Coding trends 2026

In the tech world, there is a constant flow of changes and keeping up with them means the choice for tools and technologies which are the most appropriate to invest your time in.

In 2026 the best programming language or technology stack to learn really depends on your personal aims, hobbies, and apps you are going to create.

The use of AI is increasing. AI as a “Pair Programmer” is becoming the default. Code completion, refactoring, and boilerplate generation are used often. Devs spend more time reviewing and steering code than typing it. “Explain this error” and “why is this slow?” prompts are useful.

In prompt-Driven Development programmers describe the intent in natural language and then let AI generate first drafts of functions, APIs, or configs. Iterate by refining prompts rather than rewriting code. Trend: Knowing how to ask is becoming as important as syntax.

Strong growth in: Auto-generated unit and integration tests and edge-case discovery. Trend: “Test-first” is easier when AI writes the boring parts.

AI is moving up the stack. Trend: AI as a junior architect or reviewer, not the final decider.

AI comes to Security & Code Quality Scanning. Rapid adoption in: Static analysis and vulnerability detection, secret leakage and dependency risk checks. AI can give secure-by-default code suggestions. Trend: AI shifts security earlier in the SDLC (“shift left”).

Instead of one-off prompts: AI agents that plan → code → test → fix → retry. Multi-step autonomous tasks (e.g., “add feature X and update docs”) can be done in best cases. Trend: Still supervised, but moving toward semi-autonomous dev loops.

AI is heavily used for explaining large, unfamiliar codebases and translating between languages/frameworks. It helps onboarding new engineers faster.

What’s changing: Less manual boilerplate work
More focus on problem definition, review, and decision-making. There is stronger emphasis on fundamentals, architecture, and domain knowledge. Trend: Devs become editors, designers, and orchestrators.

AI usage policies and audit trails is necessary. Trend: “Use AI, but safely.”

Likely directions:
Deeper IDE + CI/CD integration
AI maintaining legacy systems
Natural-language → production-ready features
AI copilots customized to your codebase

126 Comments

  1. Tomi Engdahl says:

    Building AI agents with the GitHub Copilot SDK
    The GitHub Copilot SDK turns the Copilot CLI into a cross-platform agent host with Model Context Protocol support.
    https://www.infoworld.com/article/4125776/building-ai-agents-with-the-github-copilot-sdk.html

    Reply
  2. Tomi Engdahl says:

    Sudo maintainer, handling utility for more than 30 years, is looking for support
    Many vital open source resources rely on the devotion of a few individuals
    https://www.theregister.com/2026/02/03/sudo_maintainer_asks_for_help/

    Reply
  3. Tomi Engdahl says:

    10 Python One-Liners That Made Developers Stop Scrolling
    Tiny automations that quietly scream “this person knows Python.”
    https://levelup.gitconnected.com/10-python-one-liners-that-made-developers-stop-scrolling-1c0ba66ef7e7

    Reply
  4. Tomi Engdahl says:

    I tried a Claude Code alternative that’s local, open source, and completely free – how it works
    I was curious if Block’s Goose agent, paired with Ollama and the Qwen3-coder model, could really replace Claude Code. Here’s how I got started.
    https://www.zdnet.com/article/claude-code-alternative-free-local-open-source-goose-getting-started/

    Reply
  5. Tomi Engdahl says:

    Are you ready for JavaScript in 2026?
    analysis
    Jan 30, 2026
    4 mins

    Strip the types and hotwire the HTML—and triple check your package security while you are at it. JavaScript in 2026 is just getting started.

    https://www.infoworld.com/article/4123802/are-you-ready-for-javascript-in-2026.html

    Reply
  6. Tomi Engdahl says:

    I Ditched Claude Code and Now Using Open Source Qwen AI for Real Sysadmin Work
    An AI assistant in the terminal can help you guide through the process, help you move faster with your tasks. I tested Qwen Code and share my findings with you.
    https://itsfoss.com/qwen-code-sysadmin-tasks/

    Reply
  7. Tomi Engdahl says:

    Review Prompts for AI-Assisted Code Review
    AI-assisted code review prompts for Linux kernel and systemd development. Works with Claude Code and other AI tools.
    https://github.com/masoncl/review-prompts

