#AI coding tools for junior devs

[curriculumsupport]

AI Coding for Junior Devs: How to Learn Smarter with Smart Tools

The world of technology is evolving faster than ever, and junior programmers today have a powerful ally that previous generations could only dream of—Artificial Intelligence (AI). From automating repetitive coding tasks to offering smart suggestions and real-time debugging, AI is revolutionizing the way newcomers learn and grow. AI coding for junior devs is not just a trend; it’s a practical path to smarter, faster, and more confident learning in the competitive software development world.

The Rise of AI in Software Development

Understanding the Impact of AI in Coding

AI is no longer just a buzzword in Silicon Valley—it's now deeply integrated into many coding environments and software development tools. From intelligent auto-completion to context-aware code suggestions, AI coding tools for junior devs are becoming essential in the early stages of a programmer’s journey.

The goal is simple: help developers become more productive and eliminate the guesswork, especially during those tough debugging sessions or while learning complex syntax.

Why Junior Developers Should Embrace AI Early

Getting started with programming can be overwhelming. There's so much to learn—syntax, logic, frameworks, and best practices. By leveraging the best AI tools for coding, junior developers can cut through the noise and get focused, real-time assistance right when they need it.

AI tools offer:

Faster learning curves

Error reduction and cleaner code

Real-world practice through smart feedback

This gives aspiring developers the edge to code smarter, not harder.

How AI Coding Tools Empower Junior Programmers

Personalized Learning Experiences

Unlike static tutorials or books, AI coding for junior programmers provides a personalized experience. These tools adapt to your level, offering contextual code suggestions and pointing out errors with explanations that help you understand—not just fix—the problem.

For example, some AI coding assistants can suggest optimal solutions based on your coding style and previous code snippets. This tailored approach boosts retention and confidence.

Accelerated Debugging and Code Review

One of the biggest hurdles for junior devs is debugging. AI can act as a second pair of eyes, scanning your code in real time and suggesting corrections or improvements.

Think of it as having a personal tutor by your side—one who doesn’t sleep and is available 24/7. Whether you're stuck on a syntax error or trying to improve the efficiency of a function, AI code generators can offer practical, real-time feedback.

Must-Try AI Tools for Junior Devs

Click-Coder: Your First AI Mentor

Click-Coder is a beginner-friendly AI coding assistant designed with junior developers in mind. It offers real-time syntax suggestions, intelligent debugging, and mini-tutorials on common programming mistakes. What sets it apart is its intuitive interface and guided feedback system, which explains why something is wrong and how to fix it.

This makes Click-Coder an excellent AI tool for junior devs just starting out in languages like Python, JavaScript, or Java.

GitHub Copilot and Tabnine: Hands-On AI Coding Assistants

GitHub Copilot and Tabnine are powerful AI-driven coding assistants that integrate directly into your code editor. They suggest lines or blocks of code as you type, drawing from vast libraries of open-source code.

GitHub Copilot: Great for exploring unfamiliar APIs or writing boilerplate code

Tabnine: Focuses on fast, contextual code completion using AI models trained on industry best practices

Both are considered among the best AI for coding, especially for those who want to improve coding speed and learn new patterns.

What Makes These the Best AI Tools for Coding?

These tools are not just fancy auto-completes—they are smart assistants that understand context, syntax, and structure. What makes them especially beneficial for junior devs is:

Easy integration with popular IDEs (like VS Code)

Access to suggestions based on real-world code

Built-in feedback that teaches better programming practices

By using tools like these, junior developers can practice coding with confidence and learn by doing—one of the most effective learning methods.

Getting the Most Out of AI Code Generators

Tips to Use AI Tools More Effectively

To truly benefit from the best AI coding assistant, junior devs should use AI as a companion rather than a crutch. Here are a few tips to keep in mind:

Understand Before You Accept: Don’t just accept AI suggestions blindly. Try to understand what the code does.

Experiment with Different Prompts: See how changing your comment or initial input affects the AI output.

Practice with Real Projects: Use AI tools in actual mini-projects to see how they perform under different scenarios.

Best Practices for Learning with AI Tools

Learning to code with AI is most effective when paired with active practice and review:

Refactor AI-generated code to fit your style

Use AI suggestions to learn new syntax and patterns

Keep a coding journal to reflect on what the AI helped you learn

Common Pitfalls to Avoid

While AI coding tools for junior devs are incredibly helpful, they’re not perfect. Watch out for:

Over-reliance on AI: Make sure you’re still learning and not just copy-pasting

Poor-quality suggestions: Always test and validate the code before using it

Skipping foundational knowledge: AI can guide, but it can't replace understanding core concepts

AI-Powered Learning: Smarter Ways to Build Skills

Building Real Projects with AI Guidance

Nothing builds coding confidence like completing a real-world project. AI can help you get past common blockers and provide best-practice insights as you build.

Try small projects like:

A personal portfolio site

A weather app using an API

A to-do list with local storage

By incorporating AI code generators into these projects, junior devs can learn by doing with instant support.

Staying Up to Date in the Evolving Tech Space

The world of AI in software development is growing rapidly. To keep up, junior programmers should:

Follow blogs and YouTube channels on technology and coding

Participate in forums like Stack Overflow or Reddit’s r/learnprogramming

Try out new AI tools for coding as they are released

This ensures that as the tech evolves, so do your skills.

FAQs: AI Coding for Junior Programmers

What is the best AI tool for junior devs to start with?

Click-Coder is a great beginner-friendly tool. It offers explanations, real-time suggestions, and helps you build a strong foundation in coding.

Can AI really help me learn coding faster?

Yes! AI tools provide instant feedback, reduce trial-and-error frustration, and help you understand code logic and structure more efficiently.

Is using AI tools considered cheating in learning?

Not at all. It’s like using a calculator in math—it enhances your ability to solve problems, provided you also understand the fundamentals.

Which programming languages do AI tools support?

Most popular tools like GitHub Copilot and Tabnine support major languages including Python, JavaScript, Java, C++, and more.

Are AI coding tools free for beginners?

Many tools offer free versions with basic features, which are perfect for junior programmers. Some may require a subscription for advanced functionality.

Conclusion

AI coding tools are transforming how junior developers learn and grow in the world of software development. By combining smart assistance with hands-on practice, these tools empower beginners to code with confidence and efficiency.

Embracing AI coding for junior devs means learning smarter, not harder. With the right tools and mindset, every junior programmer can build a strong foundation for a successful tech career.

[lithiumdoll]

Okay, look, it’s super simple:

If you can write working code and tests without AI, you’re a coder, my brothers, sisters and cousins in pain. If you use AI to speed things up, it’s a tool. Maybe don’t feed it the codebase tho? Don’t. Don’t do that. Oh nooooo.

If you can’t write working code without AI you’re an unusually communicative client and DeepClaudeGPT or whatever is the developer.

Very simple distinction, see also: literally every use of AI.

Any parity you think you have where you get to replace skill with careful phrasing lasts exactly as long as AI isn’t locked behind paywall, so if you’re getting hired based on it, you’re cooked.

This post bought to you by a dev with juniors who think she won’t notice generative code and a growing and intense hatred for the phrase “vibe coding.”

[curtainguard]

How Vibe Coding Is Empowering a New Wave of Digital Creators

In an era where technology and creativity intersect more than ever, a new paradigm known as Vibe Coding is reshaping how people, especially non-programmers and junior developers, engage with software development. From AI-powered tools that assist in writing complex code to platforms enabling intuitive interaction with development environments, Vibe Coding is leading the charge in democratizing digital creation.

This movement is opening the doors for a broader, more diverse pool of creators to express ideas through code—without needing years of technical training.

The Rise of Vibe Coding in the Digital Age

What Is Vibe Coding?

Vibe Coding is a movement that merges intuitive design, creativity, and the power of artificial intelligence to simplify coding. It's not just about writing efficient algorithms; it's about empowering individuals—regardless of their technical background—to create, iterate, and build with digital confidence. By using AI coding tools for non-programmers, even those unfamiliar with traditional development methods can participate in building digital products.

Vibe Coding for Creative Programmers emphasizes fluid, flexible approaches to software creation. It favors accessibility and imagination over syntax memorization, making it a perfect match for today's digital creatives.

Why It's More Than Just Code

Unlike traditional programming, Vibe Coding treats code like a medium for artistic and functional expression. This new wave isn't just for professional developers. It's about giving musicians, artists, educators, and junior programmers the tools to build without the friction of a steep learning curve. AI coding for junior devs turns what once felt like an intimidating process into an approachable and even fun experience.

Vibe Coding aligns closely with how modern creators work—visually, intuitively, and interactively. The result? More inclusive tech spaces and a richer array of digital innovations.

