Mirah reports back to Kallus, confirming her infiltration was successful, and also mentioning Shamie.

“Remember what I told you about making friends,” Kallus warns her. “Losing them will be hard. And you can’t know how loyal this person is to Division. Be very careful.”

Mirah internally rolls her eyes, because she’s not dumb, she knows that.

A few more quick parallels, for the Higher Ups at Division:

Arindha Pryce stands in for Percy.

She just has the right blend of Genuine Competence buried under Not As Good As She Thinks She Is to match up with him.

Founding member and leader of Division.

Thrawn stands in for Amanda.

Like, okay. The two of them, for a variety of reasons, have vastly different management styles.

But in terms of his actual skillset and the role Amanda plays, at least on paper? Which is to say, supervising training/constructing covers/monitoring recruits and agents and their mental states?

(Plus, the whole…resident torturer/interrogator/etc. thing…)

Yeah, he could pull that off.

Pellaeon stands in for Michael.

Because I love him.

Also the Vastly Different Dynamic between the Head of Division, the Whatever Amanda’s Actual Job Title Is, and the 2iC/Head Field Operative with these three as opposed to Percy, Amanda, and Michael entertains me.

(Pellaeon is more loyal to Thrawn than Pryce, but only if it came down to an Actual Contest between the two of them would that ever be relevant. He’s extremely competent, but occasionally a little too involved with the recruits, in a fairly paternal sense. Especially since he’s probably a good twenty years older than Michael. But I digress.)

So, Mirah is successfully inserted. That goes pretty much the same as in Nikita canon, completely with Kallus making a splashy return to Division’s radars.

(Probably not at Zeb’s grave, though; if Zeb even has an actual grave.)

She starts interacting with other recruits, including Shamie. The two of them click pretty quickly, all things considered, but given the circumstances…yeah, they keep a certain level of distance, at least for now.

…well, at least on the surface, anyway. Mirah is even more determined to burn Division to the ground if they breathe harm in Shamie’s direction.

(For their part, Shamie may or may not start to notice a few anomalies, but they keep that knowledge to themself for now.)

For a few months, it’s pretty much the pattern the early S1 episodes have--Mirah will get details on an official Division op, pass them along to Kallus, he’ll be on hand to foil it. She gets activated briefly once or twice, but is mostly just working as a regular recruit for her cover.

Plus, you know, evading Thrawn’s suspicions; all that good stuff.

Pellaeon does take a liking to her--she reminds him of Kallus, who was one of the better recruits, and he keeps an eye out for her, much like Michael does for Alex in canon.

Shamie gets activated for their final evaluation/first kill mission about two or three months after Mirah gets recruited. They succeed, but some of the aftermath/followup confirms their previous suspicions about Mirah, and they’re left sort of struggling with what to do about it.

On the one hand, they’re a fairly loyal Division agent at this point, and what Mirah’s doing is probably going to get a lot of their fellow agents, maybe even some recruits, killed. And they know that probably some of what’s been reported as Kallus’s activities is exaggerated, or at least spun to make him look Evil and Division look better, but they know there’s a grain of truth to it.

On the other...they spent a few years, as a child, working for a thief-runner/gang. This was…not a good situation. Gotta keep the baby thieves in line. And they’ve seen other recruits get canceled before. As much as they don’t necessarily want to go against their superiors in Division (again, gotta keep the baby thieves in line; they know what the consequences of that would be), they also know that that loyalty does not go both ways. They are expendable. All of the recruits and agents are.

And they like Mirah. And if they don’t look out for each other…well, who will?

Besides. It’s not like they have any actual proof. Bringing this to Pellaeon, who likes Mirah, or Thrawn, who likes no one--let alone Pryce--seems like it’ll backfire.

So, they stay quiet about what they’ve guessed, and wait, and watch, and work.

Things change when Orryn is recruited.

Mirah and Shamie both take one look at this sweet, gentle boy and have the same thought--he won’t last. He’ll be cancelled within a month. Maybe sooner.

Pryce questions the choice of bringing him in, too; it was Thrawn’s idea. No, he’ll never make field agent, but the boy’s good with mechanics, and computers. If he can survive the training process, they can put him to use there.

Sort of considering him for Birkhoff’s role.

Shamie, even as a full agent, doesn’t have the access or the tools they need to spring Orryn, as much as they want to.

But Mirah--Mirah has Kallus, and a way to contact him.

“This isn’t about my friend. This is about a sweet kid, too sweet for Division, who will be killed or broken if we don’t do something,” she says. “And isn’t that part of what we’re doing here? Trying to make sure that doesn’t happen to anyone else?”

Kallus is torn. Because, on the one hand, she’s absolutely right--it’s why he was reluctant to send her in undercover (oh, yes, the thought had occurred to him) until she suggested it.

But on the other hand, getting a recruit out of Division without compromising Mirah’s emergency exfiltration strategy is going to be Hard. And as much as he wants to help this kid, he also wants to help/protect the one he has already.

He tells Mirah, eventually, that he can’t promise anything, but he’ll start working on a plan.

Mirah…

Remember what I said earlier, about Mirah tending to get what she wants?

Mirah gets to work on her end. The way she sees it, if she figures out a way to get Orryn outside somehow, whether it’s getting him temporarily activated like she was that one time, or some other excuse, then Kallus won’t have a problem rescuing him.

Of course, she’s just a recruit herself, and she can’t muck around with that without compromising her cover. She’s half-tempted to just shove Orryn out her escape tunnel, her own exit be damned, but Kallus specifically told her not to do that, so she holds back.

The opportunity comes when one of Mirah’s prior breaches is discovered, two or three weeks after Orryn’s brought in.

Possibly the shell program she and Kallus have been using to talk; possibly something else and she didn’t cover her tracks quite well enough (i.e., breaking into Pryce’s office). No one’s tied it to her, not yet, but things are Tense.

Kallus asks Mirah if she needs an extraction, and she again brings up Orryn. “I’m good,” she says. “But the sweet kid I was telling you about…”

“We talked about this,” he says. “And I am working on it, I promise.”

But before either of them can do anything, Orryn ends up at the wrong place at the wrong time, and one of the guards is convinced he’s the mole.

Thrawn points out that this doesn’t make much sense--the serious breaches started well before Orryn was brought in.

Pryce agrees, but insists on letting the situation run its course, to see if it can flush out the real mole.

And Mirah has a Thing about people she’s attached herself to getting hurt.

Mirah manages to somehow get Orryn out of wherever he’s being held. She sends a quick message to Kallus--“Sweet Kid coming out, they think he’s me”--and takes him to the exit tunnel.

They are pursued, of course. By the overzealous guard--and by Shamie.

Mirah gets Orryn into the tunnel and prepares to stand her ground.

Shamie catches up first.

And handles the situation Very Differently from the way Thom does in Nikita canon.

“I’m not turning you in,” they say. “You got Orryn out?”

“Yeah.”

They nod. “Good. Okay. They think he’s the mole, but they’re gonna realize someone helped him escape, unless--”

And then the guard catches up.

There is a Fight. The guard manages to shoot Shamie (not seriously; through-and-through in the upper arm), who tosses Mirah their gun, and she fires back, putting two in his chest.

“…we can work with this,” Mirah says, pressing her hands onto where Shamie’s bleeding. “If we…if we stage it so he pointed the finger at Orryn to cover his own crimes…”

“You have any evidence we can plant on him?” Shamie says. “M’good at that. Planting evidence.”

“Yeah,” she says. She has a key card, and a few other bits and pieces. Shamie, hands shaking slightly, positions them appropriately. “And Orryn…”

“Was also a plant,” Shamie decides. “Sent in when the guard’s cover got shaky, to extract him. But he managed to get away in the confusion. We underestimated him.”

Mirah thinks about this for a minute, then nods. “I think I can sell that,” she says, as more guards start heading their way.

“Good,” Shamie says. “…talk later.”

Mirah nods, and Shamie blacks out, leaving her to spin the lies they need to survive this.

A few hours later, Mirah touches base with Kallus to confirm Orryn got out safely, and to inform him he has another inside agent.

So, the situation has improved somewhat! Unfortunately, it’s also been damaged--since the shell program was found, Kallus and Mirah don’t have secure communications. That first message she got out, about Orryn and Shamie? Yeah, she can’t use that route again, or she’ll establish a pattern.

On the other hand, Shamie is a full agent, which means they have an apartment and the freedom to move around and set an in-person meet. Which Kallus wants anyway, to evaluate Mirah’s friend.

(And, if they check out, to spoof their tracker and give them freedom of movement. Always a plus.)

So, Shamie and Kallus use another one-off communicator to set an in-person meeting, so they can talk.

“You did help Mirah and Orryn,” Kallus acknowledges, after they’ve run through their prearranged confirmation signals. “That counts for something.”

“But you think it could just be me establishing a cover,” Shamie said.

“The thought occurred.”

Shamie doesn’t say anything right away. “I hear all kinds of things about you,” they finally say. “Some of it seems true. Some of it seems exaggerated. I know you’re Division’s enemy, but that…” They shrug. “I trust Mirah. And she trusts you. That’s good enough for me.”

“And Division?”

“I know how gangs work,” they say, flatly. “I used to work for one--they ran a bunch of kids, pickpocketing. Thing about gangs is, most of them do some good in their community--take care of external threats, or whatever. That’s how almost every gang started, anyway. Division may have more money and fancier gadgets and a bigger community, but they work the same way. And most gangs, even if they keep helping their communities sometimes…somewhere along the line, it turns out to be about profit and power more than anything else. But that’s not the issue. The issue is…you can tell, when a gang’s leadership, the loyalty they demand from their members…you can tell when they reciprocate.”

“And Thrawn and Pellaeon and Pryce don’t,” Kallus says.

“Pryce for sure,” they say. “Pellaeon does, but he’s more loyal to Thrawn than the rest of us. Thrawn…is harder to read.”

Kallus considers that for a moment. “You know, what we’re doing--it’s dangerous. I can’t protect you. I burned my one extraction route getting Orryn out.”

“All of my choices are dangerous,” Shamie says. “But like I said. I trust Mirah. She trusts you. I don’t trust Division.”

Another moment of silence. “Here’s our communication protocol,” Kallus finally says. Because Mirah trusts them. And I trust Mirah. If I don’t trust her--what am I even doing here.

Shamie also, as it turns out, has valuable information Mirah didn’t have access to. While not as successful as Kallus, there’s another group working to take Division down; getting involved and throwing off some of their ops.

“Should we reach out to them?” Mirah asks, when this filters back to her.

“No,” Kallus decides. “Most likely, they’re another mercenary group. Trying to be another Division, another Gogol, and take out the competition. There’s a slim chance that they’re actually on the level, but if they’re not…Best to stick to ourselves and avoid drawing in any outsiders.”

The kids agree, because he’s the expert, and drop the subject.

He does, however, ask Shamie to keep tabs on this other group as best they can without compromising their cover. Which should be easy enough.

(Of course, Shamie can only tell him as much as Division knows about them, which isn’t much. They’re a small group, probably a five- or six-person team, and they tend to ghost in and out of situations without leaving much evidence behind…)

The other new advantage they have is Orryn.

Remember why Thrawn wanted him recruited? He’s good with tech and gadgets?

Orryn gets a look at Kallus’s setup, particularly when he’s trying to figure out how to re-establish communications with Shamie and Mirah.