    Reply
  8. Tomi Engdahl says:

    obra
    /
    superpowers
    Public
    An agentic skills framework & software development methodology that works.
    https://github.com/obra/superpowers

    Reply
  9. Tomi Engdahl says:

    Which repo would you like to understand?
    https://deepwiki.com/

    Reply
  10. Tomi Engdahl says:

    Microsoft launches LiteBox, a security-focused open-source library OS
    Microsoft has released LiteBox, a project intended to function as a security-focused library OS that can serve as a secure kernel for protecting a guest kernel using virtualization hardware.
    https://www.helpnetsecurity.com/2026/02/05/microsoft-litebox-security-focused-open-source-library-os/

    Reply
  11. Tomi Engdahl says:

    7 open-source apps I’d happily pay for – because they’re that good
    These apps are free, but they’re so good, I’d gladly throw cash at them. Here’s why.
    https://www.zdnet.com/article/free-open-source-apps-worth-paying-for/

    Reply
  12. Tomi Engdahl says:

    Developers say AI coding tools work—and that’s precisely what worries them
    Ars spoke to several software devs about AI and found enthusiasm tempered by unease.
    https://arstechnica.com/ai/2026/01/developers-say-ai-coding-tools-work-and-thats-precisely-what-worries-them/

    Software developers have spent the past two years watching AI coding tools evolve from advanced autocomplete into something that can, in some cases, build entire applications from a text prompt. Tools like Anthropic’s Claude Code and OpenAI’s Codex can now work on software projects for hours at a time, writing code, running tests, and, with human supervision, fixing bugs. OpenAI says it now uses Codex to build Codex itself, and the company recently published technical details about how the tool works under the hood. It has caused many to wonder: Is this just more AI industry hype, or are things actually different this time?

    Reply
  13. Tomi Engdahl says:

    70-vuotias ohjelmointikieli, jota ilman pankit pysähtyisivät – Miksi Cobol ei kuolekaan?
    https://www.tivi.fi/uutiset/a/bd70762b-48b7-40d0-84b0-472413551828

    Moni tärkeä ohjelmisto rakentuu edelleen lähes 70-vuotiaiden kielten varaan. Muutos on kuitenkin vääjäämättä edessä.

    ”Kun valmistuin 1990-luvulla, ensimmäinen asia mitä minulle sanottiin, oli että miksi opiskelit Cobolia, sehän on kuolemassa”, kertoo Arekin it-johtaja Carita Broms-Paulasuo.

    Reply
  14. Tomi Engdahl says:

    Optimizing Python scripts with AI
    One of the first steps we take when we want to optimize software is to look
    at profiling data. Software profilers are tools that try to identify where
    your software spends its time. Though the exact approach can vary, a typical profiler samples your software (steps it at regular intervals) and collects statistics. If your software is routinely stopped in a given function, this function is likely using a lot of time. In turn, it might be where you should put your optimization efforts.
    https://lemire.me/blog/2026/01/25/optimizing-python-scripts-with-ai/

    Reply
  15. Tomi Engdahl says:

    DevOps
    Railway Highlights the Importance of Logs, Metrics, Traces, and Alerts for Diagnosing System Failure
    https://www.infoq.com/news/2026/01/railway-diagnosing-failure/

    Railway’s engineering team published a comprehensive guide to observability, explaining how developers and SRE teams can use logs, metrics, traces, and alerts together to understand and diagnose production system failures. The post, aimed at users of modern distributed systems, lays out practical definitions, strengths, and limitations of each telemetric signal, and emphasizes how combining them enables faster and more accurate root-cause analysis. While the information provided is not unique, it does provide good insight that can help teams understand the observability space a bit more.

    According to the article, observability goes beyond basic monitoring by allowing engineers to explore unknown problems in real time rather than simply reacting to predefined thresholds. Railway outlines four core pillars: logs for detailed event context, metrics for aggregated system health, traces for mapping requests across distributed architectures, and alerts for early warnings against service-level objectives (SLOs). By linking an alert to a metric spike, a trace pinpointing a bottleneck, and logs showing specific errors, teams can rapidly diagnose the full story behind a failure.