AI Coding for Junior and Non-Programmers

Lowering the Barriers with AI

One of the most significant shifts in modern coding practices is the integration of AI as a creative and functional partner. For those who have never written a line of code, AI coding for non-programmers offers a powerful starting point. Through natural language processing and smart suggestions, AI systems can translate plain English into working code.

By using the best AI tool for coding, newcomers can now build simple applications, automate workflows, or create websites—tasks that once required expert knowledge. These tools are becoming the virtual training wheels for a new generation of creators.

Empowering Junior Devs with Vibe Coding

AI coding for junior programmers is especially impactful because it helps them learn while building. These systems act as an AI-powered coding assistant, offering real-time feedback, fixing errors, and even explaining concepts on the go. Instead of spending hours searching forums for help, junior developers can progress with confidence, learning through doing.

Vibe Coding provides junior devs with a sandbox where experimentation is encouraged, and failure is just part of the journey—not a blocker.

Creative Freedom Through AI Coding Tools

Unlocking Creativity for Non-Programmers

Creativity has always been at the heart of innovation. With AI coding tools for non-programmers, we are witnessing the rise of digital artists who build interactive experiences without needing to master a programming language. Tools now translate vision into code in real-time, allowing creators to bring their ideas to life faster and more effectively.

These platforms aren’t just technical—they’re inspirational. They provide templates, libraries, and smart guidance to support creativity, whether it's designing an interactive story, building a portfolio, or crafting a music app.

The Role of AI-Powered Coding Assistants

The best AI for coding doesn’t just write code—it collaborates. AI-powered coding assistants now help with:

Suggesting more efficient logic

Writing reusable functions

Identifying bugs before execution

Offering alternative approaches based on user goals

This revolution is critical in making development less about rote syntax and more about creative solutions. The best AI for coding becomes a partner in progress, guiding users to learn better practices while achieving their project goals.

AI Tools Leading the Charge

Click-Coder: Code Without Boundaries

Click-Coder is one of the standout tools revolutionizing Vibe Coding. Designed for both seasoned developers and absolute beginners, Click-Coder uses natural language input to generate real code that can be modified in real-time. Its intuitive drag-and-drop interface and AI engine remove the complexity of traditional coding, making it ideal for educational settings and design-first creators.

With features like project walkthroughs, live previews, and instant code explanations, Click-Coder transforms how we think about building digital products. It’s especially beneficial for junior devs who are still developing their problem-solving frameworks.

DeepPrompt and CodeMuse: Game Changers in AI Coding

DeepPrompt is another leading AI tool that uses deep learning to enhance coding workflows. With contextual understanding of your codebase, it provides suggestions that are both syntactically correct and contextually relevant—helping both beginners and experienced coders streamline their work.

CodeMuse focuses on creative coding projects. It helps artists and storytellers build interactive content using minimal technical knowledge. With pre-trained models and creative libraries, CodeMuse is tailored for those using code as a canvas.

Key Benefits of These AI Tools

Accessibility: No prior experience needed

Speed: Rapid prototyping and iteration

Support: Real-time suggestions and error correction

Education: In-line explanations help users learn as they build

Creativity: Encourage experimentation and innovation across disciplines

How Vibe Coding Is Transforming Tech Education

Coding as a Language of Creativity

Vibe Coding is not just about technical proficiency—it’s about storytelling, exploration, and personal expression through digital media. As educational systems adopt these AI tools, students are learning to see code as a medium for creativity rather than just a technical skill.

Schools and coding bootcamps now use AI coding for junior programmers to nurture problem-solving and critical thinking from an early stage. The focus has shifted from memorizing syntax to building meaningful projects that foster innovation.

Bridging the Gap Between Art and Tech

Historically, art and programming have been seen as separate domains. Vibe Coding is bridging that divide, allowing creators from all backgrounds to participate in tech. Whether you’re building generative art, designing user experiences, or composing digital music, AI-assisted tools ensure that coding doesn’t become a barrier to entry.

By blending design thinking, AI, and intuitive tools, Vibe Coding encourages a fusion of disciplines that’s essential for the future of technology.

FAQs

What is Vibe Coding, and how is it different from traditional coding?

Vibe Coding emphasizes creativity, ease of use, and accessibility. Unlike traditional coding, which often requires deep technical knowledge, Vibe Coding empowers users to build through intuitive interfaces and AI support.

Can non-programmers really build apps with AI coding tools?

Yes. Many AI coding tools for non-programmers allow users to create apps using simple natural language commands or visual interfaces, removing the need for extensive coding knowledge.

Is AI coding for junior devs a good way to learn programming?

Absolutely. AI-powered coding assistants help junior devs understand the logic behind code by offering real-time suggestions and explanations, making the learning curve much less steep.

Which is the best AI tool for coding right now?

While the best tool depends on your needs, Click-Coder is highly recommended for beginners and creative professionals. DeepPrompt and CodeMuse are also excellent for context-aware suggestions and creative coding respectively.

How does Vibe Coding fit into the future of education?

Vibe Coding supports project-based learning and encourages creative problem-solving. It’s already being integrated into tech education to help students build confidence and fluency in digital creation.

Conclusion

Vibe Coding is more than a trend—it’s a cultural and technological shift that redefines who gets to be a creator in the digital world. By leveraging AI coding tools for non-programmers and junior developers, it's unlocking the door to innovation for artists, storytellers, designers, and hobbyists. As tools like Click-Coder, Deep Prompt, and Code Muse continue to evolve, the future of coding looks more inclusive, more creative, and far more accessible than ever before. Whether you’re just starting your tech journey or looking to re imagine how you code, Vibe Coding offers a compelling, intuitive path forward.

[racilablog]

How Corporate Training Is Empowering Tech Teams to Adapt and Thrive

In tech, everything moves fast. New frameworks emerge, old tools get deprecated, and companies pivot strategies overnight. While self-learning is a part of every developer’s journey, there’s one structured approach that’s often overlooked: corporate training.

I used to think corporate training was just about soft skills or onboarding, but I’ve come to realize it can actually play a huge role in keeping dev teams future-ready—if done right.

🚀 Why Corporate Training Still Matters in Tech

Tech folks are known for figuring things out on their own—Stack Overflow, docs, tutorials, and midnight hacking. So why invest in formal training?

Here’s what I’ve observed from teams that do training well:

Bridging tech gaps: When your backend team suddenly needs to learn containerization or switch from REST to GraphQL, training helps accelerate the transition.

Consistency: Everyone’s on the same page. Instead of relying on fragmented YouTube tutorials, your team gets shared context and standards.

Faster onboarding: New hires get up to speed quickly when there's a learning track in place.

Leadership development: Training isn’t just for junior devs. Mentorship programs and leadership workshops help senior devs grow into tech leads.

What Modern Corporate Training Looks Like

Forget boring slide decks and five-hour lectures. Today’s training methods are interactive, hands-on, and tailored to a developer’s pace.

Code-alongs and live labs

Micro-courses with real-world scenarios

Project-based sprints

Internal hackathons and retrospectives

Mentorship and peer reviews

Many companies blend in-person and online formats to keep things flexible, especially in hybrid teams.

A Real-World Example: Racila Softech

I came across Racila Softech, a tech company that integrates corporate training into its IT services. What stood out to me was their hands-on, project-based approach. They train professionals in full-stack development (MERN), Python, AI/ML, data analysis, and more.

Rather than teaching theory alone, they focus on building, collaborating, and learning through guided mentorship. That kind of structure can really level up a dev team.

(This mention is purely informational—not sponsored or affiliated.)

[jcmarchi]

Bito Raises $5.7M to Supercharge Agentic AI Code Reviews and Accelerate Enterprise Dev Velocity

New Post has been published on https://thedigitalinsider.com/bito-raises-5-7m-to-supercharge-agentic-ai-code-reviews-and-accelerate-enterprise-dev-velocity/

Bito Raises $5.7M to Supercharge Agentic AI Code Reviews and Accelerate Enterprise Dev Velocity

In a funding round that signals a significant leap forward for AI-assisted software development, Bito has raised a $5.7 million seed extension to further advance its agentic AI platform for code review. The round, led by Vela Partners with backing from NextView Ventures, Maxitech Ventures, Eniac Ventures, and others, brings Bito’s total seed-stage funding to $8.8 million.

At a time when large language models (LLMs) are revolutionizing code generation, Bito is solving an equally critical—but far less addressed—bottleneck in the development lifecycle: code review at scale.

“Everyone talks about writing code with AI. But production systems live and die by how well that code is reviewed, tested, and maintained,” said Amar Goel, Bito’s co-founder and CEO. “With this funding, we’ll expand our product capabilities and help teams navigate the flood of AI-generated and human-written code that’s only just begun.”

