Gemini 4 Carbon: what it is and why you can't use it yet
Gemini 4 Carbon is Google's strongest security model, but only selected teams can use it. What it does, why it launched closed, and what to use today.
· 6 min
AI
25 articles
GitHub Octoverse 2026: 40% of pull requests now start with an agent
GitHub's Octoverse 2026 shows 40% of pull requests now start with an AI agent. The key numbers, and what the teams where it works do differently.
· 6 min
Six tasks I hand to AI, and three I don't
Tests, legacy code, debugging, review, refactoring and SQL: what I ask the AI for in each, what I watch for, and how I check it in minutes. And the three decisions I never hand off, with a real case from this month that shows why.
· 9 min
What makes a developer valuable today: what the data and this month's debate say
Developer job postings are rising again, but not for everyone, and interviews are dropping algorithm puzzles. What October's data shows, what was debated this week, and six skills you can start practicing tomorrow.
· 7 min
Claude ported the TypeScript compiler to Rust without anyone reading the code: why it worked
A developer let Claude Opus 5.5 translate the TypeScript compiler to Rust for two weeks. It passes all 184,749 tests and he says he never read a line. What happened, what's overhyped, and how to use the same structure for a migration in your own project.
· 7 min
Coding agents add 30% more code, but not more shipped work
A Harvard study of 718 companies measured what happens when a team adopts coding agents: people write 30% more code, but no more work gets finished. The time is lost in code review. What the data says and what you can do before you send a change.
· 8 min
Jev: the AI model that decides instead of writing
TypeSafe launched Jev, an AI model that doesn't generate text: it answers closed questions about a piece of text in a tenth of a second, for a fraction of the price. What it is, how to use it, where it fails, and how to try it.
· 10 min
How to manage context when coding with AI
What a language model's context is, why it fills up without you noticing, and four simple habits so the agent doesn't forget what you asked. Nothing to set up: it works from your next conversation.
· 7 min
Opus 5.5: what changes if you code with an AI agent
Anthropic released Claude Opus 5.5: cheaper, faster, and with three new restrictions. What it does to the bill for a real session, when fast mode is worth it, who it breaks things for, and how to test it on your repo.
· 8 min
How to write a spec an agent will not misread
The anatomy of a specification, the five EARS templates for writing requirements with no gaps, and why plan mode is the cheapest way to start. The practical side of working with specifications.
· 13 min
Spec-driven development: what it solves, what it costs, when to use it
The specification as the source of truth and code as a derived artifact. How the workflow actually looks, the real problem it attacks, the three traps teams hit with it in production, and the size of change where it stops paying off.
· 10 min
Choosing a coding agent is no longer choosing a model
Claude Code, Codex, Copilot and Cursor now run the same frontier models and cost roughly the same. What separates them is the harness: how much you supervise, how much you delegate, and where it runs. How to choose by the work.
· 7 min
Your repo is not ready for an AI agent
Why the agent hands you code it never verified, and the six things about the repository to fix so it can check its own work. None of them is a rewrite and none takes more than an afternoon.
· 8 min
Migrating a legacy app to a modern stack today
What changes when the migration of a Web Forms app —or any other legacy— to a modern stack is done with a coding agent: the seven steps I would not skip, the most expensive mistakes, and how to avoid ending up with a new legacy written in a newer language.
· 7 min
Claude Code best practices, to move fast without losing quality
Coding fast with an agent and coding well aren't the same thing, but they're not contradictory either. The habits and tools — CLAUDE.md, plan mode, subagents, hooks — that keep code scalable and clean, even when Claude wrote it.
· 11 min
Claude Skills, from the basics to building your own
A Skill is a folder with instructions that Claude reads on its own when it's needed, without taking up context until then. How to use the ones that already exist, how to build your own step by step, and what to check before installing someone else's.
· 8 min
Archify: the skill for verified architecture diagrams in Claude Code or Codex
Archify is a free skill for Claude Code, Codex, Cursor, and opencode that draws verified architecture diagrams instead of invented ones: it splits writing a typed description of the system, validating it, and only then drawing it.
· 11 min
Headroom compresses what your AI agent reads, before it reaches the model
A coding agent can burn half its tokens on a log or a JSON blob that never needed to be sent whole. Headroom is a free tool that compresses that before it reaches the model, without changing the answer, and without sending your code anywhere to do it.
· 8 min
You use four Claude Code commands. Ten are missing
Ten commands that solve the same four problems you already have: the context that fills up, the setup you never did, the change that has to be undone, and the work that does not fit in one turn.
· 8 min
Three tools you need to know exist for coding with Claude
Three free tools you need to know exist. One imposes a way of working before any code gets written. Another shows you where your tokens go. The third gives it design judgement. What each one does, how to install them, and what they cost you.
· 7 min
How to review code an AI wrote
It compiles, it passes the tests and it looks tidy. That does not mean it is right. Six concrete things worth checking, in the order the real problems show up.
· 5 min
MCP: the protocol that connects an AI assistant to your data
Your assistant answers general questions well but knows nothing about your database. Giving it access means writing an ordinary program. What MCP is, how to write one, and the three security mistakes that keep repeating.
· 8 min
AI-generated SQL: why it fails silently
In almost every language, incorrect code breaks and tells you. An incorrect SQL query runs, returns rows and nobody finds out. What to check before accepting one, and what changed in the databases themselves.
· 7 min
Coding with AI without overspending
What you actually pay for when using a language model to write code, why the bill almost never comes from the model you picked, and the practices that cut spending most without lowering the quality of the result.
· 7 min
Twenty-four years of .NET, version by version
From a platform that only ran on Windows to a cross-platform one with artificial intelligence support in its base library. The complete path, and the decision that defined each stage.
· 8 min