#developer-tools

What Cursor, Claude Code, and Perplexity actually built -- and why the model was never the real product.

Anthropic just shipped the first major feature that security researchers spotted weeks ago in its accidentally exposed source code. And it turns out the leaked description wasn't hype.

A senior AMD AI director's logs point to sharp regression in Claude's coding performance -- Anthropic says it's a product change, not a dumber model.

AI can write the code. The problem is the person approving it -- working with an atrophying skill set, a backlog that doubles every quarter, and a mounting suspicion they can't tell if what they're merging is safe.

This open-source Claude Code plugin generates living architecture diagrams committed to git, drillable, and kept fresh by AI.

A background agent that runs silently after every Claude Code response, building and surfacing context across sessions without adding latency to your workflow.

Context Hub, Code Review Graph, and the emerging discipline of giving AI agents less to make them smarter.

AI coding agents are blind — they read files but don't see structure. A 16K-star open-source project is changing that by building knowledge graphs that make agents actually understand codebases.

One plugin scans a desktop app's source code and generates a complete command-line interface for it, so AI agents can use software that was built for humans.

There's a page on developer.nvidia.com that lists every major open model, with optimized containers, tutorials, and deployment guides for each one. It's the best-organized AI resource nobody talks about.

Anthropic's agentic CLI reads your codebase, edits files, runs commands, and commits changes. No IDE plugin. No web UI. Just a terminal that understands what you're building.