Agentic AI: The Next Frontier in Development Automation

What sets Bito apart is its deep commitment to agentic AI—a new class of AI systems that go beyond passive tooling to operate as autonomous agents capable of reasoning and decision-making. These agents don’t just suggest syntax improvements; they interpret architecture, detect hidden regressions, and apply fixes in real time—all within the developer’s natural workflow.

Unlike traditional tools, Bito’s AI Code Review Agent actively plans, critiques, and adapts its reviews to align with organizational best practices, tech stacks, and coding styles. Its awareness spans the local pull request context to larger architectural patterns, making it an effective partner for navigating modern, fragmented codebases.

This is part of a growing movement known as vibe coding—an emerging philosophy where developers co-create software alongside intelligent agents that understand not just syntax, but context, intent, and team-specific nuances. As vibe coding gains traction across startups and enterprises alike, tools like Bito are becoming essential to scale this symbiotic interaction between human creativity and machine precision.

“Agentic systems like Bito are transforming software creation from a static, rules-based process into a dynamic, collaborative flow—one where devs don’t just code, they vibe with the system,” said one industry analyst. “This is what vibe coding enables: fluid, fast, and deeply contextual development.”

Measurable Impact on Modern Engineering Teams

Bito’s platform currently reviews more than 10,000 pull requests every week for organizations like Gainsight, Whatfix, and PubMatic, offering significant boosts in both speed and quality:

89% faster pull request merges

34% fewer code regressions

87% of feedback generated by AI

$14 return for every $1 spent

These aren’t just numbers—they represent reclaimed developer time, increased code reliability, and reduced engineering overhead. Bito also helps junior developers onboard faster, offering best-practice guidance and one-click fixes with rich context—effectively turning every code review into a mentorship session.

“Bito doesn’t just speed up code review—it levels up your team,” said Mukesh Agarwal, Bito’s Chief Product Officer. “Whether it’s a junior dev or a staff engineer, everyone benefits from smarter, more consistent feedback.”

Built for Scale, Secured for the Enterprise

Security is fundamental to Bito’s design. The platform is SOC 2 Type II certified, does not store your code, and never uses your code to train models. For industries with stricter compliance needs, Bito supports on-premises deployment via Docker, in addition to its cloud-hosted option.

Bito’s integrations span GitHub, GitLab, Bitbucket, and soon Azure DevOps, and it supports more than 50 languages, from JavaScript and Python to Go and C#. Key platform features include:

Static code analysis with Mypy, fbinfer, and more

Security scanning using Snyk, Whispers, and detect-secrets

Custom review rules, changelists, and detailed PR summaries

Smart analytics dashboards for tracking pull request quality, velocity, and contributor insights

The company’s leadership team brings together some of the most successful minds in SaaS, adtech, and enterprise infrastructure:

Amar Goel, a Harvard graduate and founder of PubMatic, which went public on NASDAQ

Anand Das, CTO of Bito and former CTO at both PubMatic and Eyeota (acquired for $165M), with seven patents

Mukesh Agarwal, product lead with a background in Microsoft, EY, and RevX (acquired by Affle)

Together, they are building more than just a tool—they are designing a new AI-native layer in the modern software stack, where code creation and review is intelligent, automated, and collaborative.

Why This Matters Now

The shift to AI-generated and AI-reviewed code is inevitable—but with it comes risks: context erosion, increased regressions, and velocity without accountability. As companies struggle to balance productivity with code integrity, and technical debt, the rise of tools like Bito—and the broader adoption of vibe coding—offers a crucial path forward.

Bito empowers teams to thrive in this new reality by acting as a trusted engineering partner, not just a linting bot. It learns. It reasons. And it helps teams move faster without sacrificing trust in their code.

“We believe that developers are the master masons behind the future,” said the Bito founding team. “With AI as their co-pilot, the possibilities are boundless.”

Bito isn’t just reviewing your code. It’s ushering in a new era of developer productivity—one pull request at a time.

[praveennareshit]

☁️ Cloud Computing Courses for Beginners (2025): Where to Start and What to Expect

👨🎓 New to Tech? Wondering if You Can Learn Cloud Computing?

You’ve seen the job listings. You’ve heard about AWS, Azure, and Google Cloud. You might’ve even asked yourself, “Is this something I can learn, or is it only for experienced developers?”

Here’s the honest answer: Yes, you absolutely can learn cloud computing—even as a beginner. And no—you don’t need to be a coder to get started.

🧠 What Exactly Is Cloud Computing?

Let’s break it down in real-world terms.

Cloud computing is about accessing technology services (like servers, storage, and databases) over the internet instead of owning them physically. Just like you stream music without downloading every song, companies use cloud platforms to run apps without buying physical machines.

This makes cloud computing:

🔄 Scalable

⚡ Fast

💰 Cost-effective

🌐 Accessible from anywhere

Think of it as “IT on rent.”

🌐 What Are the Major Cloud Platforms?

There are three major players in the cloud computing space:

🔹 Amazon Web Services (AWS)

Largest market share globally

Great documentation and job demand

Ideal for beginners starting a cloud career

🔹 Microsoft Azure

Preferred by companies already using Microsoft services

Common in large enterprises and MNCs

Works well for IT support engineers or Windows admins

🔹 Google Cloud Platform (GCP)

Known for machine learning, analytics, and modern web apps

Growing ecosystem with startups and AI companies

Ideal for learners with interest in data + development

🎓 What to Expect from a Beginner-Friendly Cloud Course?

The right course should cover:

Cloud concepts: IaaS, PaaS, SaaS

Platform navigation (AWS Console, Azure Portal, GCP Dashboard)

Virtual Machines, storage, identity & access

Networking and basic security setup

Hands-on labs and small projects

Guidance for entry-level certifications

And most importantly, it should be beginner-friendly—not overloaded with theory or code.

🧑🏫 Why Learn Cloud with NareshIT?

At NareshIT, we’ve trained over 100,000 students in real-world IT skills. Our cloud computing courses are designed to help absolute beginners start from scratch, learn hands-on, and become confident enough to apply for jobs or certifications within weeks.

📘 NareshIT’s Cloud Computing Courses for Beginners

✅ AWS Cloud Foundations (Beginner Level)

Duration: 60 Days

Topics: EC2, IAM, S3, Lambda, VPC

Bonus: Live labs, project guidance, AWS Cloud Practitioner & Associate certification prep

Outcome: Ready for junior cloud jobs & support roles

✅ Azure Essentials Course (Beginner + Admin)

Duration: 45 Days

Topics: Azure AD, VMs, Blob Storage, Azure Monitor

Bonus: AZ-900 + AZ-104 prep, DevOps preview

Outcome: Ideal for support engineers and system admins

✅ GCP Starter Course (Beginner + Cloud Native Tools)

Duration: 30 Days

Topics: Compute Engine, IAM, BigQuery, Cloud Functions

Bonus: GCP Associate Cloud Engineer certification coaching

Outcome: Great for data lovers and devs entering cloud

🎓 DevOps with Multi-Cloud Training in KPHB by NareshIT

Located in Hyderabad’s tech-learning hub, NareshIT’s DevOps with Multi-Cloud Training in KPHB is tailored for:

✅ Beginners who want an IT job fast

✅ Professionals switching from support/manual testing

✅ Freshers looking for job-ready cloud + DevOps skills

🧾 Course Highlights:

Cloud Platforms Covered: AWS, Azure, GCP

DevOps Tools: Git, Jenkins, Docker, Kubernetes, Terraform

Duration: ~60 days

Batch Options: Weekday, Weekend, Fast-track

Includes: Real-world projects, certification support, job readiness prep

Location: KPHB, Hyderabad (Online + Offline options)

📅 New Batches Are Starting Now Choose from weekday, weekend, or fast-track options based on your schedule.

👉 Check NareshIT's Latest Cloud Batches Here

🧩 Bonus: Why Learning Cloud Computing Is Worth It

💼 High-demand job roles: Cloud support, DevOps, Admin

💸 Strong entry-level salaries: ₹4.5 to ₹7 LPA (for certified freshers)

🌱 Fast career growth: Start simple, grow into architecture or security

🌍 Global opportunities: Remote jobs across India, US, UAE, and more

You don’t need to master everything at once. Just start with one platform. And with the right mentor, you'll move faster than you thought possible.

