Your daily LinkedIn post,
drafted from your real work.
PostAgent is a multi-agent system that turns your shipped work into posts worth reading. Open it. Pick one. Post.
LinkedIn writing is broken in both directions.
Builders ship real work every day and have nothing to show for it on LinkedIn. The blank page wins. Most "AI writers" replace the blank page with worse: recycled hooks, hollow claims, generic advice that nobody asked for.
The market is full of single-prompt content tools that produce slop at scale. There's no system anchoring writing to what the builder actually did this week, and no system catching the slop before it ships.
A 5-stage multi-agent pipeline
Each stage is bounded — budgeted LLM calls, narrow tool surface, idempotent. The whole pipeline runs end-to-end in about 75 seconds.
Reading your story
Loading proofs, trends, and recent posts
Thinking about angles
Brainstorming candidate topics from your story
Drafting
Writing 1–3 variants per topic
Quality checks
Receipts · anti-slop · jury vote
Finalizing
Picking winners and writing finals
Every draft shows the agent work
Reader-appeal score, full pipeline timing, tool calls, jury votes — visible per draft. No black-box generation.
A three-judge jury vetoes the slop
Every draft is read by three independent judges with sharp, different taste profiles. A draft only ships if it passes the jury.
Anti-Slop
Catches generic LinkedIn slop before it ships — recycled hooks, vague claims, hollow advice, and the usual hustle-grifter tropes.
Cynical Engineer
Reads every draft like a senior IC who has seen too much hype. Calls out unfounded claims and demands receipts for every assertion.
AI Builder
Reads as a peer building real products. Pushes for specificity, concrete examples, and writing that respects the reader.
A multi-agent compose pipeline with budgeted, idempotent stages
Story reader pulls proofs, trends, and recent posts as context — every draft is anchored to real work
Angle generator brainstorms candidate topics with a narrow, deterministic tool surface
Drafter writes 1–3 variants per topic with structured outputs
Quality stage runs receipts validation, anti-slop classification, and a three-judge jury vote
Finalizer picks the winning variants and writes the final post text
Per-stage budgets cap LLM call counts; each stage is idempotent and re-runnable
Reader-appeal score is computed from jury vote + classifier signal — visible per draft
One-click post to LinkedIn with edit-before-publish so the human stays in the loop
Built to be cheap to run and easy to ship
React + Vite frontend, Node.js + PostgreSQL backend, multi-model orchestration. Pipeline cost stays under a cent per draft.
Want to ship your own multi-agent system?
If you're building agentic workflows, content automation, or any multi-stage AI pipeline — we'll help you design, ship, and operate it.
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