AI Coding Agents
Claude Code, Cursor, Codex, and the operating habits that make agentic coding useful in real repositories.
Deep dives into AI agents, coding tools, and building with LLMs.
Reading Paths
Start with the strongest evergreen pieces, then branch into the weekly notes, guides, and comparisons around the same problem.
Claude Code, Cursor, Codex, and the operating habits that make agentic coding useful in real repositories.
How to choose between orchestration frameworks, UI copilots, stateful agents, and production app patterns.
The practical layer for giving agents access to tools, files, services, and repeatable developer workflows.
Permissions, prompt injection, tool access, audit logs, and rollback patterns for agents that can touch real systems.
Model routing, AI SDKs, deploy platforms, and the infrastructure decisions behind reliable AI products.
How the site, app directory, public APIs, and content loops are built, wired, and improved in public.
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Most developers only know .gitignore, but Git offers two other ignore mechanisms for local workflows and machine-wide patterns. Here's when to use each.
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GitHub's Agent Finder discovers and invokes Claude, Codex, MCP servers, and skills automatically. Here is how the new ARD specification changes AI coding tool integration.

MCP's new enterprise-managed authorization flow is not just less login friction. It moves agent tool access into identity, policy, and audit systems enterprises already understand.

Java's most anticipated performance feature is finally landing. Value classes eliminate object identity overhead and enable dense memory layouts - here's what changes.

A YC W25 startup open-sources CADAM, a browser-based tool that converts natural language to parametric OpenSCAD models. HN debate: is text-to-CAD genuinely useful or just another demo?

Auto-installing tree-sitter grammars, built-in markdown mode, window layout commands, and more - the upcoming Emacs release absorbs features that used to require external packages.

Alex Ellis shares real production experience running local LLMs: $12k hardware investment, 2-3 month ROI, and why treating local models as Opus substitutes misses the point entirely.

JetBrains released Mellum2 on June 2, 2026 - a 12B MoE model with only 2.5B active parameters per token. Here is how to run it locally, when to use it, and where it fits in your AI coding stack.

Midjourney, the company that makes AI pictures, just announced a full-body ultrasonic scanner and a spa chain to put it in. It sounds like a non sequitur. It is not. Here is what was actually announced, why a generative-image lab is suddenly building medical hardware, and the sharpest skeptic and believer takes from Hacker News on whether any of it survives contact with the FDA.

The Transformer co-creator leaves Google DeepMind for OpenAI just two years after Google paid $2.7 billion to bring him back from Character.AI.

A $500M accidental Claude bill and an open-weights model beating GPT-5.5 at one-sixth the cost point to the same conclusion: the margin is moving to the layer that decides when to use which model for what. Here is how routing and orchestration differ, and how to cut your model spend.

A hands-on, beginner-friendly walkthrough of building an AI agent with Vercel eve: scaffold the project, define an agent and a typed tool with defineTool, run it locally, call it through the durable session and stream API, and deploy to Vercel Functions.
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