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Beta Release Notes (March 2026)

Release Status

This repository is now publicly available as a beta release.

This beta is intended for:

  • Developers using prompt files with VS Code + GitHub Copilot
  • Educators teaching practical prompt engineering workflows
  • Teams evaluating reusable prompt templates and learning materials

This beta is not intended to be a final benchmark authority for model-to-model performance comparisons.

What’s Included in This Beta

  • Seven-module curriculum in learn/
  • Reusable stack-specific prompt templates in prompts/
  • Setup and validation scripts in scripts/
  • MkDocs documentation site and CI quality gates
  • Centralized bibliography in references.md

Known Limitations

  • Some cross-model comparison guidance is a research synthesis and includes approximate figures for pedagogical use.
  • Model behavior can drift over time as providers update model versions.
  • Not all empirical claims are currently enforced by automated citation linting.
  • Reproducibility artifacts for all “validated against” statements are still being expanded.

Usage Guidance for Beta Readers

  • Treat benchmark-style comparisons as directional guidance, not guarantees.
  • Re-run evaluations on your own model versions, prompts, and datasets before production rollout.
  • Use the provided evaluation patterns to validate task-specific reliability in your environment.

Short-Term Hardening Plan

The next release cycle will prioritize:

  1. Stronger citation and empirical-claim validation in CI
  2. Expanded reproducibility artifacts for model validation claims
  3. Tightened dependency/reproducibility controls for local and CI runs
  4. Additional script/runtime tests for non-Markdown surfaces

Feedback and Issue Reporting

  • General improvements: open a GitHub issue or pull request
  • Security-related concerns: use the private security advisory path in SECURITY.md

Release Positioning (Suggested Copy)

The Prompt Engineering Playbook is released as a beta educational framework and template library. It is stable for learning and practical team adoption, while selected comparison and validation surfaces continue to be hardened for high-scrutiny research-style review.