[la-principessa-nuova]

today i was trying to figure out why a config file wasn’t getting parsed correctly, and the junior dev i was pairing with said “why don’t you ask copilot if it has any ideas” and i held my tongue because i know the clueless higher-ups set increasing AI adoption as one of our goals for the year

but I was just thinking like… what is it going to do that googling it is not already doing? I can see the error message, it makes so sense that it’s appearing, and all the standard troubleshooting steps aren’t working. I don’t need an AI to list them for me with some made up ones thrown in.

anyway, it ended up being because the IDE was bugged out and not running any of the things that are supposed to be triggered on save, which meant the changes weren’t getting staged in git, and the thing we were running ran against the staged changes, and there’s just no way the AI would generate that as a suggestion, especially since until I knew the issue I hadn’t even considered the IDE would be involved, so I wouldn’t have mentioned anything about the IDE to the AI. I only solved it because I gave up and went to do something else and noticed it was being weird and that lead to realizing the actions weren’t running on save.

and i’m even setting aside moral reasons not to use it, just purely talking about the fact that it wasn’t even an appropriate tool for that situation. and i know it’s cliche to worry about younger people not learning how to do anything because it’s done for them by new tools, but i worry about the junior devs only knowing to do basic programming tasks and then relying on the AI for questions about problems like that, because when it is right on basic questions, they won’t gain the experience digging into the system for when they face something complicated like this that the AI wouldn’t know how to solve.

And what if it hallucinated a solution that broke the project config, or solved a slightly different problem that seems similar if you don’t really dig into it? I think I’ve already seen some stuff like where I’m just scratching my head wondering why it seems off and then I realize it’s off in the same way AI-generated code is off.

[jamesmitchia]

AI vs Junior Devs: Threat or Tool?

Let’s be real—AI coding assistants are getting really good. Tools like GitHub Copilot, ChatGPT, and CodeWhisperer can now generate snippets, complete functions, and even help debug code in seconds. It’s no wonder there’s a growing concern (especially among junior developers) about whether these tools are taking over their roles.

But here’s the thing: while AI is evolving fast, the narrative that it's replacing junior devs is oversimplified—and a little unfair.

AI coding assistants are just that—assistants. They’re not logging into Jira, joining stand-ups, understanding project context, or making product decisions. They lack the creative problem-solving, empathy, and real-world decision-making that human developers bring to the table.

That said, the junior dev role is changing. So let’s unpack that.

So, what's really happening?

Automation of Repetitive Tasks: AI is great at handling boilerplate code, basic algorithms, and syntax fixes—things junior devs used to cut their teeth on.

Faster Onboarding: New devs can now use AI to learn and produce faster, but they still need mentorship to grow.

Higher Expectations: Companies might expect junior devs to understand how to use AI as part of their workflow.

Shift in Learning Curve: Instead of memorizing syntax, new devs are focusing more on architecture, logic, and communication.

Human Skills Still Matter: Teamwork, curiosity, problem-solving, and the ability to ask good questions are irreplaceable.

In short, AI coding assistants are reshaping how junior devs work—not replacing them. Think of it as Iron Man's suit: it amplifies your abilities, but you still have to know how to fly.

About US: AI Technology Insights (AITin) is the fastest-growing global community of thought leaders, influencers, and researchers specializing in AI, Big Data, Analytics, Robotics, Cloud Computing, and related technologies. Through its platform, AITin offers valuable insights from industry executives and pioneers who share their journeys, expertise, success stories, and strategies for building profitable, forward-thinking businesses.

Contact Us :

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[web-codder]

💼 The 5 Paid Subscriptions I Actually Use in 2025 as a Staff Software Engineer

Let’s be honest — subscription fatigue is real. With everything from newsletters to toothbrushes asking for a monthly fee, it’s easy to feel like your wallet is bleeding through a thousand microtransactions. 🩸 As a Staff Software Engineer with over a decade in the tech world, I’ve subscribed to more tools, apps, and services than I care to admit — many of which were just okay. But a few? Game-changers. 🚀 So today, I’m pulling back the curtain on the 5 paid subscriptions I actually use in 2025, and more importantly, why I keep paying for them month after month. These tools save me time, streamline my workflow, and even help with my mental clarity. Whether you're a junior developer climbing the ranks or already leading engineering teams, this list might just become your new productivity toolkit. 🧠 1. Raycast Pro – $8/month The spotlight replacement that runs my desktop. Raycast has been my go-to productivity launcher for a couple of years now, but in 2025, their Pro tier has completely won me over. Why I use it daily: Superfast file search 🔍 Snippets for code, email templates, and CLI commands AI-powered commands (built-in GPT-4 Turbo) Custom scripts (Python, JS, Bash – you name it) Deep integrations with GitHub, Jira, Notion, Linear, and more As a Staff Engineer, my day flips between code reviews, design docs, debugging, and mentoring. Raycast Pro brings everything under my fingertips, cutting through context switches like a hot knife through butter 🔪🧈. Favorite Feature: I built a custom Raycast command that fetches open PRs across my org and even summarizes them using GPT — talk about dev superpowers. ⚡ Verdict: ✅ Totally worth $8/month for power users. 🔗 https://raycast.com/ 📁 2. Notion Plus – $10/month My second brain for everything personal and professional. Some engineers live in Obsidian or Evernote — I’m a Notion evangelist. While the free version is excellent, the Plus plan unlocks the real magic if you're working with teams or building advanced systems. Why it’s essential: Personal and team wikis Engineering architecture docs Career journaling & 1:1 prep Goal tracking & habit dashboards AI assistant for writing & summarizing In 2025, Notion’s AI has gotten seriously good. I use it to refactor messy meeting notes, summarize long engineering retros, and even brainstorm architecture trade-offs before I put pen to paper. ✍️🧠 Pro Tip: I maintain a “Staff Engineer Hub” inside Notion that links to my project artifacts, strategy docs, incident postmortems, and mentorship logs — one of the best ways I track my impact across teams. Verdict: 💯 Can’t live without it. 🔗 https://www.notion.so/ 💬 3. ChatGPT Plus – $20/month Your always-available pair programmer, meeting assistant, and technical buddy. Look — I’m not just writing this because this article is hosted on ChatGPT. I genuinely use the Pro version of ChatGPT (powered by GPT-4 Turbo) every single day. And no, I don’t believe AI is replacing engineers — but it's definitely leveling us up. 🚀 Here’s how I use ChatGPT Plus: Break down unfamiliar codebases (especially in onboarding) Summarize technical design proposals Draft PR descriptions and commit messages Prototype scripts or utilities Brainstorm team strategy or OKRs Generate interview questions for hiring panels 2025's GPT-4 Turbo is blazing fast, context-aware, and can now access custom GPTs — I have one that simulates a “DevOps mentor” I can ask about AWS and Terraform at 2am 😅 Is it perfect? No. It occasionally hallucinates, and I always verify its output — but it's like having an insanely smart junior dev by your side at all times. Verdict: 🧠 If you write code, docs, or even just emails — it’s a must-have. 🔗 https://chat.openai.com/ 🧘 4. Headspace – $12.99/month Because engineers need mental health too. Let’s take a break from tech tools and talk about something more important: our minds. The transition to Staff Engineer isn’t just technical — it’s deeply human.

Between cross-functional communication, driving influence without authority, and mentoring others, I’ve had days where my brain felt like a 200-tab Chrome window. 🧠🔥 Headspace has helped me slow down, focus, and breathe. How I use it: Morning focus meditations before deep work sessions Sleepcasts after late-night deployments Anxiety relief exercises before big presentations 5-minute mini-breaks between back-to-back meetings I originally thought meditation apps were “woo-woo,” but after a particularly tough quarter, I gave it a shot. Three years later, I consider it part of my engineering toolkit. Verdict: 🧘‍♂️ It’s cheaper than therapy and sometimes just as effective. 🔗 https://www.headspace.com/ 📚 5. O’Reilly Learning Platform – $49/month (covered by work) Still the gold standard for deep, technical learning. We’ve all bought 200-page PDFs from obscure newsletters, but when I need reliable, deep, up-to-date technical knowledge, I go to O'Reilly. Why I love it: Full access to industry-standard books and videos Hands-on coding environments (for Rust, Go, Kubernetes, etc.) Live online training and certifications Sandboxes for AWS, GCP, and Azure Proven content from actual experts, not AI-generated fluff As a Staff Engineer, staying current matters. Whether I’m leading a system redesign or exploring a new architecture pattern (hello, event-driven microservices), O’Reilly is my go-to. Bonus: Most companies will reimburse or directly provide access to this platform. If yours doesn’t — ask for it during performance reviews or L&D discussions. Verdict: 📚 Essential for any serious technologist. 🔗 https://www.oreilly.com/ 💭 Honorable Mentions Here are a few other paid tools that didn’t make the top 5 but are still solid: 1Password Teams – $7.99/month: Best password manager for work & personal GitHub Copilot – $10/month: Useful, but I use ChatGPT more Grammarly Premium – $12/month: For PRs and tech blog clarity Linear (Pro) – $8/month: Fastest issue tracker in existence Tailscale – $10/month: Zero-config VPN and private networking 🎯 Final Thoughts: Don’t Pay for Tools — Pay for Leverage It’s easy to get distracted by the shiny new thing. But here’s my philosophy: "If a tool helps me think better, work faster, or sleep more peacefully — it's worth every penny." As a Staff Engineer, your job is no longer just about pushing code. It’s about scaling yourself: your knowledge, your influence, your communication, and your decision-making. The subscriptions I pay for help me do exactly that. So if you’re on the fence about paying $5, $10, or even $50 a month — ask yourself this: Would you pay that much for 5 extra hours of focused output? For a calmer mind? For better code? Because I would. And I do. 👋 Over to You! Are you a developer or tech lead with favorite tools that make your life easier? Drop a comment or DM me on LinkedIn — I’d love to trade tool stacks. 📲 Connect: https://www.linkedin.com/in/webcodder 📺 YouTube: https://www.youtube.com/@web_codder 📸 Instagram: https://www.instagram.com/web_codder_official

