Engineers, devrel teams, and AI builders
Turn technical learning into public signal.
Turn messy learning notes, product opinions, and real replies into public posts and useful agent context without making everything sound like polished marketing.
The gap
What this should prevent
Useful ideas are scattered across Slack threads, GitHub comments, support conversations, and half-written posts.
AI drafts tend to over-polish the point and hide the actual product tradeoff.
The best reply usually needs context from the source, not a generic technical opinion.
Workflow
How the spec becomes useful
Collect the trail
Pull public posts, replies, comments, and later work-source receipts into one reviewable signal set.
Extract the operating taste
Turn repeated objections, examples, vocabulary, and judgment calls into rules an agent can actually follow.
Draft from the receipt
Generate posts and replies that cite the artifact or failure mode that made the idea worth saying.
Artifacts
What you get out of it
Content inbox
Seeds from recent technical learning, each with hooks, platform fit, and source links attached.
Coding-agent skill
A portable skill that gives Codex, Claude, and other local agents the same technical voice constraints.
Conversation radar
A watchlist of communities, topics, and public conversations worth replying to without sounding forced.
Starting signal
Sources this use case cares about
X posts and repliesReddit commentsSlack/work chat laterGitHub issues and docs later
Prompts
Examples this should unlock
Turn this debugging thread into a short X post with the source link.
Reply to this agent UX take without sounding like a brand account.
Find the real product lesson in this Slack thread.