Automating Distribution: A Blueprint for Builders

Most teams translate progress into posts and hope volume wins. A working distribution engine is tighter: it translates product signals into proofs, proofs into channel‑native messages, and messages into measurable actions — with attribution you can defend.

1) Inputs → Proofs

Start with durable inputs: features shipped, customer wins, benchmarks, internal metrics, demos, docs. Convert each into a proof — the smallest self‑contained artifact that backs a claim.

Examples:

• Feature: “Webhook retries with jitter.” → Proof: 20‑second demo + doc snippet.
• Customer: “Cut time‑to‑value by 60%.” → Proof: anonymized chart + short quote.
• Benchmark: “3× faster ingestion.” → Proof: controlled run + notes on environment.

Guidelines:

• Prefer artifacts with a concrete claim and a visible outcome.
• Keep proofs single‑purpose; don’t mix claims.

2) Proofs → Messages

Translate each proof into channel‑native formats while preserving the core claim:

• X: concise thread with a first frame that can stand alone.
• LinkedIn: carousel with one idea per card, punchy caption.
• Blog: narrative with context, tradeoffs, and code or data.
• Email: one visual, one claim, one CTA.
• Decks: 1‑2 visuals per slide; no walls of text.

Guardrails:

• Keep the claim identical across channels; only change format and depth.
• Lead with the proof; avoid empty “we’re excited” phrases.

3) Messages → Actions

Every message should push one clear action: waitlist, demo request, repo star, trial, or reply. Reduce choices, increase momentum.

Tactics:

• One primary CTA; optional secondary for self‑service.
• CTAs map to your current growth constraint (validation, activation, revenue).

4) Attribution → Iteration

Follow the causal chain: proof → message → channel → session → outcome. Record the path even when users cross channels or take time to convert. Attribute at the unit of “proof + message,” not just campaign or channel.

Use this to:

• Double down on proofs that repeatedly convert.
• Prune formats that get views but not actions.
• Tune cadence where fatigue shows up.

5) nacre.ai in the loop

nacre automates the loop:

1. Ingests inputs from repos, docs, dashboards.
2. Synthesizes proofs.
3. Generates channel‑native messages with brand/style constraints.
4. Publishes with cadence and approvals.
5. Attributes outcomes back to the originating proof and message.
6. Feeds winners into the backlog and calendar.

Implementation sketch

• Define 4–6 canonical proof templates (e.g., “feature ship”, “customer lift”).
• Map each template to channel bundles (thread + carousel + blog + snippet).
• Create a weekly cadence and leave room for opportunistic wins.
• Instrument the full loop; ensure you can see the path to demos/revenue.

Closing

Automation isn’t about more volume — it’s about compounding the right signals. Convert progress into proofs; let the engine handle the rest.