#software development with AI

[pauljonessoftware]

My AI Pair Programmer Works as Hard as I Do

How I Rediscovered My Love for Building With Help From an Invisible Teammate When I first started programming, it was exciting—creative, even intoxicating. I came from a background in electronics engineering, and code felt like this unlimited sandbox where I could invent anything. I dove in enthusiastically, thinking I’d found the perfect side hustle or creative outlet. But then something…

[infosprint]

Stop Writing Code! AI Code Assistants & No-Code Are The Future

Is AI taking the future of software development with its code and no-code? More than 50% non-experts are already using AI-driven coding and no-code platforms - often without being familiar with it. Platforms like WordPress, Wix, and Mailchimp utilize no-code or low-code development to create templates, emails, websites, and more. This technology is popular for its ease of use, which doesn’t require coding expertise, and its fast deployment, among other benefits.

According to a Gartner survey, Over 70% of new applications were built using this technology. This shift is not just for beginners—even experienced developers are embracing AI-powered code assistants to enhance productivity and efficiency.

The software industry is going through a significant shift, one that could redefine how applications are built. Infosprint Technologies is a software company leading the digital transformation with AI technology to enhance productivity and efficiency. Explore the software transformation and what the future holds for this technological evolution.

Demystifying AI Code Assistants: What You Need to Know

AI code assistants are tools designed to assist software developers in writing, debugging, and optimizing their code. These platforms utilize artificial intelligence (AI) and machine learning (ML) to analyze vast open-source code and programming documentation sets. This enables them to provide intelligent suggestions, ultimately enhancing the efficiency of the software development process.

AI-code Assistants: The Key Features

Code autocompletion: AI codes help developers by suggesting complete or missing lines in a code, reducing manual efforts.

Bug detection and fixes: This helps fix any errors and bugs and suggests an alternate code that will enhance and improve the deployment time of the application.

Code refactoring: Helps improve code structure and readability while maintaining functionality.

Code translation: involves converting code from one programming language to another.

Security Analysis: Detects vulnerabilities and suggests security best practices.

Integration with IDEs: Works seamlessly within development environments like VS Code, JetBrains, and GitHub.

A recent GitHub report found that developers using AI assistants like Copilot completed coding tasks 55% faster than those who didn't.

No-Code is Here: Why You Should Pay Attention

No-code development is a method for creating applications without writing any code. Unlike traditional coding, no-code development uses programs that let users drag and drop objects. This approach includes pre-built integrations and automation tools, making app development accessible to non-technical users. The popularity of this technology is growing because:

1. Demarcation of development

This technology removes technical barriers between software developers, non-developers, marketers, and business owners.

Reduces the dependency on developers, making business agile.

2. Cost-Effective:

Lower development costs by eliminating the need to hire expensive developers.

It doesn't require technical skills to maintain infrastructure and updates.

This technology is optimal for startups that need to launch quickly with limited budgets.

3. Rapid prototyping:

Reduces the time to market for new products.

Developers can test MVP(minimal viable products) without worrying about budgetary constraints.

4. Enhanced collaboration:

Business and IT teams can work together without a technical bottleneck.

Marketing, operations, and sales teams can create internal tools without waiting for developer support.

Encourages a more agile development process.

Popular No-code platforms

Bubble: An illustration program that allows users to build dynamic web apps.

Webflow: A no-code website builder with advanced design customization to design responsive websites.

Zaiper: Connect different apps to create automated workflows without coding.

What's Next in Software Development?

AI assistance has evolved rapidly from merely suggesting incomplete code to analyzing, modifying, and debugging current code. These advancements are changing how we develop software, what we create, and the very nature of the developer's role.Adopting these adjustments will be critical for success in the years ahead.

1. AI-First Development

Artificial Intelligence can analyze business needs and suggest optimal architecture, frameworks, and programming languages based on the project scope. This helps developers save time for manual research and planning.

AI-powered tools can analyze user behavior trends and suggest design improvements for better engagement, thus leading to higher-quality products with improved user experience.

Organizations have improved software quality with fewer defects as AI can enforce best coding practices, reducing errors and improving maintainability.

Before applications research the market, AI uses simulations with real-world scenarios to predict potential system failures before deployment.