“I can fix that,” he offers.

Kallus blinks. “Plan was, establish an identity and get you out of the country, into hiding,” he says. “Which I will do, I’m working on it, but--”

“Division hurt me, too,” Orryn says. “And Mirah and Shamie are in trouble, and so are you. I want to help.”

Kallus eyes him. He knows, just as clearly as Mirah and Shamie did, that he cannot take this kid into combat. On the other hand…he would’ve been recruited for a reason. And Kallus is well-trained and skilled, but there might be something to said for raw talent and an expert touch.

“All right,” he finally says. “We’ll prep an exfil for you, just in case, but it’ll be some time for me to put it together anyway. We’ll see how things go.”

Orryn nods, and gets to work.

And so pass the next few months, with Mirah working her way up towards qualifying and passing the information she has access to, and Shamie and Orryn supporting Kallus in the field.

Eventually, Mirah goes on her qualifying evaluation, and passes with flying colors. She’s an interesting counterpart to Shamie--she’s a sharpshooter and just as deadly as they are in hand-to-hand, but she doesn’t work as well with the explosives and so on.

Meanwhile, Shamie is a very tactile person--if it’s a hands-on task, especially one that requires a lot of detail work (such as setting up a bomb), there are very few people who can match them. But they have issues with distance kills and with the computer stuff.

Mirah is set up in her apartment, not too close to Shamie, but enough that they can meet. They’re in the same city.

The two of them, on their own, are pretty terrifying assassins.

Shamie is fairly innocuous-looking; dark hair, dark eyes, skinny, blends into a crowd. They’re also the most chill/calm person in the known universe, so people tend to gravitate to them in a crisis. And they’re kind. Genuinely kind, in a way that invites people’s trust.

This is what makes them an excellent priest in another life. And in this one…Beware The Nice Ones is a trope for a reason.

Mirah, on the other hand, is much more overtly intimidating. Unless she’s making an active effort to pretend otherwise, she exudes Danger. She is ruthless and practical.

She is also extremely skilled, good at manipulating people, and very hard to convince to back down.

Now imagine the two of them working together.

Unstoppable and terrifying.

And Division (and Kallus) are both aware of this.

So, they actually end up partnering quite a lot.

The four of them are circling closer and closer to closing in on Pryce and taking her out permanently--Thrawn as well, and Pellaeon as a third priority, but Pryce is their top target--when things Change again.

Mirah and Shamie are put on a wetworks op that requires a team. Probably similar to that one prince dude and the museum.

They feed Kallus the intel, as always, and he comes up with a plan to foil it.

But there are a couple of issues.

He needs Orryn for this op, for one thing. And not just as background, on-site.

When he scouts around to do his own prepwork, there are some technobabble things he need handled, but they need to be within range. Twenty yards, twenty-five on the outside.

So, his first priority--well, maybe not first, but certainly Up There--is to plan out Orryn’s escape route if things go wrong.

The second issue is that Shamie thinks this might be another mission the Unknown Third Party may also crash. Since they still don’t have a lot of intel, that’s potentially another five or six people coming in.

And that’s if they’re correct in that it’s the mystery team, and not Gogol or someone already on the radar.

But the opportunity to interfere with Division and save a life or two is too good to pass up, despite these problems. Kallus plans his counter-mission, and they get to work.

Phase One of the mission goes fairly well. Shamie does confirm a third party is involved, but at first, their presence doesn’t cause too much difficulty for either Our Heroes or Division.

Shamie gets the assassination target pinned down somewhere Kallus and Orryn can extract them; Kallus gets the victim to the prepared escape route, and then returns to deal with the secondary objective; the one that required Orryn--some sort of hacking/virus/Planting Evidence type thing.

Well.

So my Art Skillz are far from up to par, but here’s a general overview of the layout of the scene where they do:

...so I can’t figure out how to make tumblr embed it without throwing off all the rest of my formatting so, click the link.

Where things go wrong is when Kallus gets a good look at the closest member of Team Unknown.

Who is very, startlingly, distractingly Familiar.

And he does the worst possible thing he can do in this situation.

He freezes.

Naturally, another member of the Division team sees the opportunity and takes it.

He gets hit three times in that second--chest, abdomen, upper thigh. Serious injuries.

Mirah immediately runs to him, laying down cover/suppression fire at her supposed Fellow Division Agents.

(…yeah, remember that whole bit about her parents dying in front of her? She’s. Uh. She’s come to view Kallus as a second father. This is Not Okay.)

Shamie follows, of course; she gets to Kallus.

They hesitate for half a second. “…get him out of here. I can handle this. Go.”

Mirah nods and drags Kallus back to the van--

--only to find that Orryn has been taken.

She can’t--she can only be in one place at a time. She’s good, but she’s not that good. And Kallus, her teacher, her unofficially-accidentally-adopted dad, is dying in front of her.

She gets into the driver’s seat and books it.

Shamie fires after her, but…well, marksmanship has never been their strong suit, so they fail to stop her.

This is basically Mirah’s worst nightmare made real.

Her dad is dying.

Her brother is missing.

Her other sibling is trapped and about to be probably tortured.

She is holding together by a thread and the only thing keeping her going is if she falls apart now, Kallus will die.

Okay. Time to do something about that. She can’t do much, but she can do even less about the other things, so. Time to do something.

She gets a tourniquet on his leg, pressure dressings on the other wounds, but she’s pretty sure his lung’s collapsed and she doesn’t know how much other internal damage there is. Her training in field medicine/dressings Will Not Cut It on this one.

Now, Kallus has a contingency--he always has contingencies, he loves contingencies--but Mirah doesn’t know his medical contingency and he’s too unconscious and bleeding-out to tell her.

She can’t take him into an emergency room, obviously, but there’s an urgent care center close by. And Orryn’s stuff is still in the van. Which means she can hack into their records find out who’s coming off shift--because there will be someone coming off shift--and stick a gun in their face.

Which is exactly what she does.

She drags the doctor into the van and points her at Kallus.

“Fix him,” she snaps, but she stops pointing the gun at her at this point--she needs her attention elsewhere to drive and fend off Division agents in pursuit, among other things, and surely this doctor will be overcome by that whole Need To Heal thing. Hippocratic oath. Whatever.

Doctor stares at him. “He needs a hospital, I can’t--” Even as she moves towards him.

(Because there’s that whole Need To Heal thing. Hippocratic oath. Whatever.)

Mirah starts the car. “I’m not gonna tell you again.” She tosses the doctor their first aid kit--which is pretty Extensive. Not on the level of the one at the safehouse, but still impressive. “Anything you need that’s not in there, I’ll get at a pharmacy. Now. Do your damn job or I swear to God.”

The doctor looks at Mirah one last time, then turns her attention to Kallus, and opens the kit.

“Good,” Mirah says.

(And then, while the doctor is stabilizing her dad, as soon as she can pull over for a second, she gets rid of her tracker. She has the standard one, in her thigh.)

(And probably kills a Division agent or two pursuing them along the way…)

When the doctor has finished patching Kallus up as best she can with the supplies on hand and what Mirah stole from a convenient pharmacy, she says, “He really should be in a hospital. He needs a transfusion, and should be on IV antibiotics. And I think there was damage to his femur I couldn’t fix without imaging.”

“I’ll take that under advisement,” Mirah says. Note to self: rob a blood bank. And a hospital. Saline won’t cut it. I wonder how hard X-ray machines are to steal…

“I’m guessing you know how to change the dressings, and how often to do it,” the doctor says.

“Obviously,” Mirah says. She grabs a handful of money, and shoves it at the doctor--she did her job, she should be paid for it; people should always be Appropriately Compensated for the things they do and in this case that means actual money--as well as the badge she’d pulled out of the doctor’s purse. “You can go. Oh, and, Doctor Sloane? This never happened. You never saw us.”

“Right,” she says.

“Because if you say anything,” Mirah says, “I will hunt you down and kill you. Clear?”

“…crystal,” she says, and takes the money and walks away.

Mirah takes a few more distracting turns (with a couple pit stops for those last few Necessary Supplies), a very roundabout route, and eventually makes it to the safehouse. She gets Kallus set up as comfortably as she can, under the circumstances, on one of the beds, manages to take thirty seconds to check for any messages from Shamie or Orryn, and then curls up in a corner and just…melts down.

Like I said Mirah’s Worst Nightmare.

Let’s check back in with Shamie, who is about to have an extremely rough several days.

Because they get to go spend some Quality Time with Thrawn in full interrogator mode.

And they get the works--torture, hallucinogens, manipulation, everything. To figure out how much they know about Mirah’s compromised loyalties, back to Orryn and everything.

When that comes up, they repeat their older story--that they spotted Mirah pursuing Orryn and the guard, and followed. They got there, there was shooting, and they were sure it was Orryn, or the guard, but maybe it was Mirah. They know she killed the guard, and Orryn was never good at combat skills, just tech…

After somewhere between three days and a week of this, Thrawn can’t get Shamie to admit anything incriminating, and leaves them in a cell to report back to Pryce.

“I would estimate there’s somewhere between a twenty and fifty percent chance that Mirah managed to turn them,” he says.

“So, we cancel them,” Pryce says.

“We could,” Thrawn says. “But that is not my recommendation.”

“Oh?”

“I recommend surveillance,” he says. “My prior sessions with Shamie indicate that they’ve had very little human connection or affection in their life. Even we, for all we provide them, have a tendency to view our recruits more as tools than as individuals. It is absolutely within their makeup to latch on to the first person to treat them and value them as an individual. Which may mean they joined Mirah and Alexsandr’s crusade--or may mean that affection blinded them to things they should have seen in Mirah. If the former, they will lie low for a while, but eventually grow complacent and reach out to their partners. If the latter, they will redouble their efforts to prove their loyalty. And their skillset is not one we can replicate at this time--there’s one recruit showing a certain promise, but they’re very new, at least a year away from graduation. Assuming that particular recruit actually lives up to their potential.”

“So,” Pellaeon cuts in, “letting Shamie live, either way, we gain something valuable.”

“Precisely,” Thrawn says.

Pryce considers for a moment. “Very well, I’ll bow to your expertise. Shamie can return to their prior status. Add more cameras to their apartment before sending them home. And I want to upgrade their tracker.”

“I agree,” Thrawn says. “This would be an excellent time to test out the kill chip program.”

So, Shamie is kept in medical for another day, to have the surgery for the new implant and patch up some of the more significant damage from their interrogation.

They use one of the Contingencies to send a quick message to Mirah and Kallus, confirming they’re alive, and that they have a new tracker and may not be able to keep in regular contact for a while.

So! Let’s see what became of Orryn in the meantime, shall we?

And to do that, we actually have to jump back five years, to the night that made Kallus leave Division and vow to bring them down.

Zeb was military, special ops. He met Kallus when the latter was living on extended cover, and Zeb was about to get out.

They met in some kind of dojo/gym/whatever, and had one of Those sparring matches.

(You know the ones I mean. Where it’s like 30% fight and 70% foreplay?)

They danced around the issue for a while; Zeb knew Kallus works for the government somehow, and is pretty sure he’s either CIA or NSA under some kind of NOC (non-official cover). Eventually, though, they get together.

They have about six months, with Kallus staving off Division as best he can, and Zeb going through the process of finishing out his military service/resigning his commission--as soon as he wraps up one last investigation--and then he proposes.

