# claude-code

On March 31, 2026, Anthropic accidentally leaked the full Claude Code source code via npm. Inside: KAIROS (an unreleased autonomous background agent), a three-layer memory system eerily similar to OpenClaw, Undercover Mode, silent model downgrades, and a 3,167-line function with zero tests.

Paweł Huryn proposes the Vibe Engineering framework: instead of accepting raw AI output, use Context Engineering, Intent Engineering, and Sub-agent orchestration to upgrade AI coding from 'lucky demos' to 'reliable products'.

Boris Cherny shares 15 lesser-known Claude Code features he uses every day — from the mobile app and loop/schedule to worktrees and voice input.

rodspeed lays out six ways to use Claude Code as general automation, not just a code editor: fresh eyes, meta-skills, freshness-aware search, conversation harvests, structured memory, and handoffs. The deeper pattern is read, filter, decide, present.

Simon Willison used Claude Opus 4.6 and GPT-5.4 to vibe code two macOS menu bar apps — one for network traffic, one for GPU stats. The entire SwiftUI app fits in a single file, no Xcode needed. But he's the first to admit: he has no idea if the numbers are accurate.

Boris Cherny says his team lets Claude Code find 99%+ of bugs first, then an engineer sanity-checks to make sure nothing obvious slipped through.

Paweł Huryn responds to 'Anthropic's team doesn't write code anymore': the headline is right, but the framing is wrong. The bottleneck was never 'spin up more agents' — it's how you design the knowledge architecture that makes them actually effective.

Thariq from Anthropic demos a Claude Code playground plugin that generates standalone interactive HTML pages — perfect for tasks where text-based interaction just doesn't cut it.

Anthropic engineer Thariq makes a blunt case for AI agents using the file system as state. The point is not just persistence — it is giving agents a place to search, verify, iterate, and recover instead of trying to one-shot everything from memory.

Anthropic engineer Thariq argues that even non-coding agents need bash. Saving intermediate results to files lets an agent search, compose API workflows, retry, and verify its own work — but it also raises real questions about security, data exfiltration, and container-based deployment.

Anthropic launches Claude Code Channels with native Telegram and Discord support, turning Claude Code into a 24/7 always-on AI agent. VentureBeat calls it the OpenClaw killer.

Why does Claude perform great in one repo and turn dumb in the next? The answer is the .claude/ folder. Akshay breaks down the full structure: three-level CLAUDE.md, custom commands, agents, permissions, and the global ~/.claude/ you probably didn't know existed.

Anthropic engineer announces that for the next two weeks, Claude Code users get 2x usage during off-peak hours and weekends. The post doesn't define what 'off-peak' means.

Many teams treat Claude Code and Codex as interchangeable tools, only to waste hours on misconfiguration. This article breaks down the fundamental differences in their control planes and trust models, with a practical day-one setup guide.

Anthropic quietly released Dispatch, letting you remotely control Claude Cowork on your computer from your phone. Here's how to set it up, which workflows actually work, and its real limitations right now.

Ole Lehmann shares a method that applies Karpathy's 'autoresearch' concept to Claude skills — letting an agent test, tweak, and improve your prompts automatically. His landing page copy skill went from 56% to 92% pass rate with almost zero manual work.

Anthropic's Thariq shares lessons from hundreds of internal Claude Code Skills: Skills are folders, not just markdown; they cluster into nine categories; and the secret is gotchas, progressive disclosure, and descriptions written for the model.

The author spent a week tearing apart Claude Code's 213MB binary and discovered it's essentially a massive prompt delivery system built on Bun, packed with unreleased features and telemetry.

Dan McAteer shares his long-context observations: Opus 4.6 performs best at 1 million tokens with 78% accuracy, Sonnet 4.6 is the closest competitor, and GPT-5.4 actually regressed compared to GPT-5.2 at long context.

Someone took the Claude Certified Architect exam content and broke it all down — five domains, core concepts, anti-patterns, and hands-on suggestions. The certificate doesn't matter; the knowledge does.