2. Expansion of no-code in enterprise

No-code technology reduces development, infrastructure, and maintenance expenses through pre-built integrations. This technology is being adopted faster by startups and small business owners to minimize development costs and accelerate time-to-market deployment. According to a recent survey, around 70% of new applications are built by no-code technology.

No-code platforms use drag-and-drop interfaces and pre-built components, significantly reducing development time compared to custom coding.

Organizations can rapidly prototype, test, and deploy applications without long deployment cycles. They can automate workflows and streamline operations without waiting for IT backlogs.

With the increasing need for software developers, organizations are struggling to find the right developer. Still, with no-code technology, one can use this technology to build software without requiring high technical skills.

3. Hybrid Workflows: AI + No-Code – The Future of Scalable and Flexible Innovation

As businesses adopt no-code development, they leverage AI-powered code assistants to create hybrid workflows that enhance efficiency, scalability, and innovation. This approach enables enterprises to enjoy the ease of no-code creation while also benefiting from AI-driven automation, informed decision-making, and advanced features.

AI-powered automation can efficiently manage data processing, predictive analytics, and intelligent decision-making in no-code applications.

Platforms using No-code technology offer defined functionalities, while AI-driven code assistants like GitHub Copilot and OpenAI Codex can generate custom scripts when needed.

Artificial intelligence can enhance business workflows by analyzing patterns and recommending improvements for automation.

No-code tools enable quick development, while AI offers scalability by managing big data, making predictions, and facilitating dynamic decision-making.

4. Beyond Coders: The Expanding World of Software Development

No-code development has given rise to a new profession: citizen developers. These individuals are business professionals who can build applications using intuitive business platforms despite lacking traditional coding knowledge. This shift democratizes software development, making innovation across various industries more accessible.

Faster innovation and agility through no-code development. Build faster prototypes, reduce IT bottlenecks, and accelerate digital transformation.

Save money by utilizing pre-built integrations of the no-code platform, reducing custom development efforts.

Bridge the IT gap by empowering non-technical teams to build applications so software teams can focus on more technical challenges rather than routine business.

5. Ethical & Security Considerations in AI & No-Code Development

No-code technology is increasingly adopted across organizations, and as they embrace AI and ML, organizations must address the critical ethical and security challenges to ensure responsible adoption.

Modern no-code platforms include built-in security and compliance features, ensuring safe development without requiring technical expertise.

Organizations can establish centralized governance policies to promote the responsible use of technology.

AI-driven no-code platforms now include bias detection algorithms, which help ensure fairness in automation.

No-code platforms have built-in enterprise-grade security, enabling organizations to innovate without facing security-related obstacles.

Clear and transparent AI decision-making, along with responsible automation frameworks, helps build trust and ensures long-term success.

The Impact on Professional Developers: How AI & No-Code Enhance Development

One might wonder : Will no-code technology replace professional developers? No, rather than replacing them, these technologies serve as powerful augmenters. By using this technology, developers are experiencing better efficiency, code quality, and reduced development bottlenecks.

AI-driven code assistance suggests codes based on best practices reducing time spent on writing repetitive logic.

Its detection capabilities identify common programming errors and enforce industry best practices, making the codebase more scalable and maintainable.

AI enhances developers' creativity, problem-solving, and decision-making skills allowing them to automate repetitive tasks, focus on high-level architecture and system design, and continuously learn and improve coding techniques.

AI-powered tools are especially useful for handling intricate software challenges such as refactoring large codebases and generating boilerplate code. This will help developers spend less time understanding the whole codebase.

More Accessible, Faster, and Cost-Effective: The Future of Software is Here

The future of software development is changing quickly. AI code assistants improve traditional coding efficiency, while no-code platforms democratize development by allowing anybody to create applications. The confluence of these technologies is ushering in a new era in which software creation is more accessible, faster, and cost-effective.

While traditional coding will never become outdated, the way we create code is fundamentally changing. Whether you are a developer or a business professional, adopting AI-powered development and no-code solutions can help you stay ahead of the digital transition.

[primathontechnology]

Best Custom Software Development Service Company

Get custom software development from Primathon. We help our customers to transform their products and improve processes to design and develop profitable software faster.

