AI in 2026: Agents, Coding Tools, and the Changing Software Landscape

Sun, 15 Mar 2026 00:00:00 +0000

Since around November 2025, the pace of AI development has been absolutely relentless.

Retrieval-Augmented Generation (RAG) systems are evolving quickly. A few months ago the conversation was dominated by Model Context Protocols (MCPs). But after recent announcements from Perplexity AI and others, it seems AI tooling is moving closer to CLIs and APIs, integrating directly into developer workflows rather than relying heavily on new middleware layers.

Interestingly, I remember teaching in one of my modules a few years ago that Command Line Interfaces (CLIs) are among the most powerful interfaces ever created. Old really is gold. It is nice to see them getting the love again as AI tooling shifts toward developer-centric workflows. Hopefully accessibility will continue to improve so that CLI-centric tools become usable by an even wider audience.

We are also seeing consolidation around the AI agent ecosystem.

For example:

Clawdbot being acquired by OpenAI
Moltbook being acquired by Meta Platforms

These moves look largely like acqui-hire plays, but they signal something bigger: AI agents are quickly becoming one of the defining themes of 2026.

The investment momentum is equally remarkable. Replit has reportedly raised funding at around a $9 billion valuation, highlighting just how central AI-assisted development tools are becoming.

Meanwhile, renowned AI researcher Yann LeCun has been raising funding for a new venture focused on JEPA (Joint Embedding Predictive Architecture) world models, reportedly setting records with one of the largest seed rounds ever raised in Europe. This suggests growing belief that the next wave of AI may be driven by world-model approaches, not just large language models.

On the development side, tools such as Replit, OpenAI Codex, Qwen Coder, and Claude Code have made enormous progress in AI-assisted programming. Software engineers are increasingly reviewing, guiding, and orchestrating code rather than writing every line manually.

This shift is already influencing the industry. Reports of restructuring, including layoffs linked to automation initiatives at startups connected to Jack Dorsey, suggest companies are beginning to reorganise around AI-first development workflows.

Of course, there are trade-offs. As AI coding agents become more prevalent, we will likely hear more stories about failures and outages caused by automated code generation. For example, earlier this year an Amazon service outage sparked speculation that an internal agentic coding system might have been involved (something Amazon later denied publicly). Regardless of the specific cause, these incidents highlight the new risks that come with increasingly automated software pipelines.

What I am seeing in the Islamic tech ecosystem

From my vantage point working in Islamic software, something interesting is happening.

We are seeing many highly niche apps emerging almost daily. As development becomes dramatically cheaper and faster, building a small app or experimental product can now take hours instead of weekends for a developer.

This is exciting.

Lower barriers to entry mean more innovation and experimentation. But it also means many apps will struggle to survive.

AI-based products are expensive to run (inference costs, infrastructure, data pipelines). Without enough users or a clear revenue model, many projects will inevitably disappear.

So the old questions still matter:

Are we solving a real user need or pain point?
Is there a large enough user base to sustain the product?

As an academic and founder

As someone teaching AI and Software Engineering, I increasingly find myself going back to foundational concepts in the classroom.

The tooling landscape may change every few months, but the fundamentals, algorithms, systems thinking, evaluation, and user-centred design, remain stable.

As a co-founder building technology products, I am also watching closely to see which new entrants gain traction and which ones fade away.

The next few years will likely reshape how software is built.

It will be fascinating to watch.

On a personal note, as we enter the final days of Ramadan, I pray that everyone’s fasting and worship are accepted.

Advance Eid Mubarak.

Please keep me, my family, our team, and the wider Ummah in your prayers.

Teaching Software Engineering in the Age of AI Coding Agents

Sun, 15 Feb 2026 00:00:00 +0000

Last weekend I built, shipped, and pushed a reasonably complex piece of software to production.

Several thousand lines of code. Live. Working.

Time spent: a weekend.

This would have been unthinkable not long ago.

With the rise of genuinely capable coding agents, Replit, Qwen Coder, Claude Code, OpenAI Codex, and their tight integration into tools like Cursor and VS Code, the act of writing code has become faster, cheaper, and increasingly commoditised.

And that has important implications for us as academics.

If software development itself is becoming easier, then our value in teaching cannot sit primarily at the level of syntax, APIs, or boilerplate implementation anymore. What matters far more is:

Teaching how software actually works at a conceptual level
How to design sound software architectures
How to think about security, safety, and robustness by design
How to build accessible, usable, and well-designed interfaces
How to reason about trade-offs, constraints, and failure modes
How to deploy responsibly in real-world environments

Even areas like cloud deployment and DevOps, once specialist skills, are now remarkably straightforward with the right tooling. The barrier has shifted.

This semester, I will be teaching a software engineering module, and I am actively thinking about how to integrate these principles into the curriculum, not by fighting AI-assisted development, but by designing learning around it.

Our responsibility, I think, is to prepare students not just to code, but to become AI-augmented software engineers who can design systems that are safe, secure, ethical, accessible, and genuinely useful to people.

The tools have changed.

The fundamentals, good thinking, good design, and good judgement, matter more than ever.

I am curious how others are adapting their teaching in this new landscape.

Software Engineering | Dr Riasat Islam

AI in 2026: Agents, Coding Tools, and the Changing Software Landscape

What I am seeing in the Islamic tech ecosystem

As an academic and founder

Teaching Software Engineering in the Age of AI Coding Agents