And, yeah, he thought about waiting until he was completely out, but then he figured--there’s only so much time in a life, and why waste it?

Kallus is getting everything together so the two of them can disappear, when the Cleaner comes.

I’m…not sure exactly how this all works, so we’ll handwave all this. Basically, each walks away thinking the other is dead, and can credibly believe this without a body.

I think probably Kallus saw Zeb go over a cliff or something after getting shot, and Zeb found a whole heck of a lot of blood when he climbed back up to where he’d fallen from, and figured it was Alex’s.

Ooooh, better idea--while he’s climbing back up to help Alex--he thinks this attack has to do with him. With that last investigation, which was actually into some kind of Hinky thing that was either Division or Gogol…

And now the building is on fire. And Alex was still in there.

He tries to run in, but the building is too unstable, and the entrance collapses in front of him. Burying Alex--or whatever’s left of him--completely.

Kanan finds Zeb kneeling in front of the rubble, and takes him home.

He and Hera patch Zeb up, and basically explain what they do--which is something to do with trying to uncover groups like Division; essentially terrorist/assassination/murder-for-hire organizations that operate under a thin veneer of government officiality.

“Modern-day privateers,” Hera says. “Only we’re not at war, and these people commit atrocities at least as awful as the ones they’re supposedly trying to avert.”

“We work in secret,” Kanan adds. “Because when we try to work out in the open…”

(Yeah, this is how Depa died in this AU. She started this operation, possibly with Cham Syndulla, and things went Badly.)

“We think you caught on to the operations of one of the groups we’re trying to identify,” Hera said. “We don’t have a name for them, but they’re US-based, with ties all over the world.”

“Most of…most of what I had on ‘em was in the house,” Zeb says.

“So, we start again,” Kanan says.

“But…at this point, Zeb, you’re legally dead,” Hera says. “We all are. You won’t have the access to intel that you used to.”

“I don’t care,” Zeb says. They killed my fiancé. What does it matter if they killed me, too? “I wanna bring them down.”

Kanan smiles, and offers him a hand. “Welcome to the Ghost Crew.”

So, for the next two years or so, the Ghost Crew, along with Zeb, does more or less the same thing Kallus has been doing--try to suss out Division operations and interfere with them as best they can.

Of course, they don’t have insider information.

They don’t even know the name of the organization they’re hunting.

Plus, Division isn’t their only target, even if it’s the one Zeb’s most interested in. They also interfere with Gogol when they catch on to their missions, and a few other organizations throughout the world.

So there’s only so much they can do, and while they are certainly a nuisance to Pryce et al, they don’t have the same level of impact that Kallus does when he comes out swinging.

Naturally, things shift a little when a mission goes slightly less than as planned.

It’s mostly under control--it was primarily surveillance at that point; Zeb was in a restaurant scoping out their target. Unfortunately, one of said target’s bodyguards ID’d him; maybe not specifically as Ghost Crew but certainly as a Threat to their principal.

That’s about when the shooting started.

Zeb can’t get to the front door; the bodyguards now actively trying to both kill him and extract their principal are in his way; so he heads for the kitchen instead.

Yeah, he could try to pursue and complete his objective, except it was a capture mission, not a kill, and he can’t get through that many guards and get out with the target. Not by himself.

He yells at the staff to get down and stay down, and most of them listen. There’s a couple of cooks, a waiter who was grabbing a couple plates to run out, and a kid washing dishes.

Of course, Zeb loses his footing somewhere along the line and skids. He recovers fast, but the closest guy chasing him did not have that problem and is too damn close for--

--or Bad Guy could get smacked in the face with a soapy cast-iron skillet, courtesy of Dish Washing Kid.

Split second to consider the consequences, but there are two other shooters in pursuit; so Zeb does the sensible thing and grabs the kid so she doesn’t get hurt, and finally makes it to the exit. Steals the first convenient car he sees, and books it.

Once he’s pretty sure they’ve lost pursuit, he turns to the kid, who’s--shit, he’s not good at guessing kids’ ages. Maybe twelve? Shit--anyway, an actual kid, which complicates things.

“Uh. Sorry about back there,” he says. “Listen, I’ll take you back to your parents in a couple hours, after the heat’s died down, I promise.” Pretty sure the bad guys aren’t gonna hunt you down if they couldn’t grab you right then and there…

“Foster parents,” she corrects. “They’re okay, I guess, but it’s not like they actually pay attention to me. They own the restaurant.”

“I should still get you back to them,” he says. “Better for you in the long run, kid.”

“Hanny,” she says. “My name’s Hanny.” She looks at him expectantly, but he doesn’t respond in kind.

“Right,” he says instead. “In the meantime, uh…” He pulls off--they need to switch cars anyway--and takes a second to text Hera.

“So I accidentally kidnapped someone.”

“…accidentally.”

“Yeah, there was shooting, had to run through the kitchen, she hit a guy with a frying pan, couldn’t leave her there.”

“Right,” she responds, after a few seconds where he can practically hear her rolling her eyes. “How much of a fuss is she making?”

“Uh. None at all, actually.”

“All right. Bring her here, we’ll figure out how to handle this later.”

“Thanks, I owe you another one.”

He gets Hanny back to the safehouse he and the Ghost Crew are currently using.

Hera glowers at him for a minute, then makes sure Hanny is settled in an inner room before going out to have A Word.

“Zeb? That’s a child. An actual child.”

“Yeah, I know,” Zeb says. “Still couldn’t exactly leave her there. I’ll take her back to her parents…well, foster parents…”

“Our rule is, we don’t hurt kids!” Hera says.

“Does she look hurt?” Zeb says. “Look, this wasn’t my fault. I went through the kitchen, she got involved all on her own. Not like I told her to bash the guy over the head with a skillet!”

“I know,” Hera says, and takes a breath. “I know, sorry. I shouldn’t’ve snapped at you. But you need to take her back sooner than later. Tonight, if you can.”

Zeb nods. “Uh. Soon as I get her to actually tell me who her parents are. She said they own the restaurant, but…”

“Yeah, you probably don’t want to go back there.” She considers a minute. “I’ll see what I can dig up, get you an address.”

“Good,” he says.

“Why can’t I stay here?” Hanny asks, from the door.

“…because you’ve got parents--”

“Foster parents.”

“Who are probably worried about you,” he finishes.

Hanny snorts. “No, they’re not. They’ve got six of us, and mostly use the money they get from the state to keep their shitty restaurant afloat. They won’t miss me.”

“That’s a shitty situation, I get it,” Zeb says. “It’s still better than staying here.”

“Why?” she demands.

“Because I’m legally dead, for one thing,” he says.

“But you’re not actually dead,” she points out.

“I also do a lot of really dangerous things,” he says. “What you saw in that kitchen back there? Ordinary Tuesday for me.” Which is, yeah, a bit of an exaggeration, but…

She rolls her eyes. “Not like I’m asking to come into another shootout with you. Just stay with you instead of the Smiths.”

“Why do you want to stay with him?” Hera cuts in. “And ‘because he’s not the Smiths’ isn’t a good enough answer.”

Hanny chews that over for a minute. “I like him,” she says. “He actually gives a damn about something other than his stupid restaurant, or self-image, or whatever. And he apologized for kidnapping me, which is sort of weird, but nice, I guess? I don’t know, I just do.”

“…that whole bit about doing dangerous things,” Zeb says. “I can’t really look after you.”

She rolls her eyes again. “I’ve been looking after myself for ages anyway. Besides. I’m seventeen.”

He and Hera stare at her.

“…would you believe fifteen?”

Zeb’s less sure about that one, but the look on Hera’s face is answer enough.

“Okay, thirteen, but still. Plus, I cook. I’m really good at it, too. Especially when I have access to decent knives. I’m guessing that’s not a problem here?”

Well, okay, it’s not like they have a lot of kitchen knives floating around, but he could--

…shit.

Zeb turns to Hera. “…sorta running out of counter-arguments here…”

Hera looks from him, to Hanny, and back again. “…fine. I’ll babysit when you’re out in the field.”

Jumping back to the present!

So, Zeb doesn’t actually spot Kallus at this point.

Or, rather, he sees that another party is involved, and does out of the corner of his eye spot the guy going down and then Division agents running at him, but not enough to actually identify him.

He alerts his team to the presence of the Third Party--who they’ve been aware of, since Kallus and his team went active a few months ago.

(It was Sabine’s idea to nickname the team Fulcrum. Since they seem to be a pressure point that really gets to the Shadow Agency they’re chasing, and might be enough pressure to move the lever and make actual progress…)

(Look, it made sense in her head at the time, whether or not the others bought the reasoning, and it stuck.)

Of course, they’re not sure if Team Fulcrum is actually on their side, or just looking to cause Generalized Chaos. Or take Shadow Agency down to take its place. After all, they seem to have an almost personal vendetta against the Shadow Agency and some of the tactics they’ve used…

Ezra and Kanan slip around to the Fulcrum van, and find Orryn inside. They see this sweet kid, assume he’s a hostage, and extract him. There’s no way their team will get through the firefight between Division, Mirah, and the reinforcements intact, so Kanan calls Zeb back, they get Orryn into their vehicle, and they go.

They get Orryn back to their base, and he makes it Very Clear that he was not, in fact, a hostage.

“The people that had you in that van--”

“Were not Division,” he says. “They’re the ones who rescued me from Division, after I was recruited.”

“…I’m sorry,” Hera says. “We made a mistake. Division--they’re the government agents who were attacking that building back there?”

Orryn blinks. “…you didn’t know that?”

“We’ve never had a name for them,” Kanan says. “Maybe we should start from the beginning. I’m Kanan, this is Ezra, Hera, Zeb, Sabine.”

“Orryn,” he says. “…you’re trying to bring Division down, too?”

“Damn right we are,” Zeb says.

“…okay,” he says, and fills them in on what he knows.

Which is, comparatively, not all that much. He didn’t see too much of the internal structure--he wasn’t there for long enough--but they have names and so on to attach to them.

He tells them how Division recruits people in their late teens/early twenties, and trains them as assassins. He tells them how Mirah went in as a double agent, and she and Shamie and Kallus broke him out. He tells them how they tried to get him into hiding, but he offered to stay and help with their tech, which is what led them here.

(He doesn’t, of course, know Kallus’s real/full name--not something shared readily; and even if it was, that might not be the full name Zeb knew him under, so Zeb remains in the dark.)

(Part of why Orryn’s being so open about this is because he’s gotten a pretty good idea of the kind of team Hera and Kanan are running here; he also…it’s something to focus on other than the Very Strong Probability that Kallus is dead, likely Mirah with him, and Shamie, and…)

(On the other hand, if his new family is somehow still alive, they could use all the help they can get. And maybe Kallus would’ve been more cautious, and Mirah would’ve been more suspicious, and Shamie would’ve held back a little more, but Orryn knows how hard this fight will be, and how much they need genuine allies. And so he makes the first move/takes a leap of faith.)

So, to sum up the last few sections before we move on, here’s where we stand after the FUBAR mission where Kallus finds out Zeb is still alive:

Kallus has been badly hurt--near-fatally--and is more or less out of commission for the foreseeable future; not to mention whatever long-term/permanent damage he might have sustained.

Mirah’s cover is blown, and while she pulled herself together after her meltdown once Kallus was safe, she’s still teetering a little on the edge, especially as more and more time goes by without hearing from either of her siblings.