[sreegs]

the past few years, every software developer that has extensive experience, and knows what they're talking about, has had pretty much the same opinion on LLM code assistants: they're OK for some tasks but generally shit. Having something that automates code writing is not new. Codegen before AI were scripts that generated code that you have to write for a task, but is so repetitive it's a genuine time saver to have a script do it.

this is largely the best that LLMs can do with code, but they're still not as good as a simple script because of the inherently unreliable nature of LLMs being a big honkin statistical model and not a purpose-built machine.

none of the senior devs that say this are out there shouting on the rooftops that LLMs are evil and they're going to replace us. because we've been through this concept so many times over many years. Automation does not eliminate coding jobs, it saves time to focus on other work.

the one thing I wish senior devs would warn newbies is that you should not rely on LLMs for anything substantial. you should definitely not use it as a learning tool. it will hinder you in the long run because you don't practice the eternally useful skill of "reading things and experimenting until you figure it out". You will never stop reading things and experimenting until you figure it out. Senior devs may have more institutional knowledge and better instincts but they still encounter things that are new to them and they trip through it like a newbie would. this is called "practice" and you need it to learn things

[aeolianblues]

I don't like that the dev community picks on people who are most fluent in Python, when the ChatGPT-using "vibe coders" are right there. At least Python babies are coding. Bully the non-coders instead.

[nixcraft]

Imagine being this stupid to drink Kool-Aid and giving a remote LLM tool full access to your codebase, and, in many cases, not maintaining backups or using proper Git with permissions. How these guys are getting hired to write code is beyond me.

[cyle]

I know you're on paternity leave so feel free to ignore this if you don't want to think about it, but has there been any progress on open-sourcing Tumblr's front-end? Inquiring minds would like to know

i hadn’t seen any progress on it before i left. there’s a strong willingness to do it, it’s just a big task to get it open-source-able in a sustainable way. a lot of our CI/CD processes rely on stuff that would need to be rebuilt from scratch, i think. totally doable, just not a priority.

but maybe there’s been progress since i left, i dunno! 🤞

[moose-mousse]

Remember

When you write utility tools that are not specific to your workplace enviroment and you might want to use them at the next place you work.

Then make sure there is no way to prove that your code was made at your work.

Don't check it into a remote git ( just write git init and do it locally). Don't let Onedrive see it.

And then just move it back and fourth to update versions with a flash drive.

Remember.

It is not just ok to steal from your workplace, it is the ethical choice.

Think of it as "wealth distribution towards equality"

Or "Eat the rich"

Or "copyright is only a thing for your corperate masters. Your copyright is called "you are training data""

[frank-olivier]

The story of BASIC’s development began in 1963, when Kemeny and Kurtz, both mathematics professors at Dartmouth, recognized the need for a programming language that could be used by non-technical students. At the time, most programming languages were complex and required a strong background in mathematics and computer science. Kemeny and Kurtz wanted to create a language that would allow students from all disciplines to use computers, regardless of their technical expertise.

The development of BASIC was a collaborative effort between Kemeny, Kurtz, and a team of students, including Mary Kenneth Keller, John McGeachie, and others. The team worked tirelessly to design a language that was easy to learn and use, with a syntax that was simple and intuitive. They drew inspiration from existing programming languages, such as ALGOL and FORTRAN, but also introduced many innovative features that would become hallmarks of the BASIC language.

One of the key innovations of BASIC was its use of simple, English-like commands. Unlike other programming languages, which required users to learn complex syntax and notation, BASIC used commands such as “PRINT” and “INPUT” that were easy to understand and remember. This made it possible for non-technical users to write programs and interact with the computer, without needing to have a deep understanding of computer science.

BASIC was first implemented on the Dartmouth Time-Sharing System, a pioneering computer system that allowed multiple users to interact with the computer simultaneously. The Time-Sharing System was a major innovation in itself, as it allowed users to share the computer’s resources and work on their own projects independently. With BASIC, users could write programs, run simulations, and analyze data, all from the comfort of their own terminals.

