#distribution

Designing or marketing an API where an autonomous agent could evaluate, integrate, or transact on a developer's behalf — anything that sells or provisions something programmatically.

Planning docs work, an information-architecture overhaul, or deciding whether to publish llms.txt.

Docs served as markdown and OpenAPI with a quickstart that says "hand this spec to your LLM" — and a purchase flow (quote-token, idempotency keys, consent record) an agent can run without over-buying.

A solo, unfunded open-source launch topped Hacker News because the maker's decades of public credibility did the marketing and the artifact was runnable the moment you hit the repo.

Themed "innovation weeks" batch a year of shipping into a daily-drop cadence that manufactures anticipation and measurable signups.

300+ vetted engineer-writers and a stated 100+ devtool clients, Docker, JetBrains and Redpanda among the logos on the wall.

Team of ex-operators from GitHub, MongoDB and Atlassian, with AWS, GitHub, MongoDB, Netlify and Buildkite as clients, plus their own GA4/Search Console analytics app.

A managed network of coding creators with audiences from 52K to 1.8M subscribers, running cross-channel campaigns on Reddit and daily.dev, with Neon, Dub and Descope among the named clients.

Devtools and enterprise infrastructure only, with deepset, CircleCI, Prisma, RudderStack and Courier on the client wall.

Thirty-four skills covering audience context, content, distribution, developer experience, growth and retention — every one reads a shared developer-audience file first.

Scaffolds and validates an Agent Skill — the packaging format that puts your conventions, gotchas and idiomatic examples inside the agent your users already work in.

The knowledge layer for generative-engine optimisation — content patterns, structured data, crawler config, llms.txt, E-E-A-T and the monitoring to see if any of it moved.

Twelve skills that research, plan and then patch — AEO/GEO auditing with framework-specific fixes, shipped with worked plans for a Next.js blog and a WordPress site.

Probes robots.txt, llms.txt and llms-full.txt, scores AI-readiness against a structured checklist, and needs no API key.

Machine-mediated discovery moved a step this week — from AI assistants reading your docs to agents comparing and picking vendors — while a zero-budget open-source launch topped Hacker News on reputation alone.

Machine-mediated discovery is real — Vercel gets 10% of signups from ChatGPT — but most of what's sold as GEO is ritual. The work that pays is docs and API surfaces you should want anyway.

Coding assistants (Claude, Cursor, Copilot) and answer engines increasingly read and cite developer documentation, and practitioners are restructuring docs — and adding llms.txt — so machines can retrieve them, not just humans.

SlashData's Developer Nation data estimates over 47 million developers globally, but year-over-year growth has slowed to around 10% as the population ages and shifts toward South Asia and Greater China.