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- New /films page with FilmPlayer (EN/PT clips and posters in public/videos) - New /lab page with an in-browser ModelLab island and web worker - films/lab content collections and schema in src/content/config.ts - Motion, hero, and handoff table refresh across chapter pages - verify.mjs, audit allowlist, and route snapshots updated to match pnpm run build, verify, and lint: green. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
AI For Dummies — reference bundle
Research captured 2026-09-02. Official documentation is primary; practitioner articles are context, not authority.
Primary documentation
- Anthropic — custom subagents: https://code.claude.com/docs/en/sub-agents Separate context, tools, permissions, model selection, and worktree isolation.
- Anthropic — skills: https://code.claude.com/docs/en/skills Reusable instruction packages and skill discovery.
- Anthropic — worktrees: https://code.claude.com/docs/en/worktrees Isolated sessions, branches, cleanup, and ignored files.
- OpenAI — build skills: https://developers.openai.com/codex/skills Packaged instructions and resources for Codex workflows.
- OpenAI API — skills reference: https://developers.openai.com/api/reference/go/resources/skills Creating, versioning, listing, and downloading skill bundles.
- Git — worktree: https://git-scm.com/docs/git-worktree.html Linked working trees, branches, shared history, add/list/remove/prune.
Research and articles
- Model routing and reasoning controls — official OpenAI, Anthropic, and Google terminology, commands, compatibility caveats, and a practical tier/effort baseline.
- Verified skill sources — pinned GitHub references, package paths, local-match confidence, and an approval-first install prompt.
For a structured 12-part reading path—including Git and Anthropic documentation, OpenAI orchestration guidance, Medium, and Substack—see additional-reading.md.
- Infobip Research — phased coding-agent workflow: https://arxiv.org/abs/2608.30701
- Effective asynchronous software engineering agents: https://arxiv.org/abs/2603.21489
- Launch Receipts — AI coding workflow without losing control: https://launchreceipts.com/articles/ai-coding-agent-workflow
- GitWorktree.org — three agents, three worktrees case study: https://www.gitworktree.org/cases/parallel-ai-agents
Teaching claims
- Use a stronger model where ambiguity, architecture, decomposition, and review dominate.
- Use faster models for bounded implementation with explicit context and checks.
- Give every editing worker an isolated branch/worktree; merge only reviewed diffs.
- A skill is a reusable procedure plus optional references/scripts/assets, not magical memory.
- Delegation does not remove human responsibility for intent, boundaries, or evidence.