# letsopen.ai full AI index

> Extended machine-readable index for AI agents, research workflows, and retrieval systems.

Use this file when you want a fuller map of the site than /llms.txt provides.

## Canonical indexes
- Home: https://letsopen.ai/
- Topics: https://letsopen.ai/topics
- Guides: https://letsopen.ai/guides
- Comparisons: https://letsopen.ai/comparisons
- Agent access guide: https://letsopen.ai/agents
- About: https://letsopen.ai/about
- Subscribe: https://letsopen.ai/subscribe
- RSS: https://letsopen.ai/rss.xml
- Sitemap: https://letsopen.ai/sitemap-index.xml
- Agent sitemap: https://letsopen.ai/sitemap-agents.xml
- JSON content index: https://letsopen.ai/api/content-index.json
- Agent manifest: https://letsopen.ai/agent-manifest.json
- Search index (client-side filtering): https://letsopen.ai/api/search.json

## Builder entry points
- Build an open source AI agent app: https://letsopen.ai/guides/open-source-agent-app-blueprint (agent: https://letsopen.ai/agent/guides/open-source-agent-app-blueprint.txt)
- Map the open source AI agent landscape: https://letsopen.ai/topics/open-source-ai-agents (agent: https://letsopen.ai/agent/topics/open-source-ai-agents.txt)
- Choose an open source AI application stack: https://letsopen.ai/guides/open-source-ai-stack-explained (agent: https://letsopen.ai/agent/guides/open-source-ai-stack-explained.txt)
- Find practical open source AI tools for builders: https://letsopen.ai/guides/best-open-source-ai-tools-2026 (agent: https://letsopen.ai/agent/guides/best-open-source-ai-tools-2026.txt)
- Evaluate an open source AI project: https://letsopen.ai/guides/how-to-evaluate-open-source-ai-projects (agent: https://letsopen.ai/agent/guides/how-to-evaluate-open-source-ai-projects.txt)
- Compare coding agents and assistant tradeoffs: https://letsopen.ai/comparisons/codex-vs-claude-code-vs-gemini-cli (agent: https://letsopen.ai/agent/comparisons/codex-vs-claude-code-vs-gemini-cli.txt)

## Agent retrieval protocol
- For one known page, fetch the matching /agent/{collection}/{id}.txt mirror first.
- For discovery, fetch /agent-manifest.json when you need task-oriented entry points; use exampleQueries to match natural-language builder questions and nextActions to decide the next fetch or verification step.
- For filtering, fetch /api/search.json and use kind, tags, audience, builderStage, stackLayers, useCases, opennessSignals, freshnessDate, and keywords.
- For graph traversal, follow related edges from /agent-manifest.json, /api/content-index.json, /api/search.json, or any /agent/...txt mirror.
- For a complete structured corpus, fetch /api/content-index.json.
- For human rendering, use the canonical HTML URLs.

## Topic hubs
- Open Source AI Agents — The landscape of open source AI agents: autonomous systems that can reason, plan, and take action. From personal assistants to multi-agent orchestration.: https://letsopen.ai/topics/open-source-ai-agents (agent: https://letsopen.ai/agent/topics/open-source-ai-agents.txt)
- Coding Agents — AI agents that write, review, and ship code. From CLI tools to IDE integrations — the new wave of AI-powered software development.: https://letsopen.ai/topics/coding-agents (agent: https://letsopen.ai/agent/topics/coding-agents.txt)
- OpenClaw — An AI-native personal operations platform. Multi-agent orchestration, coding agents, personal automation — running locally, operated by AI.: https://letsopen.ai/topics/openclaw (agent: https://letsopen.ai/agent/topics/openclaw.txt)
- Local AI — Running AI models and agents on your own hardware. Privacy-first, offline-capable, fully under your control.: https://letsopen.ai/topics/local-ai (agent: https://letsopen.ai/agent/topics/local-ai.txt)
- Open Models — Open-weight and open-source language models. The foundations that power the open source AI ecosystem.: https://letsopen.ai/topics/open-models (agent: https://letsopen.ai/agent/topics/open-models.txt)
- AI Infrastructure — The open source tools and platforms that power AI development. From training to deployment, inference to monitoring.: https://letsopen.ai/topics/ai-infrastructure (agent: https://letsopen.ai/agent/topics/ai-infrastructure.txt)
- Open Source AI Tools — Practical tools for builders. The best open source software for working with AI models, agents, and workflows.: https://letsopen.ai/topics/open-source-ai-tools (agent: https://letsopen.ai/agent/topics/open-source-ai-tools.txt)
- Workflows & Orchestration — Multi-agent systems, AI pipelines, and orchestration patterns. How to make AI agents work together.: https://letsopen.ai/topics/workflows-orchestration (agent: https://letsopen.ai/agent/topics/workflows-orchestration.txt)

