LinkedIn
recommended
Angle: making AI tuning auditable before it can affect runtime behavior.
Risk level: low
Loaded convention path: missing local social convention docs; fallback to ship-end BIP contract.
Claim-safety notes: process claim only; no performance, model-quality, or launch claim.
Publish precheck: verify repo notes are intended public and do not expose private roadmap details.
I added a small convention to the project: when I ask for "AI tuning," agents should run the offline evidence/review loop, not edit runtime AI directly. The loop runs deterministic local scenarios, writes structured logs, produces candidate review notes, and keeps every candidate as "not promoted" until a human-reviewed promotion path exists.
X
recommended
Angle: concise guardrail around AI automation.
Risk level: low
Loaded convention path: missing local social convention docs; fallback to ship-end BIP contract.
Claim-safety notes: no claim that the AI is improved, only that the workflow is safer.
Publish precheck: avoid naming specific candidate values unless the report is public-safe.
Project convention added: "tune the AI" means run the offline AI-TUNE evidence loop, not patch live browser AI. Simulate locally, review structured logs, keep candidates as evidence, and promote nothing without explicit human-reviewed runtime values.
Bluesky
recommended
Angle: small safety boundary for game AI iteration.
Risk level: low
Loaded convention path: missing local social convention docs; fallback to ship-end BIP contract.
Claim-safety notes: keeps source-safe wording and avoids unverifiable outcome claims.
Publish precheck: confirm no internal agent tooling details should remain private.
Useful game-AI workflow rule: AI tuning requests should produce review evidence first. Runtime behavior only changes after a reviewed promotion step. This keeps tuning from becoming an accidental path for opaque or unsafe behavior to ship.
Mastodon
recommended
Angle: deterministic local testing before live behavior changes.
Risk level: low
Loaded convention path: missing local social convention docs; fallback to ship-end BIP contract.
Claim-safety notes: no external benchmarks or public quality claims.
Publish precheck: use content warning if paired with war-game screenshots.
Added an agent note to keep game-AI work boring in the right way: "AI tuning" now routes to local deterministic scenario runs, structured logs, and candidate review. Runtime AI stays authored until a later promotion task explicitly names the values and files.
Reddit
not-now
Angle: workflow feedback post for game-dev process communities.
Risk level: medium
Loaded convention path: missing local social convention docs; fallback to ship-end BIP contract.
Claim-safety notes: would need a concrete question and public artifact link.
Publish precheck: read community rules and avoid promotional framing.
Possible title: "How do you keep offline AI tuning from accidentally becoming runtime behavior?" Body should ask for process critique, not market the project.
Hacker News
rejected
Angle: process note about deterministic game-AI tuning.
Risk level: high
Loaded convention path: missing local social convention docs; fallback to ship-end BIP contract.
Claim-safety notes: not enough standalone technical artifact for HN yet.
Publish precheck: wait for promotion-packet tooling or a deeper technical write-up.
Rejected for this wrap-up. Save for a later post once the fail-closed promotion gate and run manifest exist.