    Reply
  16. Tomi Engdahl says:

    The Advanced Claude Code Setup Guide
    You’ve read the basics. Now here’s the configuration layer that separates casual users from teams shipping production code at 3x speed.
    https://blog.devgenius.io/the-advanced-claude-code-setup-guide-358f7b69334d

    Reply
  17. Tomi Engdahl says:

    Local AI is finally boring, and that’s why it’s finally useful
    https://www.xda-developers.com/local-ai-is-finally-boring-and-thats-why-its-finally-useful/

    For the last year or two, local AI has had a bit of a wild west edge to it. In the beginning, it was just about the ability to run a local LLM on your computer and get tangible results out of it. That ability, which you might feel is something reserved for giant corporations, when you first pull it off, feels pretty darn amazing. Download a model of your choice, watch as your computer’s fans spin up, and then get results a few seconds later. However, that was the 2024, even 2025 way of doing things.

    In 2026, local AI is entering its best era yet. It’s getting boring. Boring in the same way as Wi-Fi, your favorite password manager, or even Docker is boring. Boring is dependable, and boring gives you a great platform to build on. Boring is good, and in 2026, AI is less about running any model on your hardware and more about doing something useful with it. And that’s the part that matters most.

    Local AI that slots into your daily use like a tool and that you keep running and build habits around is where local AI becomes ubiquitous. It becomes part of how you research, search, plan, automate, and optimize the more tedious parts of your computer use. And for those who live their lives in a self-hosted world, optimizing for efficiency and performance comes naturally.

    Reply
  18. Tomi Engdahl says:

    Top engineers at Anthropic, OpenAI say AI now writes 100% of their code—with big implications for the future of software development jobs
    https://fortune.com/2026/01/29/100-percent-of-code-at-anthropic-and-openai-is-now-ai-written-boris-cherny-roon/

    Reply
  19. Tomi Engdahl says:

    Cursor Blame
    Cursor Blame is available on the Enterprise plan.

    Cursor Blame extends traditional git blame with AI attribution, showing you exactly what was AI-generated versus human-written in your codebase.

    https://cursor.com/docs/integrations/cursor-blame

    Reply
  20. Tomi Engdahl says:

    When AI ‘builds a browser,’ check the repo before believing the hype
    Autonomous agents may generate millions of lines of code, but shipping software is another matter
    https://www.theregister.com/2026/01/26/cursor_opinion/

    Opinion AI-integrated development environment (IDE) company Cursor recently implied it had built a working web browser almost entirely with its AI agents. I won’t say they lied, but CEO Michael Truell certainly tweeted: “We built a browser with GPT-5.2 in Cursor.”

    He followed up with: “It’s 3M+ lines of code across thousands of files. The rendering engine is from-scratch in Rust with HTML parsing, CSS cascade, layout, text shaping, paint, and a custom JS VM.”

    That sounds impressive, doesn’t it? He also added: “It *kind of* works,” which is not the most ringing endorsement. Still, numerous news sources and social media chatterboxes ran with the news that AI built a web browser in a week.

    Reply
  21. Tomi Engdahl says:

    ‘Ralph Wiggum’ loop prompts Claude to vibe-clone commercial software for $10 an hour
    Developer behind it is sick with worry he might have changed software development in nasty ways
    https://www.theregister.com/2026/01/27/ralph_wiggum_claude_loops/

    Feature Open source developer Geoff Huntley wrote a script that sometimes makes him nauseous. That’s becaues it uses agentic AI and coding assistants to create high-quality software at such tiny cost, he worries it will upend his profession.

    Here’s the script :
    while :; do cat PROMPT.md | claude-code ; done

    Huntley describes the software as “a bash loop that feeds an AI’s output (errors and all) back into itself until it dreams up the correct answer. It is brute force meets persistence.” He calls the code and the technique it enables “Ralph,” a homage to 1980s slang for vomiting, and to Simpsons character Ralph Wiggum and his combination of ignorance, persistence, and optimism.

    The Register put it to Huntley that current human-in-the-loop practices mean developers use AI coding assistants as if playing table tennis: They send a prompt to produce some code over the net, and the LLM bats back some code. He accepted the metaphor, which assumes the developer/bot game continues until the human is satisfied the AI produced something useful, picks up the ball, and goes away to work.