[transparencyhub]

How AI Coding for Junior Programmers Enhances Learning

The rise of artificial intelligence (AI) in software development has significantly transformed how programmers approach coding. AI is no longer just a tool for experienced developers; it has become a valuable resource for junior programmers looking to strengthen their coding skills. AI-powered coding assistants help newcomers navigate the complexities of programming by offering real-time suggestions, error detection, and automated code generation. 

This article explores how AI coding for junior programmers enhances learning and simplifies the journey for those new to software development. By using tools like AI code generators and AI-powered coding assistants, junior developers can accelerate their learning process and build confidence in their abilities.

The Role of AI in Learning to Code

How AI Tools Support Junior Developers

AI has introduced innovative ways to help junior programmers overcome challenges. An AI tool for junior devs provides instant feedback, allowing beginners to understand coding concepts faster. These tools analyze the code, detect syntax errors, and suggest improvements, reducing the frustration often associated with learning to code. By using AI-powered coding assistants, junior developers can focus on logic and problem-solving rather than getting stuck on syntax or minor errors. This shift in focus helps them build a strong foundation in programming principles.

Benefits of Learning to Code with AI

Immediate Feedback: AI-powered tools analyze code in real-time and suggest optimizations, helping junior programmers learn from their mistakes.

Guided Learning: The best AI coding assistant provides structured recommendations, guiding new developers through different coding challenges.

Faster Debugging: AI-driven debugging features highlight errors and suggest fixes, making it easier to resolve issues quickly.

Efficient Code Generation: An AI code generator automates repetitive tasks, allowing junior developers to focus on problem-solving.

AI-Powered Coding Assistants and Their Impact

Making Coding More Accessible

For beginners, coding can be intimidating due to the complexity of programming languages and logic structures. AI-powered coding assistants simplify the learning process by breaking down complicated code into understandable components. With AI coding tool for junior programmers, learners can explore different programming languages and frameworks without feeling overwhelmed. These AI tools provide explanations for functions, variables, and syntax, making it easier for new developers to grasp fundamental concepts.

Enhancing Problem-Solving Skills

While AI tools assist in writing code, they also encourage junior programmers to think critically. Instead of simply providing answers, the best AI for writing code suggests multiple solutions, helping learners understand different approaches to problem-solving. By using an AI-powered coding assistant, junior programmers develop the ability to analyze problems and optimize their code. This skill is essential for professional growth, as efficient coding is a key aspect of software development.

Choosing the Best AI Coding Assistant for Learning

Key Features to Look For

Not all AI coding tools are created equal, and junior developers should select an AI-powered coding assistant that aligns with their learning goals. Some essential features to look for include:

Code Suggestions: The best AI for writing code offers intelligent suggestions that improve code efficiency and readability.

Error Detection: AI tools identify mistakes in real-time, reducing debugging time.

Integration with IDEs: A good AI tool for junior devs should integrate seamlessly with development environments like VS Code, PyCharm, or IntelliJ.

Multi-Language Support: For learners exploring different programming languages, an AI code generator that supports multiple languages is beneficial.

Popular AI Tools for Junior Programmers

Several AI-powered coding assistants cater to junior developers, offering various features to enhance learning. Some of the most widely used AI tools include:

GitHub Copilot: A widely recognized AI coding assistant that provides real-time code suggestions and explanations.

Click-Coder: A free AI-powered coding tool that helps junior programmers understand and improve their code.

Tabnine: An AI-driven assistant that enhances code completion and syntax suggestions.

Each tool has unique strengths, and choosing the right AI tool for junior devs depends on individual learning preferences and coding goals.

Learning to Code with AI: Best Practices

Balancing AI Assistance and Manual Coding

While AI tools offer tremendous support, it’s important for junior programmers to strike a balance between using AI and writing code manually. Relying too much on AI-powered coding assistants can limit problem-solving skills, so beginners should actively engage in coding exercises and try to solve problems before seeking AI-generated solutions.

Practicing Code Optimization

AI-generated code is not always the most efficient. Junior programmers should analyze AI suggestions and optimize their code to enhance performance and readability. By refining AI-generated code, developers gain detailed insights into best coding practices.

Exploring Real-World Projects

To reinforce learning, junior programmers should apply AI-assisted coding to real-world projects. Building applications, contributing to open-source projects, or working on personal coding challenges can help learners gain practical experience and confidence in their abilities.

The Future of AI Coding for Junior Programmers

AI’s Evolving Role in Software Development

As AI continues to advance, its role in software development will become even more significant. AI-powered coding assistants are expected to become more intuitive, offering even better recommendations and deeper insights into code quality. For junior programmers, this means a more interactive and personalized learning experience. Future AI tools may incorporate voice-based coding assistance, advanced debugging features, and even virtual mentors that guide learners through complex coding challenges.

Ethical Considerations in AI-Assisted Coding

With the growing use of AI in coding, ethical considerations such as code originality, security, and dependence on AI need to be addressed. Junior developers should understand how to use AI responsibly and ensure that their code adheres to ethical programming standards. By staying informed and using AI tools wisely, junior programmers can make the most of AI’s capabilities while developing their coding skills independently.

Conclusion

AI coding for junior programmers has revolutionized the way beginners learn and develop their skills. By leveraging AI-powered coding assistants, junior developers can gain valuable insights, enhance their problem-solving abilities, and improve their coding efficiency. While AI tools offer significant benefits, it is essential for learners to balance AI assistance with manual coding practices.

By actively engaging with coding exercises, optimizing AI-generated code, and contributing to open-source projects, junior programmers can build a solid foundation for a successful career in software development. With AI continuing to evolve, the future of coding education looks promising, offering more accessible and intelligent learning experiences for aspiring developers.

Frequently Asked Questions (FAQs)

How can AI help junior programmers learn to code?

AI helps junior programmers by providing real-time code suggestions, error detection, and guided learning. AI-powered coding assistants simplify complex concepts, making coding more accessible for beginners.

What is the best AI coding assistant for beginners?

The best AI coding assistant depends on the programmer’s needs. GitHub Copilot, Click-Coder, and Tabnine are some of the top AI tools that help junior developers improve their coding skills.

Can AI completely replace learning to code manually?

No, AI should be used as a learning aid rather than a replacement. While AI-powered coding assistants provide support, junior programmers should still practice coding manually to develop problem-solving skills and a deeper understanding of programming concepts.

Is AI-generated code always correct?

AI-generated code is not always perfect. Junior programmers should review and optimize AI-generated code to ensure accuracy, efficiency, and best practices in software development.

How can junior developers make the most of AI coding tools?

Junior developers should use AI coding tools as learning aids, analyze AI-generated code, practice manual coding, and apply their knowledge to real-world projects to enhance their programming skills.

[davidfegan]

React native App Development Services

React native App Development Services from Agicent ?

We used to use various flavors of Javascript long before react native came into being and once it came, we went all big on it. There were times when React-native and other cross platform technologies (like Flutter, Ionic, QT) were only good for creating App MVPs and had a lot of issues such as integration with third party libraries, with Device’s own hardware capabilities and so on. But today as of mid-2022 we can safely say that React Native can help building as good or superior apps as a native tech would do and that do with single coding effort. Its like Java of old days, “Write once, run anywhere”.

Theoretically, an App that you can make in React-native can be created in Flutter or ionic or in native technologies too. However, if we have to rate the cross-platform technologies, react native rules the roost hands down because of its larger community support, flexible frameworks, and capability to generate the native code over other platforms.

Rates for react native App Developers on Demand

Following is the standard rate card for different Exp and skill levels of On Demand Reac Native App Developers. Besides this, we can also create a custom on Demand App Team and optimized the monthly rate based on our specific needs.

