# v0.22.0 Launch Tweets

*Council Deliberation for Verification*

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## Main Announcement Thread

### Tweet 1 (Hook)

> LLM Council v0.22.0: Now with multi-model deliberation for code verification
>
> Instead of one AI saying "looks good" — multiple models review your code, anonymously rank each other's reviews, then synthesize a consensus verdict.
>
> Here's how it works

### Tweet 2 (Architecture)

> The 3-stage deliberation:
>
> Stage 1: Multiple models review your code in parallel
> Stage 2: Anonymous peer ranking (no model favoritism)
> Stage 3: Chairman synthesizes APPROVED/REJECTED verdict
>
> One model catches SQL injection, another spots race conditions. Together = better coverage.

### Tweet 3 (The Key Innovation)

> The secret sauce? Anonymous peer review.
>
> Models evaluate reviews as "Response A, B, C" — not "GPT-4, Claude, Gemini"
>
> No prestige bias. No self-promotion. Just quality-based ranking.
>
> Attribution only appears in the audit trail.

### Tweet 4 (CI/CD Integration)

> Built for CI/CD:
>
> Exit 0 = PASS (ship it)
> Exit 1 = FAIL (block deployment)
> Exit 2 = UNCLEAR (human review needed)
>
> Confidence threshold configurable. Low agreement? Automatically flags for human review instead of guessing.

### Tweet 5 (Security)

> Security hardened in this release:
>
> - Async file ops (no more blocking)
> - Streaming reads (DoS protection)
> - Path traversal prevention
> - Batched fetching with early termination
>
> Your verification API won't be the vulnerability.

### Tweet 6 (CTA)

> Try it:
>
> ```
> pip install llm-council-core==0.22.0
>
> llm-council verify $(git rev-parse HEAD) --focus security
> ```
>
> Docs: https://github.com/amiable-dev/llm-council

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## Standalone Tweets (Alternative Posts)

### Short Version

> LLM Council v0.22.0: Multi-model code verification
>
> - Single model: "looks good" (misses 2/4 issues)
> - Council: 3-stage deliberation with anonymous peer review
>
> Exit codes for CI/CD. Audit trails for compliance.
>
> `pip install llm-council-core==0.22.0`

### Technical Angle

> What if code review worked like academic peer review?
>
> LLM Council v0.22.0:
> - Multiple independent reviews
> - Double-blind evaluation
> - Consensus-based verdicts
> - Complete audit trail
>
> Except it takes 60 seconds, not 6 months.
>
> https://github.com/amiable-dev/llm-council

### Problem/Solution

> The problem with AI code review: one model, one opinion, one blind spot.
>
> The solution: deliberation.
>
> LLM Council v0.22.0 runs 3-stage verification:
> 1. Parallel reviews
> 2. Anonymous ranking
> 3. Chairman synthesis
>
> Confidence score included. Low agreement = human review.

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## Hashtags

Use sparingly: `#LLM #CodeReview #DevTools #AI #OpenSource #CICD`

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## Links

- GitHub: https://github.com/amiable-dev/llm-council
- PyPI: https://pypi.org/project/llm-council-core/0.22.0/
- Release: https://github.com/amiable-dev/llm-council/releases/tag/v0.22.0
- Blog: docs/blog/13-council-deliberation-verification.md
