Open · Community driven · Vendor neutral
AI Engineering Standard
The open, vendor-neutral community standard for production AI delivery
Knowledge base and operating playbooks are shipped. What remains Draft is industry adoption: external pilots, shared governance, and inter-org critique — not inventing the practices.
Maintained in the open. Attribution: project steward · not a personal portfolio.
Why AI engineering needs a standard
Teams invent private dialects for prompts, agents, evals, and approvals. The result is unreproducible delivery, silent security gaps, and tools that cannot interoperate. AIES exists so organizations share one vocabulary, one set of gates, and one way to evidence production readiness — without locking to a single model vendor.
Trust comes from documentation, versioning, and community critique — not from declaring “the standard” on day one.
Standards by capability
Organized by engineering concern — not by a laundry list of frameworks.
Engineering principles
The constitution every AIES artifact should obey.
Adoption roadmap
Corpus is shipped. What remains is external adoption and shared governance.
- A1Corpus publish — prompts, skills, MCP, evals, AIDLC, patternsdone
- A2Packaging & discoverability for external contributorscurrent
- A3External pilots with published evidence notesnext
- A4Shared governance + non-steward RFC reviewersplanned
- A5Inter-assessor SoA reliability notesplanned
- S1Community-standard claim (adoption earned)future
Community & contributing
AIES improves through issues, PRs, pilot evidence, and disagreement on the record.