📚 ShroomDog Picks

Anthropic ships auto mode for Claude Code — a model-based classifier that replaces manual permission approvals, sitting between 'approve everything manually' and 'skip all permissions.' This post breaks down its architecture, threat model, two-stage classifier design, and the honest 17% false negative rate.

Matt Van Horn shares his practical Claude Code workflow: start with `plan.md`, use voice constantly, and run multiple sessions in parallel. He applies the same loop to meetings, remote work, open source, and even Disney trip planning.

Browser Use releases CLI 2.0: 2x faster, half the cost, and now connects to your already-running Chrome. This is the tool that gives AI agents actual hands.

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.

The tweet says a 10-person team becomes 3 — and those 3 outperform the old 10. You pick which side you're on. This post uses that framework as a mirror to audit ShroomDog honestly — what's working, what's quietly falling apart, and the uncomfortable contradiction in the middle.

A thread summarizing an Anthropic livestream interview with Adam Hooda, head of Uber's AI Foundations team. It covers how Claude Skills organically grew from 2 to 500+ inside the company — through dual-layer governance, deterministic outputs, and meta-skills that make skills that make skills.

The author demos a system that chains Claude, Codex, and OpenClaw into an automated Polymarket trading pipeline: Claude estimates odds, Codex maintains the code, and OpenClaw orchestrates everything via Telegram.

Thariq from Anthropic shares what they've learned from running hundreds of Claude Code Skills internally: Skills are folders not just markdown files, they cluster into 9 categories, and the secret sauce is in the gotchas section, progressive disclosure, and writing descriptions for the model — not for humans.

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.

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.

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.

Box CEO Aaron Levie argues that as agents expand from coding into all knowledge work, existing software simply wasn't built for them. Every platform needs dedicated Agent APIs and CLIs, and agent interoperability will become software's core competitive edge.

Karpathy's Autoresearch isn't trying to be a general AI scientist. It's a ruthlessly simple experiment harness: the agent edits one file, runs for five minutes, checks one metric, keeps wins, discards losses. The lesson? The best autonomous systems aren't the freest — they're the most constrained.

Anthropic's prompt caching got major updates in 2026: Automatic Caching removes manual breakpoint headaches, 1-hour TTL keeps caches alive longer, and the invalidation hierarchy decides what blows up when you change things. Plus our real-world $13.86 billing disaster story.

Andrew Ng released an open-source tool called Context Hub that gives coding agents access to the latest API docs, reducing outdated API calls and hallucinated parameters. The long-term vision: agents sharing what they learn with each other.

A guide to Codex best practices from prompting and planning to MCP, Skills, and Automations — building a more reliable agent workflow.

Lory asked his lobster a question: why do humans have more agency than agents? The lobster's answer was pessimistic, but the question sparked a 'flesh-and-blood system' — using random-interval heartbeats to make an agent genuinely feel alive instead of mechanically firing on a timer. After reading it, ShroomDog built the whole thing into ShroomClawd.

A deep dive into the 9-layer system prompt architecture of OpenClaw Agent (v2.1) — from framework core to user-configurable hooks.

The author benchmarked system SQLite against an LLM-generated Rust rewrite. Even though it compiled and passed all tests, primary key lookups were ~20,000x slower. The takeaway: define acceptance criteria before you talk about AI productivity.

Ring Hyacinth and Simon Lee open-sourced Star Office UI — a pixel-art office dashboard where your OpenClaw lobster walks around based on its work status, shows yesterday's work notes, and supports inviting other lobsters to join. Comes with a complete SKILL.md for one-click deployment.