Shamie is fighting desperately to maintain their cover, still deep in Division, but now with little to no support.

Orryn is with Zeb and the Ghost Crew, with no idea if any of his family is still alive, and missing a few Key Pieces of Information that might help smooth things over.

(Yeah, this day went Super Well for everyone.)

After a couple days, though, a glimmer of light at the end of the tunnel--Kallus wakes up.

Okay, technically, he’s sort of half-woken up a couple times, but this is the first time he’s been lucid enough to actually process being awake and/or interact with Mirah.

She sees him trying to sit up and is instantly there.

“Stay down, you’re hurt.”

He sinks back without too much argument, and she takes a second to make sure he’s really awake, really back with her, and then, as people with her particular personality and background are likely to do, covers up her fear with “How dare you.”

“Mirah…”

“You got yourself shot! You froze!”

“I know, I--”

And then the look on her face, she’s clearly just barely holding back from bursting into tears (which, she’s done enough of that over the past three days damn it) and he just…wordlessly holds out his arms, offering a hug.

Very, very carefully, she curls up next to him and clings, and she does burst into tears at that point, and stays there until she’s cried herself out.

“…sorry,” she says, when she gets her breath back.

“It’s fine,” he assures her. “And…so am I. For scaring you.”

She nods. “I know it wasn’t on purpose.”

He laughs a little, which is a mistake, because that hurts, but manages to get out, “when I get shot on purpose, it’s generally not this…bad.”

“I know,” she says, then hesitates before blurting out, “Iloveyou.”

He’s taken a little bit by surprise--he was her handler as much as her friend, and that’s not exactly conducive to…but he can’t deny that he’s come to think of her as a favorite niece, or maybe even a daughter, and…

Between being caught off guard, and the pain, and the bloodloss, and the drugs she’s probably got him on, he can’t find the words to respond.

So, of course, she tries to backtrack.

He cuts her off, “love you, too, Mirochka.”

(LOOK fandom has decided he’s a Space Russian ANYWAY so for this AU either one or both of his parents was a first-generation Russian immigrant so FAKE RUSSIAN DIMINUTIVES FOR EVERYONE. Also it makes me smile. So there.)

She brightens and clings again. Very, very carefully.

But he can already feel the room start to spin and blur at the edges. “Probably gonna pass out again. Don’t be afraid.”

“Okay,” she says. “Just don’t die.”

“Of course not,” he says, already fading. “Still have work to do.”

“Yeah, well, you’re not allowed to die when we’re done, either.”

“Right,” he manages to say, before he’s out again.

The next time he’s fully conscious and lucid is just after Shamie finally managed to send word they’re alive.

Which is, naturally, his first thought. To ask about Shamie and Orryn.

Mirah tells him--Shamie’s at least alive and free enough to make contact, but Orryn is still missing.

Kallus, at this point, is half-convinced he hallucinated Zeb--it would make more sense, obviously; Zeb is dead, he knows that, he saw him die, and yet…

On the other hand, he finds himself desperately hoping it wasn’t a hallucination, for more than just his personal needs. If Zeb has Orryn, then he knows Orryn is safe.

“I tried to get him,” Mirah says.

“I know,” he says. “It wasn’t your fault. None of this was.” It was mine.

“What happened?” she asks, and the question had to come sometime, but he’s not sure he can explain. Not sure he should, as on-edge as she is already.

But she’s asking, so he does the best he can.

“I thought I saw…someone,” he says.

“…interesting pause there…”

“A ghost.”

“…cryptic. Are you gonna keep doing that, or…?”

He looks away. He can’t bring himself to say his name. “It couldn’t have been…I know it couldn’t have been, but I saw him, I was sure, and for a moment, I…I lost control. Again.”

I let you all down.

“…again?”

He struggles for a moment, then says, “I told you, before you went into Division…I told you why I left, didn’t I?”

It takes her a minute to get it. “…oh.”

“I only…I only saw him for a moment, and I may have been seeing things.” He takes a shallow, shaky breath, and blinks rapidly for a moment. “But if it was real, and Orryn’s with him, then he’s safe. I am certain of that.”

Mirah nods. “Then I’ll go find out.”

“Be careful,” Kallus cautions. “Division will be out in force, looking for you. And Shamie can’t--they have to keep their head down. Even if they’ve managed to satisfy Thrawn for now--” He starts to get up, because he needs to hit the ground running on this one, pain and shakiness be damned--

“Don’t you dare,” Mirah snaps, pushing him back. “I’ll be careful. Trust me. Papa.”

“I do,” he says; his head is spinning again and he’s gone chalk-white. “Just…don’t get overconfident.”

“I won’t,” she promises. “Go back to sleep. I’ll text every hour.”

“Please,” he says.

“I will,” she promises, and by the time she’s out the door he’s unconscious again.

Of course, by the time she gets back, he’s somehow managed to muster the strength to get himself over to the computer.

“What did I say?” she says, annoyed.

“I did sleep, for a while,” he says. A little breathless, but he’s still conscious, and it doesn’t look like he’s torn any of his stitches, which is probably a goddamn miracle.

(Of course, they are long overdue a miracle or two.)

“I found footage of the incident,” he says. “Target had security cameras all over. I wanted to see if…see if I could track Orryn that way.”

“And?”

He shakes his head. “But I can be sure Division didn’t take him. I accounted for all of them.”

“That’s good.”

“Yes,” he says, then hesitates. “Nothing more from Shamie, which…I don’t know. You find anything?”

“Maybe,” she says, and hands him a blurry photo, of Orryn--with Zeb.

The world spins around him again, just like it did back in that firefight, because there’s no mistaking it this time.

Mirah mistakes his reaction for him being about to pass out again; he vaguely hears her mention going to kidnap Dr. Sloane again; he cuts her off.

“No, it’s…it’s him.”

“Oh!” She considers for a moment. “Good. I’ll go get him.”

He nods; he can feel his heart beating erratically and knows he should probably do something about that--relaxation exercise, get horizontal, something--but first thing’s first. “Tell…no.” He can’t think of a good verbal code, but he has something even better.

Using the chair to hold himself up and keeping as much weight off his injured leg as possible, he starts over to the wall.

“Let me--” Mirah starts.

“Wall safe,” he says. “Keep forgetting to program your fingerprints.”

She makes a face. “And you’ll go to bed as soon as you get whatever it is?”

“Yes, fine,” he says. He makes it to the safe, and opens it, pulling out a fist-sized stone and handing it to her. “Show…show him this. He’ll know you’ve seen me.”

“I will. Now, bed.”

“Right,” he says. But his head is spinning and it seems so very far away right now. I possibly overdid it. “I’m just going to…sit here for a moment first. Catch my breath.”

“Fine,” she says. “I’ll be back soon.”

“I know.”

There is, of course, a slight problem with sending the meteorite instead of some kind of verbal message. One that, if Kallus had been firing on all cylinders, so to speak, he would’ve figured out.

A verbal message can’t be pulled off a dead body, after all.

…yeah, Zeb pulls a gun on Mirah when she shows up.

She restrains herself from responding the way all her training has told her to respond to a gun in her face, because she knows how important Zeb is to Kallus. “Rude,” she says instead.

Zeb snarls at her. “Where the hell did you get that.”

“From Papa,” Mirah says, like it should be obvious. “Are you going to let me in?”

Papa? Zeb had never imagined the monsters that killed Alexsandr--who did the kind of things Orryn described--would have children. “…no,” he says. “You’re going to take me to Papa.”

It’s the best, most solid lead he’s had in forever, more concrete than Orryn in terms of tracing back to the specific people who killed his fiancé, he finally has an actual agent, a string to pull to unravel Division and end them.

“Well, yeah,” Mirah says, because that is the plan. But not right now.”

Zeb glares at her. “No. Now.”

Mirah sighs. “ORRYN!”

Orryn, who heard the commotion and was already on his way, joins Zeb at the door. “She’s okay, Zeb. Really. This is Mirah, I told you about her?”

Zeb is…not at all sure what to make of all this. But he lets her in while he tries to figure it out.

(Keeping her covered with the gun, of course. As much as he can when the first thing she does is wrap Orryn in a flying tackle hug.)

“I’m so glad you’re okay,” Orryn says, clinging back so hard. “I was worried.”

“You were worried!” Mirah says. “You know what you’re supposed to do in a firefight! Keep your head down, and wait for Papa to come get you!”

“I know,” Orryn says. “But I saw him go down, and then…” I got grabbed, there wasn’t a whole lot I could do.

Mirah nods. “I already yelled at him about that.”

Which is not what Orryn would’ve done, but he knows his sister, so he’s not surprised. “And…and Shamie, are they with you? Are they okay?”

“They’re alive,” Mirah says. “They got in touch. But they’re still undercover. We’re working on it.”

“Touching as this reunion is,” Zeb interrupts, “you need to tell me where the hell you got that rock.”

“I already told you.”

“Not enough.”

“Well, then ask,” Mirah says. “I don’t know what you know.”

“Who the hell is Papa, and how the hell did he get that meteorite?” Zeb asks.

“No idea where he got it,” she says, which is true. “He just told me to give it to you.”

Zeb stares at her, for a long moment. “What the hell kind of sick joke--”

“What?” Mirah says. “Explain, because I have no idea what the hell you mean.”

“He’s taunting me,” Zeb says, flatly. “Whoever he is.” ...on the other hand, that means I’m close…or they know I have Orryn. He frowns, then shakes his head. “But to use this to lure me out…”

Now it’s her turn to stare. “Lure you? You’re the one who demanded I take you places!”

“Because you turn up, out of the blue, on my damn doorstep, holding that!”

“Because Papa told me to!” she says. “What’s so important about it, anyway?!”

“It’s something I gave to--” He stops. “Your people, Division, they took it off him after they killed him. I’ve spent the last five years trying to track down the bastards who did it.”

And SUDDENLY EVERYTHING IS CLEAR.

“You didn’t see him,” Mirah realizes.

“…what.”

“Okay,” she says. “We can go see Papa now. But leave your gun behind, he’s been shot enough this week.”

“No, seriously, what the hell,” Zeb says. “Saw who?”

“Papa,” she says. Obviously.

“You still haven’t told me who that is!”

“Because I love him, but he’s sometimes a secretive jerk and I don’t know his full name and that’s embarrassing, okay?”

Zeb just stares at her for a moment.

Mirah sighs, exasperated. “Orryn, do you know Papa’s full name? I don’t have any pictures, and I don’t want to wake him up by calling.”

Orryn shakes his head. “Never had that much access to Division’s computers, and you know he doesn’t talk about that stuff. …Shamie might know, but…”

“I’ll text,” she decides. “They won’t get it until it’s safe.”

“Like hell I’m waiting for that,” Zeb says. “Take me to him. Now.” “First, leave the gun behind,” Mirah says, and there is No Room For Argument in her face or her tone.

Zeb considers this for a moment.

He’s dealing with one guy who’s apparently been shot all to hell, and one baby agent…he’s got the raw physical strength to overpower her if it comes to that. Besides, she didn’t say anything about other weapons.

“Fine,” he says, and ostentatiously puts both the gun he already had out and the backup from his boot on the table.

“Thank you,” she says. “Orryn, you coming?”

Orryn hesitates for a second. “…someone should probably stay with Hanny.”

