Claude: Workflow

A detailed 6-step system for building an Obsidian vault that auto-captures content via Readwise, Airr, Whisper, and a Telegram bot, routes everything through N8N pipelines, and uses Claude to generate daily briefings and weekly syntheses. The core thesis: knowledge systems fail because they optimize for input, not output—feedback loops (daily briefs, weekly synthesis) are what turn a dead archive into a thinking partner.

gstack is Garry Tan's open-source Claude Code setup that transforms a solo AI assistant into a structured 6-role virtual engineering team (CEO, Eng Manager, Designer, QA, Release Engineer, Doc Engineer) via 23 slash-command skills. Tan claims ~810× his 2013 productivity rate measured in normalized logical lines of code, shipping 3 production services and 40+ features in 60 days part-time. The system enforces a think→plan→build→review→test→ship→reflect sprint discipline where each skill feeds context into the next, and supports 10-15 parallel sprints via Conductor.

Tolaria is a free, open-source (AGPL-3.0) desktop app for Mac and Linux that implements Karpathy's LLM wiki concept — a shared knowledge environment for humans and AI agents. It uses plain markdown, Git-backed vaults, and includes a built-in MCP server for Claude Code integration. Built with Tauri, React, and Rust; 100K+ lines, 85% test coverage, 9.9/10 code health.

Hannah Stulberg (DoorDash PM) built a shared git repo where every team function checks in context—call summaries, decision logs, analytics queries—queryable in natural language via Claude Code. Four independent implementations (DoorDash, Pendo, Google, solo) converged on the same 3-layer architecture, suggesting a generalizable pattern for solving institutional knowledge loss.

A workflow pattern combining LLM Wikis (structured knowledge stores) with interactive HTML Artifacts creates a bidirectional agent-UI layer. Artifacts are built on top of wikis, can invoke agents, and agents can update artifacts—enabling inbox-zero automation, research scheduling, topic discovery, and live figure generation from a single HTML file.

Comprehensive operator guide for Hermes Agent by Nous Research—an open-source autonomous agent framework with 150K GitHub stars and #1 OpenRouter usage. Covers architecture (brain/personality/skillset), four-level deployment progression (laptop to full VPS fleet), multi-agent control room patterns, a 21-step SEO pipeline, and the prototype→production methodology for marketing automation.

A structured /goal prompt template for AI coding agents (Codex, Claude Code, Hermes) that prevents scope creep, ranks uncertainties before acting, and closes completion loops. Key sections: GOAL (single measurable outcome), CONSTRAINTS, PLAN (understand-first), DONE WHEN (verifiable state), VERIFY (tests + rollback), STOP RULES (halt on ambiguity, surface ranked proposals not open questions).

Claude Code's /goal and Codex's /goal commands implement a completion-contract pattern: a working agent loops until a separate evaluator confirms a stated condition is met, judged only from evidence surfaced in the conversation. The post argues this punishes vague PM requirements faster than traditional development, raising the bar from 'write enough detail an engineer understands' to 'define done clearly enough an agent can keep trying and a harness can inspect proof.' Includes a practical goal template and anti-patterns.

Claude Code's real power comes from building the ecosystem around it—persistent memory (CLAUDE.md), project initialization (/init), parallel Git worktrees, MCP servers, plugins, subagents, and CI/CD integration—rather than prompting better. The claude-code-setup plugin automates recommending and installing these components.

Claude Code has launched 'agent view,' a consolidated list of all active sessions, currently available as a research preview. The feature addresses session management as Claude Code's multi-agent usage scales.