The impact of BASIC was immediate and profound. The language quickly gained popularity, not just at Dartmouth, but also at other universities and institutions around the world. It became the language of choice for many introductory programming courses, and its simplicity and ease of use made it an ideal language for beginners. As the personal computer revolution took hold in the 1970s and 1980s, BASIC became the language of choice for many hobbyists and enthusiasts, who used it to write games, utilities, and other applications.

Today, BASIC remains a popular language, with many variants and implementations available. While it may not be as widely used as it once was, its influence can still be seen in many modern programming languages, including Visual Basic, Python, and JavaScript. The development of BASIC was a major milestone in the history of computer science, as it democratized computing and made it accessible to a wider range of people.

The Birth of BASIC (Dartmouth College, August 2014)

Friday, April 25, 2025

[aaliya-b]

The Rise of AI-Powered SaaS Products in Indian Tech

India's SaaS ecosystem is evolving fast, and AI is now at its core. From customer service to HR to sales, AI-enabled software is automating tasks that once needed full teams.

Ultimez Technology has developed a modular AI product for digital teams—helping clients monitor, analyze, and optimize customer engagement.

Freshworks, headquartered in Chennai, is now globally known for its AI-powered customer support tools. Likewise, Zuper, a SaaS player from Bangalore, uses AI for field workforce optimization.

"SaaS + AI is the new startup formula in India" 

This shift positions Indian SaaS companies as global players, offering affordable, scalable, and intelligent platforms.

[reva1231]

Spring Boot Development for Modern Software Development Platforms enables rapid, scalable, and production-ready application creation using minimal configuration. It streamlines enterprise-grade backend development, making it ideal for microservices and cloud-native architectures.

[mentalisttraceur-software]

DeepSeek R1 First Impressions

DeepSeek R1 is almost as good as me at belabored exhaustive analysis and application of C89 rules. For practical purposes, it's equally good.

I asked: "How would you implement zig-zag encoding in strictly portable C89?" It was spitting out thinking output for at least a minute, but it got a basically-perfect solution on first try:

unsigned int zigzag_encode(int n) { return (((unsigned int)n << 1) ^ ((n < 0) ? -1 : 0); }

It also provided a `zigzag_encode_long`.

Note that this code will optimize on modern C compilers to the best assembly you could write. There is no branch in the produced code with even just `-O1` (`clang`, `gcc`), the branch is how we portably tell the compiler the right idea.

The only thing DeepSeek did "wrong" vs the above, was redundantly add an `(unsigned int)` cast to the `-1`. I mentioned this as I would to a person: that the usual arithmetic conversions would take care of it at the `^`. It reasoned the rest on its own: yes, because the left operand is already at least an unsigned int, so integer promotion will make the left side an unsigned int as well.

We talked at length about how we can prove that the above is portable to the most pathological C89-conformant implementations. It kept taking longer to "think", but it didn't show any weakness until the very last question.

I asked it to help me rigorously prove if the maximum value of unsigned integers is required by the C standard to be a Mersenne number (2^n-1). To have all bits one, that is.

What if an implementation just decided to arbitrarily not use one or more of the top values? I.e., why not `#define UINT_MAX 0xFFFFFFFE`?

DeepSeek R1 didn't seem to conceive of this possibility until I made it explicit. (But it did a great job of ruling out all others.)

Finally, it gave a longer, non-trivial argument, which I don't find convincing. Basically, it seemed to be saying that since integers used "pure binary representation", and every value bit could be either one or zero, well then the maximum value always has all value bits one - in other words, it seemingly assumed that just because each value bit individually was allowed to be one or zero, the possibility of them all being one at once must be both legal and used to represent a distinct value.

I see a shorter argument, which follows directly from what the standard does say: C89 has two definitions of `~`:

flip all the bits;

subtract from maximum value of that unsigned integer type.

The only way both can be true at once is if the maximum value is all value bits one. DeepSeek R1 agreed.

So what does this all mean?

This is an insane level of competence in an extremely niche field. Less than a year ago I tested LLAMA on this, and LLAMA and I didn't even get past me hand-holding it through several portability caveats. DeepSeek R1 and I just had a full-blown conversation that most devs I've talked to couldn't have with me. DeepSeek R1 managed to help me think in an extremely niche area where I'm basically a world-class expert (since the area in question is C89 portability, "world-class expert" is derogatory, but still).