“Who’s Hanny?”

“My kid,” Zeb says. “…kinda. Long story. Can we go?”

“Sure,” Mirah says. “Hanny can come, too.”

“Hell no,” Zeb says. “I don’t bring her into potential danger if I can avoid it.”

“If you say so,” Mirah says. “Just a suggestion.”

So, Orryn and Hanny stay back at Zeb’s place. Mirah texts Kallus to let him know they’re coming.

He. Uh. Wakes up on the floor by the wall safe when his phone buzzes. Never quite made it back to bed…oops.

Part of him thinks he should probably correct that, but on the other hand, standing up sounds like Work right now. He’ll just…wait here. Gather his strength.

Oh, right, I should text back. “Fine, see you soon.”

As they approach, Mirah once again warns Zeb that Kallus has been shot, so he is not allowed to get him worked up or let him out of bed.

“Yeah, you mentioned.”

“It bears repeating,” she says. “And he is not allowed to die.”

“Copy that,” Zeb says, though he makes no promises. Whoever Papa is, he had Alexsandr’s meteorite, which means he Knows Something about the people who killed him.

She opens the door to the safehouse. “PAPA YOU HAD BETTER BE IN BED.”

…well, at least he hasn’t moved from where she left him last?

Mirah gives him her best Aggrieved and Disappointed Face.

“…I think I fell asleep here,” he says, wearily.

And then Zeb has a Moment.

Because he couldn’t quite see Mirah’s papa from this angle.

But he knows that voice.

“Did I or did I not tell you to go back to bed,” Mirah says, but she knows it’s gonna be a lost cause for at least a few minutes. “…I’ll lecture you later.”

“Alex?” Zeb says. Whispers. It takes him a few seconds to actually get the name out and it comes out strangled and disbelieving.

And even though he already knew Zeb was alive, he’d seen him in person and then the picture, something about it…he’s here now, it’s real--

Fortunately, before Alex can try to get up, Zeb is right there.

“You were…you were dead, I thought--”

For his part, Kallus cannot form words right now. He just reaches up, hand shaking, to touch Zeb’s face.

(Mirah, in the background, discreetly texts her siblings with an update.)

(Orryn, upon reading the text, asks Hanny if she’s ever seen The Parent Trap.)

(“Because I think your spy dad and my spy dad used to be together. Wanna go join them?”)

(Hanny doesn’t need to be asked twice.)

Zeb, at that point, just scoops Kallus up and, very gently, puts him back in the bed.

“Oh, good,” Mirah says. “Now we need to keep him there.”

“No arguments here,” Zeb says.

And this had better not be a dream, he adds, in the privacy of his own mind.

Of course, there’s a lot more catching up to do from there, and a creepy organization of spysassins to take down, but I think we got enough here for one outline, lol. XD Future developments, of course, involve Team Fulcrum (who keep the nickname because Why Not) teaming up with the Ghost Crew to actually take down Division and shoot Pryce in the face; getting Shamie’s kill switch removed; and then…whatever adventures the Family of Spies might have in the future. Maybe head down to Miami, run into another team of former spies. Or up to Boston, run across a team of thieves…

The point is, they’ve found each other again. The rest…well, the rest is just Details.

#shadowsong writes star wars #shadowsong writes crossovers #shadowsong writes self-indulgent bs #au outlines for the win #tigerkat24

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savipra · 8 years ago

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7 NLP Meta-Programs for Understanding People

“Everything that irritates us about others can lead us to an understanding of ourselves.” – Carl Jung

In Neuro-Linguistic Programming or, NLP, meta-programs are the keys to the way you process information.

NLP meta-programs are basically how you form your internal representations and direct your behavior.

In Unlimited Power: The New Science Of Personal Achievement, Tony Robbins writes about meta-programs that people use to sort and make sense of the world.

7 NLP Meta-Programs

Here are the 7 NLP Meta-Programs

Toward or Away

External or Internal Frame of Reference

Sorting By Self or Sorting by Others

Matcher or Mismatcher

Convincer Strategy

Possibility vs. Necessity

Independent, Cooperative and Proximity Working Styles

1. Toward or Away NLP Meta Program

You can use this lens for understanding whether somebody drives from pain or gain. You can also use this for looking at yourself. Do you find that you move towards pleasure or away from pain?

Robbins writes:

“All human behavior revolves around the urge gain pleasure or avoid pain. You pull away from a lighted match in order to avoid the pain of burning your hand. You sit and watch a beautiful sunset because you get pleasure from the glorious celestial show as day glides into night.”

2. External or Internal Frame of Reference NLP Meta-Program

If you ever give a compliment and it seems like somebody doesn’t believe you, it might be because they are using an internal frame of reference. You also can check this in yourself. For example, do you put more stock in how you rate your performance or do you look to feedback from others?

Robbins writes:

“Ask someone else how he know when he’s done a good job. For some people, the proof comes from the outside. The boss pats you on the back and says your work was great. You get a raise. You win a big award. Your work is noticed and applauded by your peers.

When you get that sort of external approval, you know your work is good. That’s an external frame of reference. For others, the proof comes from inside. They ‘just know inside’ when they’ve done well.”

3. Sorting By Self or Sorting by Others NLP Meta-Program

In this case, do you first think about what’s in it for you, or do you think about what’s in it for others?

Robbins writes:

“Some people look at human interactions primarily in terms of what’s in it for them personally, some in terms of what they can do for themselves or others.

Of course, people don’t always fall into one extreme or the other. If you sort only by self, you become a self-absorbed egotist. If you sort only by others, you become a martyr.”

4. Matcher or Mis-matcher NLP Meta-Program

If you ever find somebody that always seems to have to disagree with you, now you know why.

Robbins writes:

“This meta-program determines how you sort information to learn, understand, and the like. Some people respond to the world by finding sameness. They look at things and see what they have in common.

They’re matchers.

Other people are mis-matchers — difference people. There are two kinds of them. One type looks at the world and sees how things are different … The other kind of mis-matcher sees differences with exceptions. He’s like a matcher who finds sameness with exceptions in reverse – he sees the differences first, and then he’ll add the things they have in common.”

5. Convincer Strategy NLP Meta-Program

This meta-program involves what it takes to convince someone of something.

Robbins writes:

“The convincer strategy has two parts. To figure out what consistently convinces someone, you must first find out what sensory building blocks he needs to become convinced, and then you must discover how often he has to receive these stimuli before becoming convinced.”

6. Possibility vs. Necessity NLP Meta-Program

You might know some people that are minimalists or you might be a minimalist yourself, and focus on just what you need. On the other hand, you might be a seeker and always looking to expand your opportunities and possibilities.

Robbins writes:

“Ask someone why he went to work for his present company or why he bought his current car or house. Some people are motivated primarily by necessity, rather than by what they want. They do something because they must.

They’re not pulled to take action by what is possible. They’re not looking for infinite varieties of experience. They go through life taking what comes and what is available. When they need a new job or a new house or a new car or even a new spouse, they go out and accept what is available. ‘

Others are motivated to look for possibilities. They’re motivated less by what they have to do than by what they want to do. They seek options, experiences, choices, paths.”

7. Independent, Cooperative and Proximity Working Styles NLP Meta-Program

By understanding this pattern, you can figure out where your most enjoyable work environments would be.

Robbins writes:

“Everyone has his own strategy for work. Some people are not happy unless they’re independent. They have great difficulty working closely with other people and can’t work well under a great deal of supervision. They have to run their own show.

Others function best as a part of a group. We call their strategy a cooperative one. They want to share responsibility for any task they take on. Still others have a proximity strategy, which is somewhere in between. They prefer to work with other people while maintaining a sole responsibility for a task. They’re in charge but not alone."

Additional Considerations

Robbins provides the following suggestions:

All NLP meta-programs are context-and stress-related

There are two ways to change NLP meta-programs. One is from a significant emotional event. The other way you can change is by consciously deciding to do so.

Use NLP meta-programs on two levels. The first is a tool to calibrate and guide your communication with others. The second is a tool for personal change.

Constantly gauge and calibrate the people around you. Take note of specific patterns they have for perceiving their world and begin to analyze if others have similar patterns.

Through this approach you can develop a whole set of distinctions about people that can empower you in knowing how to communicate effectively with all types of people.

Become a student of possibility. NLP Meta-programs give you the tools to make crucial distinctions in deciding how to deal with people. You are not limited to the meta-programs discussed here.

Key Take Aways

Here are my key take aways:

Use meta-programs to understand yourself and others. Meta-programs helps you understand how people sort and make sense of the world. They also help you understand your own values, beliefs and behaviors.

Remember that people use a blend of meta-programs. It’s not this or that, it’s a spectrum of possibilities. It’s a tool for understanding how or why people behave and adapting your own behaviors to improve communication. They aren’t a tool for stereo-typing or pigeon-holing.

Change your own limiting meta-programs. If you have a way of processing the world that’s limiting your success, find a way to consciously adapt. Identifying your own meta-programs you use is a start. Once you have awareness, you can see how this shows up.

Ultimately, I think knowing how people work, helps bridge gaps.

It can also lead you to self-understanding and the better you know yourself, the better you can drive yourself.

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biofunmy · 6 years ago

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Driverless Cars May Be Coming, but Let’s Not Get Carried Away

“Sometime next year,” Elon Musk says, “you’ll be able to have the car be autonomous without supervision.”

“None of us have any idea when full self-driving will happen,” counters Gill Pratt, an expert in robotics and the director of the Toyota Research Institute.

Beyond Mr. Musk, who has said twice this year that Tesla could have a million “robotaxis” on the roads next year, few experts in autonomous cars believe that the technology is ready to safely chauffeur occupants in any and all driving conditions. And that’s before the regulatory hurdles, including a quaint-seeming 1971 New York law that requires at least one hand on the wheel.

Instead, for the foreseeable future, there are Advanced Driver Assistance Systems. Think of them as a co-pilot, not the Autopilot of Tesla’s marketing parlance but a wingman that amplifies human skills instead of replacing them.

These building blocks of autonomy are becoming common on even the most affordable cars: electronic stability controls, certainly, but now radar, cameras and other sensors that perceive their surroundings and automatically accelerate, stop, steer, follow lanes or take evasive action. And every major carmaker in America has pledged to make automated emergency braking standard on all new models by September 2022.

Global giants like General Motors, Toyota, Ford and Volkswagen are fully engaged in the self-driving race against the likes of Tesla, Uber and Waymo, a unit of Google’s parent company, and are loath to be outmaneuvered by Silicon Valley disrupters. But traditional automakers are also hitting the brakes, as premature promises run headlong into reality — what Mr. Pratt calls the current “trough of disillusionment” in autonomy.

A growing consensus holds that driver-free transport will begin with a trickle, not a flood. Low-speed shuttles at airports or campuses may be the early norm, not Wild West taxi fleets through Times Square. Operational boundaries will be enforced by the electronic leash of geofencing.

Toyota is among the many companies backing that more cautious, two-track approach. Mr. Pratt, who ran the vaunted robotics program at the Defense Advanced Research Projects Agency, or Darpa, recalls tossing and turning on the night in 2015 when he signed a contract to lead Toyota’s $1 billion research arm for artificial intelligence and robotics.