    Huntley’s approach changes the game by telling a coding assistant to attempt to satisfy a developer’s requests, assess whether it did so, then try again until it delivers the desired results. Humans remain in the loop, but enter the software development process later and less often than is the case today.

    The developer has used his approach, and Anthropic’s Claude Code service, to clone commercial products, a job it can achieve if provided with resources including source code, specs, and product documentation.

    Reply
  22. Tomi Engdahl says:

    Windsurf vs. Cursor – which AI coding app is better?
    An honest review of Windsurf
    https://www.thepromptwarrior.com/p/windsurf-vs-cursor-which-ai-coding-app-is-better

    Conclusion
    I think Windsurf is actually the better IDE for beginners.

    If I were to start out coding today, Windsurf would be a great choice. You don’t need to think about context much, and the Windsurf agent will guide you through the code, helping you write everything.

    Cursor by contrast has a bit of a steeper learning curve.

    But if you’re aiming to write production-ready code, e.g. applications that have a working backend, payments integration, and authentication, the more fine-grained control that you get in Cursor will result in higher quality code.

    For professional purposes, I would currently still choose Cursor over Windsurf.

    Reply
  23. Tomi Engdahl says:

    How one developer used Claude to build a memory-safe extension of C
    Robin Rowe talks about coding, programming education, and China in the age of AI
    iconThomas Claburn
    Mon 26 Jan 2026 // 21:30 UTC
    feature TrapC, a memory-safe version of the C programming language, is almost ready for testing.

    “We’re almost there,” Robin Rowe told The Register in a phone interview. “It almost works.”

    We caught up with Rowe, a computer science professor and entrepreneur, amid debugging efforts that had kept him up until four in the morning. The long-awaited TrapC website has appeared.

    https://www.theregister.com/2026/01/26/trapc_claude_c_memory_safe_robin_rowe/

    https://trapc.org/trapc-a-year-later/

    Reply
  24. Tomi Engdahl says:

    Carrd
    Simple, free, fully responsive one-page sites for pretty much anything.
    https://carrd.co/

    Reply
  25. Tomi Engdahl says:

    We got Claude to teach open models how to write CUDA kernels!
    https://huggingface.co/blog/upskill

    Reply
  26. Tomi Engdahl says:

    Daggr Introduced as an Open-Source Python Library for Inspectable AI Workflows
    https://www.infoq.com/news/2026/02/daggr-open-source/

    Reply
  27. Tomi Engdahl says:

    How to maximize GitHub Copilot’s agentic capabilities
    A senior engineer’s guide to architecting and extending Copilot’s real-world applications.
    https://github.blog/ai-and-ml/github-copilot/how-to-maximize-github-copilots-agentic-capabilities/

    Reply
  28. Tomi Engdahl says:

    Introducing the Codex app. OpenAI just released a new macOS app for their Codex coding agent. I’ve had a few days of preview access – it’s a solid app that provides a nice UI over the capabilities of the Codex CLI agent and adds some interesting new features, most notably first-class support for Skills, and Automations for running scheduled tasks.
    https://simonwillison.net/2026/Feb/2/introducing-the-codex-app/

    Reply
  29. Tomi Engdahl says:

    CPython vs. PyPy: Which Python runtime has the better JIT?
    feature
    Jan 28, 2026
    9 mins

    https://www.infoworld.com/article/4117428/which-python-runtime-does-jit-better-cpython-or-pypy.html

    How does CPython’s new native-JIT compiler stack up against PyPy? We ran side-by-side benchmarks to find out, and the answers may surprise you.

    Reply
  30. Tomi Engdahl says:

    https://www.xda-developers.com/open-source-image-editor-does-90-percent-what-photoshop-does/

    Even though I’ve already built a pretty solid open-source graphics stack at this point, I’m always on the lookout for new tools or hidden gems. That’s exactly how I discovered some of my favorites, like Photopea and PhotoDemon. Recently, I came across a tool called miniPaint. It’s a free, open-source, lightweight image and graphics editor that runs in your browser, and it’s self-hostable too.

    Reply

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