If it's this good in one domain, it's this good in most domains. I bet it can do comparably well in Python, Go, JavaScript, C++, and so on.

In other words, it's already better than many devs in areas like this. I've seen plenty of devs making 6-figure USD salaries who didn't bother to know any of their day job tech stack this deeply. There's a market adjustment coming. Knowledge and expertise are about to become dirt-cheap commodities.

AI will eat current software dev jobs even faster than even I thought - and I already thought it would be sooner than most expect. Meanwhile, much of the industry is busy rationalizing from human intuition and ignorance that it just can't happen.

For years I've thought that the future is human devs delegating to teams of AI. That future is almost upon us, and this AI is good enough that I will be seriously experimenting with making that future a reality. I think if you hack together the right script to hook it up to a sandbox with dev tools, and prompt it just right... you might already be able to get this thing to actually do useful dev work.

[atcuality3]

Simplify Decentralized Payments with a Unified Cash Collection Application

In a world where financial accountability is non-negotiable, Atcuality provides tools that ensure your field collections are as reliable as your core banking or ERP systems. Designed for enterprises that operate across multiple regions or teams, our cash collection application empowers agents to accept, log, and report payments using just their mobile devices. With support for QR-based transactions, offline syncing, and instant reconciliation, it bridges the gap between field activities and central operations. Managers can monitor performance in real-time, automate reporting, and minimize fraud risks with tamper-proof digital records. Industries ranging from insurance to public sector utilities trust Atcuality to improve revenue assurance and accelerate their collection cycles. With API integrations, role-based access, and custom dashboards, our application becomes the single source of truth for your field finance workflows.

[magebird]

Sometimes I feel like the discourse about AI art misses the actual point of why it’s not a good tool to use.

“AI art isn’t ‘real’ art.” —> opinion-based, echoes the same false commentary about digital art in general, just ends up in a ‘if you can’t make your own store-bought is fine’ conversation, implies that if art isn’t done a certain way it lacks some moral/ethical value, relies on the emotional component of what art is considered “real” or not which is wildly subjective

“AI art steals from existing artists without credit.” —> fact-based, highlights the actual damage of the tool, isn’t relying on an emotional plea, can actually lead to legally stopping overuse of AI tools and/or the development of AI tools that don’t have this problem, doesn’t get bogged down in the ‘but what if they caaaaan’t make art some other way’ argument

Like I get that people who don’t give a shit about plagiarism aren’t going to be swayed, but they weren’t going to be swayed by the first argument either. And the argument of “oh well AI art can’t do hands/isn’t as good/can’t do this thing I have decided indicates True Human Creativity” will eventually erode since… the AI tools are getting better and will be able to emulate that in time. It just gets me annoyed when the argument is trying to base itself on “oh this isn’t GOOD art” when AI does produce interesting and appealing images and the argument worth having is much more about the intrinsic value of artists than the perceived value of the works that are produced.

[learn-ai-free]

How to Build Custom AI Agents in Minutes Using Chai (Vibe Code)

Most business teams are still struggling to push the idea of an AI agent from the whiteboard to production—Why? The majority of professionals are non-technical and do not have a deep understanding of what goes on behind the scenes.

What is Chai by Langbase? 📌

Chai by Langbase is a prompt‑first service that builds, deploys, and scales AI agents straight from plain English. In much simpler terms, Chai can build AI agents for you. Users can vibe code production-ready AI agents within minutes after entering the prompt/ agent idea.

What sets Chai apart? 📌

Langbase describes Chai with three simple verbs—"Prompt. Sip. Ship," which literally means enter a prompt for your agent, sip chai tea while it vibe codes the agent for you, and ship it to your clients.

How to Build Custom AI Agents in Minutes Using Chai (Vibe Code) 📌

Step 1️⃣: Visit Chai.new.

Step 2️⃣: Enter a prompt for the AI agent.

Step 3️⃣: Chai will start by thinking and creating an overview of the AI agent.

Step 4️⃣: Deploy the AI agent.

↗️ Full Read: https://aiagent.marktechpost.com/post/how-to-build-custom-ai-agents-in-minutes-using-chai-vibe-code