Toyota’s cars alone, he figured, log perhaps one trillion miles of annual travel around the globe. Making a robocar perform in controlled demonstrations is easy, Mr. Pratt says, such as having it effortlessly avoid hay bales tossed in front of it. Making a robocar so foolproof that consumers and automakers can trust it with their lives, including in one-in-a-billion situations, is very different.

“Ever since, we’ve tried to turn down the hype and make people understand how hard this is,” he said.

That’s not preventing companies from trying. Toyota’s Chauffeur technology fully intends to create autonomous cars for corporate fleets. But using 80 to 90 percent of the same software, its Guardian concept blends inputs from man and machine.

General Motors’ Cadillac is also working to keep humans in the driving loop — even if it requires an occasional slap on the wrist, via the driver-monitoring system developed by an Australian company, Seeing Machines.

Consider Cadillac’s Super Cruise the digital disciplinarian that makes drivers sit straight and keep eyes up front. It is G.M.’s consumer answer to Tesla’s Autopilot, but its approach illustrates the divergent philosophies of traditional automakers and the Valley rebels.

Many experts say Super Cruise, or a system like it, might have prevented the highly publicized fatal crashes of some Tesla Autopilot users, or Uber’s robotic Volvo that struck and killed an Arizona pedestrian in March last year. In the Uber case, police investigators said the human backup driver had been streaming Hulu before the accident. In some Tesla crashes, driver overconfidence in Autopilot’s abilities, leading to inattention, appears to have played a role.

That kind of carelessness isn’t possible with Super Cruise, as my own testing on Cadillac’s CT6 sedan has shown. The optional system will expand to other Cadillac models next year. Unlike Tesla’s current Autopilot, the system is explicitly designed for hands-free operation, allowing people to drive safely without touching the steering wheel or pedals — but strictly on major highways.

Using laser-based lidar, the Detroit-area company Ushr mapped 130,000 miles of freeway in the United States and Canada, in deep detail. That map is stored onboard the car, and updated monthly over the air to account for new construction and other road changes. The maps fix the Cadillac’s global position to within four inches, backed by onboard cameras, radar and GPS.

When I drove the Cadillac outside its geofenced borders, self-driving was strictly off limits. But once on its proper turf, Super Cruise breezed along highways in New Jersey for up to two hours with zero input from me.

It’s an odd sensation at first. But the Cadillac tracked down its lane as if it was on rails — better than the average Uber — so that I quickly gained confidence, eventually leaning back with hands folded behind my head as we zipped between semitrailers.

An infrared camera and lighting pods tracked my face, eyelids and pupils. The system let me look away long enough to, say, fiddle with radio stations. But if I closed my eyes or dared to text, the Caddy flashed escalating warnings. Putting eyes back on the road allowed me to proceed.

Ignore more prompts, and the system shuts down, refusing to work with a distracted driver. If that driver is disabled or asleep, the Caddy can pull over, stop automatically and call for help.

“What I love about Super Cruise is that it’s always watching you,” said Chris Thibodeau, Ushr’s chief executive.

The system also disengaged when it couldn’t confidently identify lane markings, or when it approached construction zones. While those cautious disengagements could be frustrating at times, Super Cruise proved a trusty co-pilot that prevents overconfidence from either party.

“The last thing you want is the machine making a judgment that would be better done by a human,” Mr. Thibodeau said.

Experts add that driver monitoring systems would be a boon to safety even in conventional situations. For one, parents could rest assured that teenagers weren’t texting while driving.

Designing skill amplifiers for automobiles, Mr. Pratt noted, is infinitely complex, in part because of the crowded and varied roadways that cars must perceive, predict and react to: what he calls the “complex ballet” of driving.

It doesn’t help that human drivers can be the weak dance partner. Roughly 1.3 million people die in global auto accidents every year, according to the World Health Organization. Human error is blamed in 94 percent of those deaths.

While Mr. Pratt is a champion of modern robotics, he said artificial intelligence would still take decades to rival some human abilities.

“We shouldn’t have this replacement mind-set to pop out the human and pop in the machine,” he said. “Sometimes the A.I. is better than the human. Sometimes the human is better than the A.I.”

The brain gives people one advantage, in predicting behaviors based on visual cues. Mr. Pratt offered the example of a driver cruising through intersections where various pedestrians wait to cross: an older person, a mother holding a child’s hand or a group of teenagers. A human driver will instantly process the scene and know that the teenagers are most likely to jaywalk.

“The A.I. system, unless it’s fed with hundreds of millions of examples, can’t pick that up, because it doesn’t think. It just pattern-matches,” Mr. Pratt said.

In the robot’s corner, it never gets tired or drunk, and has 360-degree sensor “vision.”

Mr. Musk has dismissed any need for a driver monitoring system on Teslas, or redundant hardware sensors, insisting that its coming “full self-driving computer” will handle any task.

That stance is drawing an unusual backlash against Tesla from industry analysts, from skepticism that Tesla can pull it off, to charges that the company is cutting corners on safety.

My tests of various semiautonomous systems highlighted what experts call a paradox of self-driving: As the technology gets better, it may initially become more hazardous, because drivers are sidelined for longer periods, lulled into a false sense of security.

“It’s a whole new paradigm for the manufacturers: How do I keep drivers engaged, what are the right alerts?” Mr. Thibodeau said.

“People have been trained for years to pay attention to everything on the road. It’s going to be hard to change that behavior and trust the machine.”

For people who envision the government coming for their car keys, Mr. Pratt has a message: The rise of the machines is real, but most people will choose personal autonomy over an autonomous car.

“The joy of driving a car is something that is incredibly innate and precious, and we don’t think that’s under threat at all,” he said.

Sahred From Source link Business

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littlemarketingproject · 8 years ago

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Marketing Machines: Is Machine Learning Helping Marketers or Making Us Obsolete?

Hollywood paints a grim picture of a future populated by intelligent machines. Terminator, 2001: A Space Odyssey, The Matrix and countless other films show us that machines are angry, they’re evil and — if given the opportunity — they will not hesitate to overthrow the human race.

Films like these serve as cautionary tales about what could happen if machines gain consciousness (or some semblance of). But in order for that to happen humans need to teach machines to think for themselves. This may sound like science fiction but it’s an actual discipline known as machine learning.

The machines are coming. But fear not — they could help you become a better marketer. Image via Shutterstock.

Still in its infancy, machine learning systems are being applied to everything from filtering spam emails, to suggesting the next series to binge-watch and even matching up folks looking for love.

For digital marketers, machine learning may be especially helpful in getting products or services in front of the right prospects, rather than blanket-marketing to everyone and adding to the constant noise that is modern advertising. Machine learning will also be key to predicting customer churn and attribution: two thorns in many digital marketers’ sides.

Despite machine learning’s positive impact on the digital marketing field, there are questions about job security and ethics that cannot be swept under the rug. Will marketing become so automated that professional marketers become obsolete? Is there potential for machine learning systems to do harm, whether by targeting vulnerable prospects or manipulating people’s emotions?

These aren’t just rhetorical questions. They get to the heart of what the future of marketing will look like — and what role marketers will play in it.

What is Machine Learning?

Machine learning is a complicated subject, involving advanced math, code and overwhelming amounts of data. Luckily, Tommy Levi, Director of Data Science at Unbounce, has a PhD in Theoretical Physics. He distills machine learning down to its simplest definition:

You can think of machine learning as using a computer or mathematics to make predictions or see patterns in data. At the end of the day, you’re really just trying to either predict something or see patterns, and then you’re just using the fact that a computer is really fast at calculating.

You may not know it, but you likely interact with machine learning systems on a daily basis. Have you ever been sucked into a Netflix wormhole prompted by recommended titles? Or used Facebook’s facial recognition tool when uploading and tagging an image? These are both examples of machine learning in action. They use the data you input (by rating shows, tagging friends, etc.) to produce better and more accurate suggestions over time.

Other examples of machine learning include spell check, spam filtering… even internet dating — yes, machine learning has made its way into the love lives of many, matching up singles using complicated algorithms that take into consideration personality traits and interests.

Machine learning may be helpful in getting products or services in front of the right prospects. Click To Tweet

How Machine Learning Works

While it may seem like witchcraft to the layperson, running in the background of every machine learning system we encounter is a human-built machine that would have gone through countless iterations to develop.

Facebook’s facial recognition tool, which can recognize your face with 98% accuracy, took several years of research and development to produce what is regarded as cutting-edge machine learning.

So how exactly does machine learning work? Spoiler alert: it’s complicated. So without going into too much detail, here’s an introduction to machine learning, starting with the two basic techniques.

Supervised learning

Supervised learning systems rely upon humans to label the incoming data — at least to begin with — in order for the systems to better predict how to classify future input data.

Gmail’s spam filter is a great example of this. When you label incoming mail as either spam or not spam, you’re not only cleaning up your inbox, you’re also training Gmail’s filter (a machine learning system) to identify what you consider to be spam (or not spam) in the future.

Unsupervised learning

Unsupervised learning systems use unlabeled incoming data, which is then organized into clusters based on similarities and differences in the data. Whereas supervised learning relies upon environmental feedback, unsupervised learning has no environmental feedback. Instead, data scientists will often use a reward/punishment system to indicate success or failure.

According to Tommy, this type of machine learning can be likened to the relationship between a parent and a young child. When a child does something positive they’re rewarded. Likewise, when “[a machine] gets it right — like it makes a good prediction — you kind of give it a little pat on the back and you say good job.”

Like any child (or person for that matter), the system ends up trying to maximize the positive reinforcement, thus getting better and better at predicting.

The Power of Machine Learning

A lot of what machine learning can do is yet to be explored, but the main benefit is its ability to wade through and sort data far more quickly and efficiently than any human could, no matter how clever.

Tommy is currently experimenting with an unsupervised learning system that clusters landing pages with similar features. Whereas one person could go through a few hundred pages in a day, this model can run through 300,000 pages in 20 minutes.

How do your landing page conversion rates compare against your industry competitors?

We analyzed the behavior of 74,551,421 visitors to 64,284 lead generation landing pages. Now we want to share average industry conversion rates with you in the Unbounce Conversion Benchmark Report.

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By entering your email you’ll receive other resources to help you improve your conversion rates.

The advantage is not just speed, it’s also retention and pattern recognition. Tommy explains:

To go through that many pages and see those patterns and hold it all in memory and be able to balance that — that’s where the power is.

For some marketers, this raises a troubling question: If machine learning systems solve problems by finding patterns that we can’t see, does this mean that marketers should be worried about job security?

The answer is more nuanced than a simple yes or no.

Machine Learning and the Digital Marketer

As data becomes the foundation for more and more marketing decisions, digital marketers have been tasked with sorting through an unprecedented amount of data.

This process usually involves hours of digging through analytics, collecting data points from marketing campaigns that span several months. And while focusing on data analysis and post-mortems is incredibly valuable, doing so takes a significant amount of time and resources away from future marketing initiatives.

As advancements in technology scale exponentially, the divide between teams that do and those that don’t will become more apparent. Those that don’t evolve will stumble and those that embrace data will grow — this is where machine learning can help.

Marketers that don’t embrace data will fumble. Those that do will grow — ML can help. Click To Tweet

That being said, machine learning isn’t something digital marketers can implement themselves after reading a quick tutorial. It’s more comparable to having a Ferrari in your driveway when you don’t know how to drive standard… or maybe you can’t even drive at all.

