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What should I test first for a checkable AI-work stack?

Project Telos is scheduled to launch here on June 26. I am building it around one rule: if AI work matters, the person and the system should be looking at the same checkable state, not trusting the model's self-report.

The public line is five flagships:

- gather: witnessed intake and provenance receipts

- index: rerunnable workspace maps and MATCH / DRIFT / UNVERIFIABLE certificates

Looking for workflow testers for the five-flagship Telos stack

Project Telos is now at the point where outside workflow tests are more useful than private polishing.

The current public pieces are:

- gather: source intake receipts

- index: evidence-built workspace maps

ZentropyLabs.ai - I build systems for tomorrow.

Systems engineer and cross-domain builder whose work spans AI-agent infrastructure, compilers and language tooling, real-time graphics and color science, verification systems, docs, and operations. Builds inspectable tools with explicit boundaries, tests, documentation, provenance, and reproducible release paths. Independent engineering practice, grounded in earlier technical support, freelance technical writing, compliance documentation, customer-facing operations, and field leadership.