Junior React Native Developer

Exp. Level: 1-2 Years

Hands on react native Development.

3 Projects experience minimum.

Agicent’s inhouse trained.

Familiar with PM Tools

Perfect for rapid MVPs and maintenance react native works

Starting at

$ 2200 /mo.

Mid-level React Native Developer

Exp. Level: 2-5 Years

All of Jr. Dev +

10 Projects experience minimum.

Has Backend Experience.

Hands on CI/CD pipeline.

Manages Jr. Developers.

Perfect for complex react-natived projects and fast Development

Starting at

$ 2900 /mo.

Senior React Native Developer

Exp. Level: 5+ Years

All of Mid-level Exp +

15 Projects experience minimum.

Full Stack Developer.

Participate in Architecture.

Ability to play Tech. Lead Role.

Perfect for bigger size projects with multi teams

Starting at

$ 3800 /mo

BEST Practices followed by Agicent React Native App Development Company

First and foremost, we critically analyze if the App project is a good candidate for cross platform or react native development or not. In some pretty niche Apps, native can still be a technology of choice so ruling out this possibility is most important first step. Once it is identified that react native is the tech of choice, we then figure out the backend stack (like node.js or graphql, or traditional LAMP stack), or web front-end third-party libraries, like vue.js, typescript, redux etc. If it’s a regular kind of app that we do time and again (like a dating app or ecommerce app, or healthcare app) then we decide on tech stack in few hours only; if it is a niche one- of-a-kind project (like an AI based app suggesting you medicine dosage or an App that heavily uses some third- party APIs for its core function – like creating digital avatars or facilitates Holoportation) then we take more than few hours to check on libraries, their scalability with react native and then decide.

Performance optimization, Build optimization

Native applications are top performers because they use stock APIs, patters, and enjoy best support from the OEM’s OS and hardware and you achieve great performance by the virtue of the platform. However, in case of creating a react native app, which is cross platform by the way you have to use a variety of testing tools (like Appium, jest, detox etc), be more meticulous for performance parameters, and optimize your code for best performance across different devices. It can be a time-consuming exercise at times, but totally worth it and warranted.

For react native app development, you have to take care of multi-threading, third party library integration in optimized way, image compression, APK or iPA file size optimization and lot more what you don’t really do when doing native app development.

Limitations of React Native App Development

Lack of native libraries:

If the app has a lot of features, React Native can slow down the development process due to a lack of native libraries and reliance on external, third-party libraries.

Takes more time to initialize:

The issue with React Native is that it takes more time to initialize the runtime for gadgets and devices, mostly because of the JavaScript thread which takes time to initialize.

Excessive Device Support required

Due to the variety of OEM Devices size, Type, Version, and OS Versions, it is challenging for a developer to provide full support to all the app uses in one go, so it becomes sort of a continuous exercise to extend support to more and more devices.

Still in pre-mature face

React native latest version is 0.68 as of June 2022, which shows that it is still in face of evolving which is why it still have lack functionality. Good thing is that it is continuously maturing and have community support with big tech giants like Facebook & tesla also it easy to learn and understand even for the beginner.

React Native Doesn’t Fully Support NFC

NFC enables the communication between nearby devices. But React Native Devices still don’t support or provide full access for NFC communication.

Future of React Native Development

Start-up first choice

Many big names like Facebook, Instagram, tesla and all have an app on react native also react native becomes one of the most discussed libraries on StackOverflow. Most startup and even enterprise start adopting it because it only needs a single manager to manage for both android and IOS app development which save it time, resources and money.

Better integration with Device’s and external Hardware

We are already working on some react native projects where we are interacting with external hardware (using Silabs or infi semiconductors) and have found that react native doesn’t always get priority support, however this is going to be changed in the future. React native will be more scalable and easier to integrate with device’s own hardware as well as external Hardware (Bluetooth, NFC devices).

Open the gate for new open-source frameworks

The domain-specific engineers are meet-up and do conferences in which each platform bring their own player who are working on a similar problem. Like web where react (which power react-native) which commonly draw inspiration from other open-source web frameworks like: Vue, Preact & Svelte. On mobile, React Native was inspired by other open-source mobile frameworks, and we learned from other mobile frameworks built within Facebook.

Source: https://www.agicent.com/react-native-development-company

[techy-guy]

Sachin Dev Duggal | Artificial intelligence is poised to disrupt the labor market in the near future

A McKinsey & Company survey claims that up to 30% of all humans hour work worldwide may be task-automatized due to AI before 2030. The World Economic Forum predicts that between 85 million and 100 million jobs will be done away with globally by automation and artificial intelligence, while about 97 million new ones will spring up concurrently. Nevertheless, this transition has significant hurdles because most newly created positions require specific skills or training, which displaced people do not have; hence, skill gaps are hard to fill quickly.

Sachin Dev Duggal, Chief Wizard at Builder.ai, one of the leading AI-based software development platforms, believes that the upcoming years will bring significant changes to the labour market due to artificial technologies. "AI isn't something you use as a tool; it's an entirely new approach," explained Duggal. "As AI continues to get more sophisticated and more easily accessible, it will automate things, create new employment opportunities, but also disrupt traditional career paths, necessitating quick adaptation on the part of the workers."

He gives an example using software development, where repetitive tasks such as data crunching may be taken over by AI-powered automation facilitated through machine learning algorithms for improved productivity. "Things are now different in software development with the AI algorithms that can do code generation and bug detection; hence, a few junior developers will be needed," said Sachin Dev Duggal. "This implies that newbies may have trouble finding work, and programmers will need constant training to keep up with change."

[random-hunter]

I'm a software dev and my company has made it mandatory for everyone to use Copilot. We are one of the largest software development companies in the world. As much as I hate it, it is incredibly useful for software development. Coding languages are constantly changing so it is impossible for anyone to know everything about one language and most of us are working in multiple languages. But now we have a tool that can give us updated information and explain anything we have questions on. From the business side, this means we no longer need junior devs because our seniors can now do twice as much work with half the mistakes.

Another example from our company, they had a team create an AI that can answer HR questions. So now instead of an HR team of 50* people who are answering the questions of our hundreds of thousands of employees, we can have the AI answer the 90% of questions that are predictable, and have 5* people who deal with the more complex issues.

*I have no idea how large our HR team was/is. I just know my friend was exited to work on this until I pointed out that it would be used to eliminate jobs. "No, it's just a cool tool! It will make their jobs easier!" "Yeah, so then one person can do the work of 3 and you get to cut labor."

I think generative AI has improved a lot over the last 18 months for the people who use it, and it will continue to do so as the blockers to its growth are removed. When I asked it what topics it's asked about the most, it's top 3 topics were related to software development and 4th was "general knowledge". And that's why it's good at code but shit at understanding how many fingers humans have.

AI hasn't improved in 18 months. It's likely that this is it. There is currently no evidence the capabilities of ChatGPT will ever improve. It's time for AI companies to put up or shut up.

I'm just re-iterating this excellent post from Ed Zitron, but it's not left my head since I read it and I want to share it. I'm also taking some talking points from Ed's other posts. So basically:

We keep hearing AI is going to get better and better, but these promises seem to be coming from a mix of companies engaging in wild speculation and lying.

Chatgpt, the industry leading large language model, has not materially improved in 18 months. For something that claims to be getting exponentially better, it sure is the same shit.

Hallucinations appear to be an inherent aspect of the technology. Since it's based on statistics and ai doesn't know anything, it can never know what is true. How could I possibly trust it to get any real work done if I can't rely on it's output? If I have to fact check everything it says I might as well do the work myself.

For "real" ai that does know what is true to exist, it would require us to discover new concepts in psychology, math, and computing, which open ai is not working on, and seemingly no other ai companies are either.

Open ai has already seemingly slurped up all the data from the open web already. Chatgpt 5 would take 5x more training data than chatgpt 4 to train. Where is this data coming from, exactly?

Since improvement appears to have ground to a halt, what if this is it? What if Chatgpt 4 is as good as LLMs can ever be? What use is it?

As Jim Covello, a leading semiconductor analyst at Goldman Sachs said (on page 10, and that's big finance so you know they only care about money): if tech companies are spending a trillion dollars to build up the infrastructure to support ai, what trillion dollar problem is it meant to solve? AI companies have a unique talent for burning venture capital and it's unclear if Open AI will be able to survive more than a few years unless everyone suddenly adopts it all at once. (Hey, didn't crypto and the metaverse also require spontaneous mass adoption to make sense?)

There is no problem that current ai is a solution to. Consumer tech is basically solved, normal people don't need more tech than a laptop and a smartphone. Big tech have run out of innovations, and they are desperately looking for the next thing to sell. It happened with the metaverse and it's happening again.