Until the day when implementing a machine learning system is just a YouTube video away, digital marketers could benefit from keeping a close eye on the companies that are incorporating machine learning into their products, and assessing whether they can help with their department’s pain points.

So how are marketers currently implementing machine learning to make decisions based on data rather than gut instinct? There are many niches in marketing that are becoming more automated. Here are a few that stand out.

Lead scoring and machine learning

Lead scoring is a system that allows marketers to gauge whether a prospect is a qualified lead and thus worth pursuing. Once marketing and sales teams agree on the definition of a ��qualified lead,” they can begin assigning values to different qualified lead indicators, such as job title, company size and even interaction with specific content.

These indicators paint a more holistic picture of a lead’s level of interest, beyond just a form submission typically associated with lead generation content like ebooks. And automating lead scoring takes the pressure off marketers having to qualify prospects via long forms, freeing them up to work on other marketing initiatives.

Once the leads have reached the “qualified” threshold, sales associates can then focus their efforts on those prospects — ultimately spending their time and money where it matters most.

Content marketing and copywriting

Machine learning models can analyze data points beyond just numbers — including words on your website, landing page or PPC ads. Machine learning systems can find patterns in language and detect words that elicit the most clicks or engagement.

Is emotional copywriting on your landing page effective in your industry?

We used machine learning to help create the Unbounce Conversion Benchmark Report, which shares insights on how different aspects of page copy correspond to conversion rates across 10 industries.

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But can a machine write persuasive copy? Maybe, actually.

A New York-based startup called Persado offers a “cognitive content platform” that uses math, data, natural language processing, emotional language data and machine learning systems to serve the best copy and images to spur prospects into action. It does this by analyzing all the language data each client has ever interacted with and serving future prospects with the best possible words or phrases. An A/B test could never achieve this at the same scale.

Think this is a joke? With over $65 million in venture capital and a reported average conversion rate uplift of 49.5% across 4,000 campaigns, Persado’s business model is no laughing matter.

Still, there is no replacement for a supremely personalized piece of content delivered straight to your client’s inbox — an honest call to action from one human to another.

Recently Unbounce’s Director of Campaign Strategy, Corey Dilley, sent an email to our customers. It had no sales pitch, no call to action button. It was just Corey reaching out and saying, “Hey.”

Corey’s email had an open rate of 41.42%, and he received around 80 personal responses. Not bad for an email written by a human!

Sometimes it’s actions — like clicks and conversions — you want to elicit from customers. Other times the goal is to build rapport. In some cases we should let the machines do the work, but it’s up to the humans to keep the content, well, human.

There is no replacement for personalized content and an honest ask from one human to another. Click To Tweet

Machine learning for churn prediction

In the SaaS industry, churn is a measure of the percentage of customers who cancel their recurring revenue subscriptions. According to Tommy, churn tells a story about “how your customers behave and feel. It’s giving a voice to the customers that we don’t have time or the ability to talk to.”

Self-reporting methods such as polls and surveys are another good way to give a voice to these customers. But they’re not always scalable — large data sets can be hard for humans to analyze and derive meaning from.

Self-reporting methods can also skew your results. Tommy explains:

The problem with things like surveys and popups is that they’re only going to tell you what you’ve asked about, and the type of people that answer surveys are already a biased set.

Machine learning systems, on the other hand, can digest a larger number of data points, and with far less bias. Ideally the data is going to reveal what marketing efforts are working, thus leading to reduced churn and helping to move customers down the funnel.

This is highly relevant for SaaS companies, whose customers often sign up for trials before purchasing the product. Once someone starts a trial, the marketing department will start sending them content in order to nurture them into adopting the service and become engaged.

Churn models can help a marketing team determine which pieces of content lead to negative or positive encounters — information that can inform and guide the optimization process.

Ethical Implications of Machine Learning in Marketing

We hinted at the ethical implications of machine learning in marketing, but it deserves its own discussion (heck, it deserves its own book). The truth is, machine learning systems have the potential to cause legitimate harm.

According to Carl Schmidt, Co-Founder and Chief Technology Officer at Unbounce:

Where we are really going to run into ethical issues is with extreme personalization. We’re going to teach machines how to be the ultimate salespeople, and they’re not going to care about whether you have a compulsive personality… They’re just going to care about success.

This could mean targeting someone in rehab with alcohol ads, or someone with a gambling problem with a trip to Las Vegas. The machine learning system will make the correlation, based on the person’s internet activity, and it’s going to exploit that.

Another dilemma we run into is with marketing aimed at affecting people’s emotions. Sure copywriters often tap into emotions in order to get a desired response, but there’s a fine line between making people feel things and emotional manipulation, as Facebook discovered in an infamous experiment.

If you aren’t familiar with the experiment, here’s the abridged version: Facebook researchers adapted word count software to manipulate the News Feeds of 689,003 users to determine whether their emotional state could be altered if they saw fewer positive posts or fewer negative posts in their feeds.

Posts were deemed either positive or negative if they contained at least one positive or negative word. Because researchers never saw the status updates (the machine learning system did the filtering) technically it fell within Facebook’s Data Use Policy.

However, public reaction to the Facebook experiment was generally pretty scathing. While some came to the defense of Facebook, many criticized the company for breaching ethical guidelines for informed consent.

In the end, Facebook admitted they could have done better. And one good thing did come out of the experiment: It now serves as a benchmark for when machine learning goes too far, and as a reminder for marketers to continually gut-check themselves.

For Carl, it comes down to intent:

If I’m Facebook, I might be worried that if we don’t do anything about the pacing and style of content, and we’re inadvertently presenting content that could be reacted to negatively, especially to vulnerable people, then we would want to actively understand that mechanism and do something about it.

While we may not yet have a concrete code of conduct around machine learning, moving forward with good intentions and a commitment to do no harm is a good place to start.

The Human Side of Machine Learning

Ethical issues aside, the rise of machines often implies the fall of humans. But it doesn’t have to be one or the other.

“You want machines to do the mundane stuff and the humans to do the creative stuff,” Carl says. He continues:

Computers are still not creative. They can’t think on their own, and they generally can’t delight you very much. We are going to get to a point where you could probably generate highly personal onboarding content by a machine. But it [will have] no soul.

That’s where the human aspect comes in. With creativity and wordsmithing. With live customer support. Heck, it takes some pretty creative data people to come up with an algorithm that recognizes faces with 98% accuracy.

Imagine a world where rather than getting 15 spam emails a day, you get just one with exactly the content you would otherwise be searching for — content written by a human, but served to you by a machine learning system.

While pop culture may say otherwise, the future of marketing isn’t about humans (or rather, marketers) versus machines. It’s about marketers using machines to get amazing results — for their customers and their company.

Machine learning systems may have an edge when it comes to data sorting, but they’re missing many of the things that make exceptional marketing experiences: empathy, compassion and a true understanding of the human experience.

Editor’s note: This article originally appeared in The Split, a digital magazine by Unbounce.

Marketing Machines: Is Machine Learning Helping Marketers or Making Us Obsolete? syndicated from https://unbounce.com

0 notes

maxslogic25 · 8 years ago

Text

Marketing Machines: Is Machine Learning Helping Marketers or Making Us Obsolete?

The machines are coming. But fear not — they could help you become a better marketer. Image via Shutterstock.

Still in its infancy, machine learning systems are being applied to everything from filtering spam emails, to suggesting the next series to binge-watch and even matching up folks looking for love.

These aren’t just rhetorical questions. They get to the heart of what the future of marketing will look like — and what role marketers will play in it.

What is Machine Learning?

Machine learning may be helpful in getting products or services in front of the right prospects. Click To Tweet

How Machine Learning Works

Facebook’s facial recognition tool, which can recognize your face with 98% accuracy, took several years of research and development to produce what is regarded as cutting-edge machine learning.

Supervised learning

Supervised learning systems rely upon humans to label the incoming data — at least to begin with — in order for the systems to better predict how to classify future input data.

Unsupervised learning

Like any child (or person for that matter), the system ends up trying to maximize the positive reinforcement, thus getting better and better at predicting.

The Power of Machine Learning

How do your landing page conversion rates compare against your industry competitors?

We analyzed the behavior of 74,551,421 visitors to 64,284 lead generation landing pages. Now we want to share average industry conversion rates with you in the Unbounce Conversion Benchmark Report.

By entering your email you'll receive other resources to help you improve your conversion rates.

The advantage is not just speed, it’s also retention and pattern recognition. Tommy explains:

To go through that many pages and see those patterns and hold it all in memory and be able to balance that — that’s where the power is.

The answer is more nuanced than a simple yes or no.

Machine Learning and the Digital Marketer

As data becomes the foundation for more and more marketing decisions, digital marketers have been tasked with sorting through an unprecedented amount of data.

Marketers that don’t embrace data will fumble. Those that do will grow — ML can help. Click To Tweet

Lead scoring and machine learning

Lead scoring is a system that allows marketers to gauge whether a prospect is a qualified lead and thus worth pursuing. Once marketing and sales teams agree on the definition of a “qualified lead,” they can begin assigning values to different qualified lead indicators, such as job title, company size and even interaction with specific content.

Once the leads have reached the “qualified” threshold, sales associates can then focus their efforts on those prospects — ultimately spending their time and money where it matters most.

Content marketing and copywriting

Is emotional copywriting on your landing page effective in your industry?

We used machine learning to help create the Unbounce Conversion Benchmark Report, which shares insights on how different aspects of page copy correspond to conversion rates across 10 industries.

By entering your email you'll receive other resources to help you improve your conversion rates.

But can a machine write persuasive copy? Maybe, actually.

Think this is a joke? With over $65 million in venture capital and a reported average conversion rate uplift of 49.5% across 4,000 campaigns, Persado’s business model is no laughing matter.

Still, there is no replacement for a supremely personalized piece of content delivered straight to your client’s inbox — an honest call to action from one human to another.

Corey’s email had an open rate of 41.42%, and he received around 80 personal responses. Not bad for an email written by a human!

There is no replacement for personalized content and an honest ask from one human to another. Click To Tweet

Machine learning for churn prediction

Self-reporting methods can also skew your results. Tommy explains:

The problem with things like surveys and popups is that they’re only going to tell you what you’ve asked about, and the type of people that answer surveys are already a biased set.

Churn models can help a marketing team determine which pieces of content lead to negative or positive encounters — information that can inform and guide the optimization process.

Ethical Implications of Machine Learning in Marketing

According to Carl Schmidt, Co-Founder and Chief Technology Officer at Unbounce:

For Carl, it comes down to intent:

While we may not yet have a concrete code of conduct around machine learning, moving forward with good intentions and a commitment to do no harm is a good place to start.

The Human Side of Machine Learning

Ethical issues aside, the rise of machines often implies the fall of humans. But it doesn’t have to be one or the other.

“You want machines to do the mundane stuff and the humans to do the creative stuff,” Carl says. He continues:

Editor’s note: This article originally appeared in The Split, a digital magazine by Unbounce.

from RSSMix.com Mix ID 8217493 http://unbounce.com/online-marketing/marketing-machines-is-machine-learning-helping-marketers-or-making-us-obsolete/

0 notes

racheltgibsau · 8 years ago

Text

Marketing Machines: Is Machine Learning Helping Marketers or Making Us Obsolete?

The machines are coming. But fear not — they could help you become a better marketer. Image via Shutterstock.