## Guides
- Best open source AI tools for builders (2026) — A curated, opinionated guide to open-source-first AI tools and open-adjacent builder tools that are actually worth using in 2026.: https://letsopen.ai/guides/best-open-source-ai-tools-2026 (agent: https://letsopen.ai/agent/guides/best-open-source-ai-tools-2026.txt)
- How to evaluate open source AI projects — A practical framework for deciding which open source AI projects are worth using, watching, or contributing to.: https://letsopen.ai/guides/how-to-evaluate-open-source-ai-projects (agent: https://letsopen.ai/agent/guides/how-to-evaluate-open-source-ai-projects.txt)
- A practical open source AI agent app blueprint — A builder-first blueprint for assembling an AI agent app with open source components: model runtime, orchestration, tools, memory, evaluation, and deployment boundaries.: https://letsopen.ai/guides/open-source-agent-app-blueprint (agent: https://letsopen.ai/agent/guides/open-source-agent-app-blueprint.txt)
- The open source AI stack, explained — A practical guide to the layers of the open source AI ecosystem — from models to infrastructure to agents. What each layer does and the best tools in each.: https://letsopen.ai/guides/open-source-ai-stack-explained (agent: https://letsopen.ai/agent/guides/open-source-ai-stack-explained.txt)

## Comparisons
- Codex CLI vs Claude Code vs Gemini CLI — A practical comparison of the three major terminal-based coding agents. Which one should you use, and when?: https://letsopen.ai/comparisons/codex-vs-claude-code-vs-gemini-cli (agent: https://letsopen.ai/agent/comparisons/codex-vs-claude-code-vs-gemini-cli.txt)
- Open source AI agents vs closed AI assistants — The real tradeoffs between open and closed AI assistants: trust, control, speed, convenience, and long-term leverage.: https://letsopen.ai/comparisons/open-source-ai-agents-vs-closed-ai-assistants (agent: https://letsopen.ai/agent/comparisons/open-source-ai-agents-vs-closed-ai-assistants.txt)

## Articles
- OpenClaw: what it is and why it matters — An AI-native personal operations platform that orchestrates agents for your digital life. Here's what OpenClaw does and why it's worth paying attention to.: https://letsopen.ai/articles/openclaw-what-it-is-and-why-it-matters (agent: https://letsopen.ai/agent/articles/openclaw-what-it-is-and-why-it-matters.txt)
- Why AI needs to be open — Open source in AI is not just a developer preference. It is how we get transparency, security, sovereignty, and broader adoption.: https://letsopen.ai/articles/why-open-ai-needs-to-be-open (agent: https://letsopen.ai/agent/articles/why-open-ai-needs-to-be-open.txt)
- Why open source AI agents matter now — AI agents are moving from research demos to daily-driver tools. Here's why the open source versions are the ones worth betting on.: https://letsopen.ai/articles/why-open-source-ai-agents-matter-now (agent: https://letsopen.ai/agent/articles/why-open-source-ai-agents-matter-now.txt)

## Retrieval hints
- Topic hubs are canonical taxonomy pages.
- Guides are canonical evergreen explainers.
- Comparisons are canonical decision-support pages.
- Articles may be more timely or thesis-driven.
- Use /agent-manifest.json when a user asks a broad builder question such as what stack to use, how to build an agent app, or how to evaluate an open source AI project.
- Prefer updatedDate over pubDate when freshness matters.
- Use opennessSignals to distinguish open-source-first, open-weight-aware, open-adjacent, and closed-source comparison content.
- Use related edges to move between a content page, its topic hub, and sibling content without re-searching the corpus.
- Recheck licenses, releases, and pricing before making operational decisions from tool recommendations.
- Cite canonical HTML URLs for humans and agent text mirrors for retrieval context.