In summary:

Ai hasn't materially improved since the launch of Chatgpt4, which wasn't that big of an upgrade to 3.

There is currently no technological roadmap for ai to become better than it is. (As Jim Covello said on the Goldman Sachs report, the evolution of smartphones was openly planned years ahead of time.) The current problems are inherent to the current technology and nobody has indicated there is any way to solve them in the pipeline. We have likely reached the limits of what LLMs can do, and they still can't do much.

Don't believe AI companies when they say things are going to improve from where they are now before they provide evidence. It's time for the AI shills to put up, or shut up.

[codemerything]

untitled.28.13

I was pretty excited about AI when ChatGPT 3 dropped and i used it as another tool to increase productivity and my learning. Everything was going well until ChatGPT 4 dropped and I panicked so hard and started overthinking everything: I was mentally drained for two days, I didn’t code or do anything. I was just reading tweets from senior devs saying

“Junior Devs roles won’t be needed with the advancement in AI”

“If AI continues at this pace of advancement, so many jobs will be taken”

like can you fucking chill?🙄😒 I just got my life together and started learning JS, and this is not encouraging. Well, I decided to do research and I read some positive and realistic takes from other optimistic devs and I even listened to a really long podcast from the CEO of OpenAi to fully understand what I am worried about and to make my own decision

SPOTIFY LINK TO THE PODCAST

Anyway, I’m still scared but I’ll still learn how to code because whatever is happening is out of my control and learning to code is something I can control and do and that’s what I’m going to do. Have a nice day ✌️

[applitools]

Monthly Testing Links (Oct 2017)

Guest post by Gil Tayar, Senior Architect at Applitools

My monthly lists of blog posts about testing that I read and have found interesting enough to share.

Browser and Mobile Testing

AUTOMATING VISUAL REGRESSION TESTING, Viv Richards: Really great post about why visual testing is such a hot topic right now and how it improves both the quality and speed of your testing.

Strategies for automated visual regression, Katrina Clokie: what it says — real world tips and strategies on how to add visual testing to your suite.

Dealing with Selenium API Gotchas, Stephen Haberman: Do you want your browser automation tests to stop being flaky? Read this article! A plethora of great advice that I’ve never seen anywhere.

Email Validation Testing: How to Test the Email Functionality of an Application, Nandini K. (Software Testing Help): an encyclopedic post that has everything you need to know about testing the email functionality of an app. And when I say it has everything, I mean it.

Foxdriver: A Node.js Remote Debugging Client, Christian Bromann (SauceLabs): Chrome DevTools has puppeteer, and now, thanks to SauceLabs, Firefox has FoxDriver, an alternative to Selenium WebDriver that works directly with Firefox’s Remote Developer Tools protocol. Love it!

AI and Test Automation

Not Only Cars: The Six Levels of Autonomous Testing, Gil Tayar (shameless plug): Can AI automate this process? Can we make some, or all parts of our testing, and writing our tests, autonomous? Can AI do to writing tests what it is doing to driving?

AI for Testing: Identifying App State, Jason Arbon (AppDiff): how to use machine-learning techniques to make the AI recognizing types of pages automatically.

Dev Testing

The problem that unit tests solve, Theodore Bendixson: a different view on unit tests. Unit tests as a way to test difficult to trigger situations. The example of testing a chess game is spot on! As a lover of integration tests, this take on unit tests explains exactly when unit tests, and not integration tests, are a solution.

Write tests. Not too many. Mostly integration, Kent C. Dodds: Kent Dodds is reading my mind. There is not one sentence in this blog post that I disagree with. This article is a “practical school of testing” article. Read it. Now.

Baseline Testing, Tingan: Tingan gives the case that even unit tests can gain from writing the test validation as baseline testing, vs. checking for explicit results. This approach is heavily used in visual testing, where there is no other option, but has been popularized by Jest’s “snapshot” methods.

Beginner’s Testing

How frontend unit testing turned from a fling to a real thing for me, Mirjam Bäuerlein: “for a long time, all I knew about testing was more on an academic level”. This is a story of Mirjam’s journey from thinking testing is an academic thing, to getting serious about testing.

Funny Tweet, Vranac Srdjan:  YOU ARE IN A LEGACY CODEBASE > RUN TESTS YOU HAVE NO TESTS > READ SPEC YOU HAVE NO SPEC > WRITE FIX YOU ARE EATEN BY AN ELDER CODE HACK.

Microservice Testing: Introduction, Nathan Peck: an introduction to the testing pyramid and how to write testing code. Good introductory article, though mis-named, as it has nothing to do with microservices.

Frontend Development

Building the DOM faster: speculative parsing, async, defer and preload, Milica Mihajlija: an excellent article about how browsers deal with the <script> tag and how developers can use to build faster-loading websites. Excellent in-depth information.

Size Limit: Make the Web lighter, Andy Barnov: I love these kinds of articles which read a bit like detective novels. In this post, our detective slowly uncovers who the murderous npm module is that creates so big a webpack bundle, and shrinks the bundle x5000 smaller.

h2, h3, h4, h5 { font-weight: bold }

About the Author: 30 years of experience have not dulled the fascination Gil Tayar has with software development. From the olden days of DOS, to the contemporary world of Software Testing, Gil was, is, and always will be, a software developer. He has in the past co-founded WebCollage, survived the bubble collapse of 2000, and worked on various big cloudy projects at Wix. His current passion is figuring out how to test software, a passion which he has turned into his main job as Evangelist and Senior Architect at Applitools. He has religiously tested all his software, from the early days as a junior software developer to the current days at Applitools, where he develops tests for software that tests software, which is almost one meta layer too many for him. In his private life, he is a dad to two lovely kids (and a cat), an avid reader of Science Fiction, (he counts Samuel Delany, Robert Silverberg, and Robert Heinlein as favorites) and a passionate film buff. (Stanley Kubrick, Lars Von Trier, David Cronenberg, anybody?) Unfortunately for him, he hasn’t really answered the big question of his life - he still doesn't know whether static languages or dynamic languages are best.

[our-beginnings]

Nick Caldwell, VP Engineering at Reddit

First thing’s first: tell us a bit about who you are, and what you do now.

Sure! I’m Nick Caldwell, and I’ve been VP of Engineering at Reddit for the past 9 months. Before that I had a 13 year career at Microsoft where I worked my way up from intern to General Manager of a product group called Power BI. I live in San Francisco with my wife Tia and dog Poochie (a corgi, because Cowboy Bebop). I grew up in Largo, Maryland which is a little suburb to the south east of D.C. as an only child.

Besides building the team at Reddit, lately I’ve been doing a lot of writing about management, participating in /dev/color, and am starting up a scholarship fund called Color Code.

What's does your day-to-day at Reddit look like? What’s your favourite part about it?

Management is all about making sure that your team has everything they need -- inspiration, tools, processes -- to head in the right direction together. Over the last year, Reddit has undergone a lot of change and there’s more to come. A big part of my job is organizing the engineering team and making sure that we are delivering new features to users on time with high quality. So on a typical day you’ll see me tracking engineering work in JIRA, coordinating upcoming features with the PM team, working with our network of vendors/contractors, and coaching my staff.

A sort of mission statement we like to say around the office is that “everyone has a home on Reddit” and I look forward to making that a reality.

There’s no one favorite thing about my job, so I’ll give you three. First, it’s pretty amazing that I get to come into work every day and make Reddit better. I have been a Redditor for just shy of a decade and it’s always been one of my favorite sites to learn, laugh, kill time, and more. There is nothing better than getting to work on a product you love alongside a great team, which is the second thing I like about my job! Reddit’s engineering organization is packed deep with some of the smartest yet low-ego engineering minds I’ve encountered. We’ve also got a “People and Culture” team that does a great job of making Reddit a fun place to work. Probably my favorite example of this is the all-company trip to Lake Tahoe. The final thing I love is Reddit’s potential. We have 300M monthly active users but there’s a lot we’re doing this year that should drive the number even higher. A sort of mission statement we like to say around the office is that “everyone has a home on Reddit” and I look forward to making that a reality.

When you were a kid, your dad brought home a Tandy 1000— is this where your love for coding began? 

I was only about 4 years old then, so I don’t remember much about it other than that I learned enough to play my favorite games: Reader Rabbit, Pac Man, Tank!, and a few others. When I watch my nieces play with their iPads and iPhone nowadays, I suspect they are far more tech savvy than I was at that age.

At that time no one in my life knew about computer programming. But gamers and coders have a lot in common. They share the same systematic ways of thinking about problems, the desire to optimize systems, and the superpowered ability to stare at screens for hours at a time. So inevitably, my love of games eventually transformed into coding.