Still in its infancy, machine learning systems are being applied to everything from filtering spam emails, to suggesting the next series to binge-watch and even matching up folks looking for love.

These aren’t just rhetorical questions. They get to the heart of what the future of marketing will look like — and what role marketers will play in it.

What is Machine Learning?

Machine learning may be helpful in getting products or services in front of the right prospects. Click To Tweet

How Machine Learning Works

Facebook’s facial recognition tool, which can recognize your face with 98% accuracy, took several years of research and development to produce what is regarded as cutting-edge machine learning.

Supervised learning

Supervised learning systems rely upon humans to label the incoming data — at least to begin with — in order for the systems to better predict how to classify future input data.

Unsupervised learning

Like any child (or person for that matter), the system ends up trying to maximize the positive reinforcement, thus getting better and better at predicting.

The Power of Machine Learning

How do your landing page conversion rates compare against your industry competitors?

We analyzed the behavior of 74,551,421 visitors to 64,284 lead generation landing pages. Now we want to share average industry conversion rates with you in the Unbounce Conversion Benchmark Report.

By entering your email you'll receive other resources to help you improve your conversion rates.

The advantage is not just speed, it’s also retention and pattern recognition. Tommy explains:

To go through that many pages and see those patterns and hold it all in memory and be able to balance that — that’s where the power is.

The answer is more nuanced than a simple yes or no.

Machine Learning and the Digital Marketer

As data becomes the foundation for more and more marketing decisions, digital marketers have been tasked with sorting through an unprecedented amount of data.

Marketers that don’t embrace data will fumble. Those that do will grow — ML can help. Click To Tweet

Lead scoring and machine learning

Once the leads have reached the “qualified” threshold, sales associates can then focus their efforts on those prospects — ultimately spending their time and money where it matters most.

Content marketing and copywriting

Is emotional copywriting on your landing page effective in your industry?

We used machine learning to help create the Unbounce Conversion Benchmark Report, which shares insights on how different aspects of page copy correspond to conversion rates across 10 industries.

By entering your email you'll receive other resources to help you improve your conversion rates.

But can a machine write persuasive copy? Maybe, actually.

Think this is a joke? With over $65 million in venture capital and a reported average conversion rate uplift of 49.5% across 4,000 campaigns, Persado’s business model is no laughing matter.

Still, there is no replacement for a supremely personalized piece of content delivered straight to your client’s inbox — an honest call to action from one human to another.

Corey’s email had an open rate of 41.42%, and he received around 80 personal responses. Not bad for an email written by a human!

There is no replacement for personalized content and an honest ask from one human to another. Click To Tweet

Machine learning for churn prediction

Self-reporting methods can also skew your results. Tommy explains:

The problem with things like surveys and popups is that they’re only going to tell you what you’ve asked about, and the type of people that answer surveys are already a biased set.

Churn models can help a marketing team determine which pieces of content lead to negative or positive encounters — information that can inform and guide the optimization process.

Ethical Implications of Machine Learning in Marketing

According to Carl Schmidt, Co-Founder and Chief Technology Officer at Unbounce:

For Carl, it comes down to intent:

While we may not yet have a concrete code of conduct around machine learning, moving forward with good intentions and a commitment to do no harm is a good place to start.

The Human Side of Machine Learning

Ethical issues aside, the rise of machines often implies the fall of humans. But it doesn’t have to be one or the other.

“You want machines to do the mundane stuff and the humans to do the creative stuff,” Carl says. He continues:

Editor’s note: This article originally appeared in The Split, a digital magazine by Unbounce.

from RSSMix.com Mix ID 8217493 http://unbounce.com/online-marketing/marketing-machines-is-machine-learning-helping-marketers-or-making-us-obsolete/

0 notes

archiebwoollard · 8 years ago

Text

Marketing Machines: Is Machine Learning Helping Marketers or Making Us Obsolete?

The machines are coming. But fear not — they could help you become a better marketer. Image via Shutterstock.

Still in its infancy, machine learning systems are being applied to everything from filtering spam emails, to suggesting the next series to binge-watch and even matching up folks looking for love.

These aren’t just rhetorical questions. They get to the heart of what the future of marketing will look like — and what role marketers will play in it.

What is Machine Learning?

Machine learning may be helpful in getting products or services in front of the right prospects. Click To Tweet

How Machine Learning Works

Facebook’s facial recognition tool, which can recognize your face with 98% accuracy, took several years of research and development to produce what is regarded as cutting-edge machine learning.

Supervised learning

Supervised learning systems rely upon humans to label the incoming data — at least to begin with — in order for the systems to better predict how to classify future input data.

Unsupervised learning

Like any child (or person for that matter), the system ends up trying to maximize the positive reinforcement, thus getting better and better at predicting.

The Power of Machine Learning

How do your landing page conversion rates compare against your industry competitors?

We analyzed the behavior of 74,551,421 visitors to 64,284 lead generation landing pages. Now we want to share average industry conversion rates with you in the Unbounce Conversion Benchmark Report.

By entering your email you'll receive other resources to help you improve your conversion rates.

The advantage is not just speed, it’s also retention and pattern recognition. Tommy explains:

To go through that many pages and see those patterns and hold it all in memory and be able to balance that — that’s where the power is.

The answer is more nuanced than a simple yes or no.

Machine Learning and the Digital Marketer

As data becomes the foundation for more and more marketing decisions, digital marketers have been tasked with sorting through an unprecedented amount of data.

Marketers that don’t embrace data will fumble. Those that do will grow — ML can help. Click To Tweet

Lead scoring and machine learning

Once the leads have reached the “qualified” threshold, sales associates can then focus their efforts on those prospects — ultimately spending their time and money where it matters most.

Content marketing and copywriting

Is emotional copywriting on your landing page effective in your industry?

We used machine learning to help create the Unbounce Conversion Benchmark Report, which shares insights on how different aspects of page copy correspond to conversion rates across 10 industries.

By entering your email you'll receive other resources to help you improve your conversion rates.

But can a machine write persuasive copy? Maybe, actually.

Think this is a joke? With over $65 million in venture capital and a reported average conversion rate uplift of 49.5% across 4,000 campaigns, Persado’s business model is no laughing matter.

Still, there is no replacement for a supremely personalized piece of content delivered straight to your client’s inbox — an honest call to action from one human to another.

Corey’s email had an open rate of 41.42%, and he received around 80 personal responses. Not bad for an email written by a human!

There is no replacement for personalized content and an honest ask from one human to another. Click To Tweet

Machine learning for churn prediction

Self-reporting methods can also skew your results. Tommy explains:

The problem with things like surveys and popups is that they’re only going to tell you what you’ve asked about, and the type of people that answer surveys are already a biased set.

Churn models can help a marketing team determine which pieces of content lead to negative or positive encounters — information that can inform and guide the optimization process.

Ethical Implications of Machine Learning in Marketing

According to Carl Schmidt, Co-Founder and Chief Technology Officer at Unbounce:

For Carl, it comes down to intent:

While we may not yet have a concrete code of conduct around machine learning, moving forward with good intentions and a commitment to do no harm is a good place to start.

The Human Side of Machine Learning

Ethical issues aside, the rise of machines often implies the fall of humans. But it doesn’t have to be one or the other.

“You want machines to do the mundane stuff and the humans to do the creative stuff,” Carl says. He continues:

Editor’s note: This article originally appeared in The Split, a digital magazine by Unbounce.

from RSSMix.com Mix ID 8217493 http://unbounce.com/online-marketing/marketing-machines-is-machine-learning-helping-marketers-or-making-us-obsolete/

0 notes

zacdhaenkeau · 8 years ago

Text

Marketing Machines: Is Machine Learning Helping Marketers or Making Us Obsolete?

The machines are coming. But fear not — they could help you become a better marketer. Image via Shutterstock.

Still in its infancy, machine learning systems are being applied to everything from filtering spam emails, to suggesting the next series to binge-watch and even matching up folks looking for love.

These aren’t just rhetorical questions. They get to the heart of what the future of marketing will look like — and what role marketers will play in it.

What is Machine Learning?

Machine learning may be helpful in getting products or services in front of the right prospects. Click To Tweet

How Machine Learning Works

Facebook’s facial recognition tool, which can recognize your face with 98% accuracy, took several years of research and development to produce what is regarded as cutting-edge machine learning.

Supervised learning

Supervised learning systems rely upon humans to label the incoming data — at least to begin with — in order for the systems to better predict how to classify future input data.

Unsupervised learning

Like any child (or person for that matter), the system ends up trying to maximize the positive reinforcement, thus getting better and better at predicting.

The Power of Machine Learning

How do your landing page conversion rates compare against your industry competitors?

We analyzed the behavior of 74,551,421 visitors to 64,284 lead generation landing pages. Now we want to share average industry conversion rates with you in the Unbounce Conversion Benchmark Report.

By entering your email you'll receive other resources to help you improve your conversion rates.

The advantage is not just speed, it’s also retention and pattern recognition. Tommy explains:

To go through that many pages and see those patterns and hold it all in memory and be able to balance that — that’s where the power is.

The answer is more nuanced than a simple yes or no.

Machine Learning and the Digital Marketer

As data becomes the foundation for more and more marketing decisions, digital marketers have been tasked with sorting through an unprecedented amount of data.

Marketers that don’t embrace data will fumble. Those that do will grow — ML can help. Click To Tweet

Lead scoring and machine learning

Once the leads have reached the “qualified” threshold, sales associates can then focus their efforts on those prospects — ultimately spending their time and money where it matters most.

Content marketing and copywriting

Is emotional copywriting on your landing page effective in your industry?

We used machine learning to help create the Unbounce Conversion Benchmark Report, which shares insights on how different aspects of page copy correspond to conversion rates across 10 industries.

By entering your email you'll receive other resources to help you improve your conversion rates.

But can a machine write persuasive copy? Maybe, actually.

Think this is a joke? With over $65 million in venture capital and a reported average conversion rate uplift of 49.5% across 4,000 campaigns, Persado’s business model is no laughing matter.

Still, there is no replacement for a supremely personalized piece of content delivered straight to your client’s inbox — an honest call to action from one human to another.

Corey’s email had an open rate of 41.42%, and he received around 80 personal responses. Not bad for an email written by a human!

There is no replacement for personalized content and an honest ask from one human to another. Click To Tweet

Machine learning for churn prediction

Self-reporting methods can also skew your results. Tommy explains:

The problem with things like surveys and popups is that they’re only going to tell you what you’ve asked about, and the type of people that answer surveys are already a biased set.

Churn models can help a marketing team determine which pieces of content lead to negative or positive encounters — information that can inform and guide the optimization process.

Ethical Implications of Machine Learning in Marketing

According to Carl Schmidt, Co-Founder and Chief Technology Officer at Unbounce:

For Carl, it comes down to intent:

While we may not yet have a concrete code of conduct around machine learning, moving forward with good intentions and a commitment to do no harm is a good place to start.

The Human Side of Machine Learning

Ethical issues aside, the rise of machines often implies the fall of humans. But it doesn’t have to be one or the other.

“You want machines to do the mundane stuff and the humans to do the creative stuff,” Carl says. He continues:

Editor’s note: This article originally appeared in The Split, a digital magazine by Unbounce.

from RSSMix.com Mix ID 8217493 http://unbounce.com/online-marketing/marketing-machines-is-machine-learning-helping-marketers-or-making-us-obsolete/

0 notes