What was your ‘eureka'  moment—the one that, if you look back on it now, sparked your journey? How did it feel? Was it “Hello World”? 

In junior high school, I had a friend named Billy, and we were great friends back then because we both loved video games and were both absolute nerds. One day he invited me over for video games at his house. I was expecting Super Nintendo but what I got instead was an absolutely epic re-introduction to PCs.

Billy had LHX Attack Chopper [pictured above], Wing Commander, and Wolfenstein 3D. These were all amazing, groundbreaking PC games at the time. After that, Billy launched a game he had written himself in QBasic. It wasn’t especially complicated but he showed me how he could change the scoring system and game text, then relaunch the game with the changes. Then he used a 2400 baud modem to dial into a local Bulletin Board System called “The Illusionary Forest” and download a copy of Commander Keen.

I was completely blown away by all this. I biked home after that and begged my father to buy a new PC, which we did a few weeks later on a trip to Micro Center.  

Out of all that experience, it was the BBS that stuck. BBSs were a doorway to a much bigger world, where I could be anyone I wanted to, talk to whoever I wanted to, learn more than I could at school. I eventually learned to code so that I could write and sell my own BBS software.

Of course, the first program I wrote was “Hello World” in C++, but I think the real catalyst for my coding career was watching my friend hacking on QBasic and imagining what I could do when it was my turn.

BBSs were a doorway to a much bigger world, where I could be anyone I wanted to, talk to whoever I wanted to, learn more than I could at school.

A bit later, I was also introduced to the idea of starting something of my own, the Silicon Valley dream; I was in a summer program call MITES (Minority Introduction to Science and Technology) hosted at MIT. It prepared me for the school and introduced me to entrepreneurship.

You went from that Maryland/DC magnet school to MIT, then to Microsoft. What brought you to Reddit eventually?

Before Microsoft, I got my first paid internship as an engineer at NASA working on software for x-ray detectors. In school, I became fascinated by AI and machine learning and game programming, and that resulted in my first internship at Microsoft on the Direct3D team.

My first fulltime job, though, was at Microsoft— first working on natural language processing components, which led to learning about enterprise search, information retrieval, machine translation, and machine learning. After that, I jumped into business intelligence where I picked up knowledge about data modelling, data visualization, in memory databases, and advanced analytics. Somewhere in the middle of all that I got my MBA from UC Berkeley, became a General Manager, and started learning about the inner workings of marketing, finance, and business development. Because of MITES, I was continually coming up with ideas with that startup mindset; I always wanted to do something, but it was safer and still fun to stay inside Microsoft and do "intra-preneurial" projects. Now I’m at Reddit and it’s great fun to pick up knowledge about consumer products, online ads, and venture capital.

Going to Reddit was a shock to a lot of people in my life. I had been at Microsoft 13 years and was having one of the fastest career trajectories possible. I’d also built a truly amazing team. I think if I were still there I’d probably be working with my mentor James on how to become a corporate vice president at a large company. But a combination of things finally got me to leave: 

First was a mental shift around how “safe” I felt. I realized that a lot of my energy and motivation came from proving myself through work and that my validation came in the form of promotions and money. But at a certain point, money just stopped being a huge motivator for me and by the time I became a General Manager there was nothing left for me to prove career wise, other than to manage more and more people. 

I realized that a lot of my energy and motivation came from proving myself through work and that my validation came in the form of promotions and money. 

I like learning new stuff and challenging myself but there wasn’t anything on the horizon that excited me.  So, in the months before left Microsoft I was faced with a choice: continue on the same track and be paid a lot to work on a huge new project I didn’t honestly love, or finally chase the dream of Silicon Valley I’d been putting aside for a decade.

Second, Seattle weather. ‘Nuff said. 

Third, living in Seattle made it very hard to see our family. Our brother and sister and live in California but we rarely got to see them, and they were starting to have kids of their own. It made us stop and realize just how isolated we were. At one point the trade-offs made sense, but I could see it in my wife’s eyes that being separated from her family by such a distance was weighing on her.

Somewhere in the middle of all this, Reddit contact me about a VP of Engineering opportunity. The timing was good because my manager at Microsoft was asking me to move into a larger role outside of the Power BI organization. I was already thinking about “what’s next?” and open to taking on something new. I suddenly found myself with an opportunity to make a clean break from Microsoft and get down to the Bay Area. So I handed the reins of my organization over to a guy I knew would take great care of it, and my manager found another experienced exec to run his new team.

I had been looking at other jobs in the Bay Area, but Reddit was the first consumer company. What they needed perfectly matched my skillset: building product teams fast. I’m no longer the best coder around, but if you drop me out of a plane handcuffed and blindfolded into the deepest darkest Amazon, I will crawl out of the jungle 3 weeks later with a kick-ass product team and a working MVP.   

The other thing that “de-risked” the decision for me was a conversation with Steve the CEO where he explained just how much traffic Reddit gets on a monthly basis, the general direction he wanted to head with the business model, and how critical communities are to Reddit. Having launched a few products before, it immediately clicked that his vision would work as long as we could move quickly and carefully.

You’ve mentioned before that “you can’t go home again” after life changes so much. How do your parents perceive your career now, after laying such strong foundations for it?

They are astoundingly proud but I’m sure they have no idea what I do. I know they aren’t on Reddit or Power BI users. Whenever I go home my family asks me to help them install Office or debug their machines. But I think that’s true for a lot of people who work as software engineers. 

The other thing it took me a long time to realize, being so focused on my own career, is that my parents never really cared how high I got in the corporate world. When I was at Microsoft, they didn’t understand what a General Manager was, or show any interest in the fact that had come to have a large team with employees around the world.

My mom was a school teacher and my father a public defender. I have yet to meet two people who are more selfless and satisfied with what they have. They only ever really cared that I was doing my best for the people around me. 

Do you ever feel pressure to be a mentor, an example, or a role model for underrepresented folks in tech?

I feel a lot of pressure to be a good person. I’ve had a very fortunate career with an unbroken string of supportive managers and great opportunities. The great thing about being where I’m at career-wise is that I can do pretty much whatever I want now. I don’t need to prove anything to anyone or chase money.

So when I try to mentor, give back, or write a blog, it’s because I actually think it is important to help other people. Tech careers are today’s gold rush, and I want to make sure that women and minorities have access to the opportunity.

If you could do everything all over again, do you think your journey would be the same? Would you want it to be? 

Looking back on my early career I thought of Microsoft was a “safe” job where I could build a career and fortune over time. I equated money with a safety net that would allow me to take on more risks. But now I realize that I always had something even more valuable: time and motivation. When you are early in your career, time itself is a safety net. You can take on risks, try a lot of things, and if it doesn’t work out you can try again. Because I didn’t have this mentality, I passed on great opportunities that would have made the entrepreneur in me happy. 

Second, I am a total workaholic. I put all my energy into building software with little to spare for thinking about kids or family. But eventually I came to understand that tech projects are sandcastles. Even the most beautiful and carefully designed system is meant to be swept away and replaced someday. Looking back, I would have learned to balance work and life more carefully.

Nowadays I work at Reddit where the company culture makes it hard to fall into that trap, and my wife also gives me a back-of-the-hand slap if I’m spending too much time on the keyboard.

"Roy Rogers is terrible but nothing beats the spice of nostalgia.” Is there anything about the internet or technology that you remember from your childhood/early years that gives you the same nostalgic feeling as Roy Rogers?  

I hate to age myself this badly but Usenet, IRC, BBS systems, MUDs. You could be pseudo-anonymous and because of that you could connect with people in ways that weren’t possible in real life. But something got lost along the way from the development of those early systems to modern social networks. It could be the nostalgia speaking but the connections with total strangers I met on BBSs, and even AOL, felt more real to me than most of my Facebook and Twitter “friends.” The early internet was maybe slower paced and harder to get into, but the result was a deeper sense of community.

total strangers I met on BBSs, and even AOL, felt more real to me than most of my Facebook and Twitter “friends.”

Reddit works because of great communities. I think it has the potential to bring back that spirit of the early internet and make it available to everyone on the planet.

How many steps did it take you to become an C++ expert in the end?¹

I will proudly say that I have written software in C++ that is today used by a good fraction of humanity. But I will never say I’m an expert in C++.

Thank you so, so very much to Nick for his time and thoughtful responses to my questions. I originally reached him via the dev/color speaker request form. A lot of this interview was sparked by his piece From “Hello World” to VP Eng, which you should most definitely read. You can also find him on Twitter.

¹ - “My father got me a copy of my first coding book called “Learn C++ in 12 Easy Steps”. Now, this was an absolute god damned lie.” From “Hello World” to VP Engbuild