Lean governance for AI-assisted development: requirements tracking, test enforcement, epistemic context compression, auditable evidence, Grace local REPL, and coding-agent integrations.
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Updated
Jul 27, 2026 - Python
Lean governance for AI-assisted development: requirements tracking, test enforcement, epistemic context compression, auditable evidence, Grace local REPL, and coding-agent integrations.
Certified log-concavity of the Riemann-Jacobi kernel with Arb/FLINT ball-arithmetic certificates. Source-critical audit of the Polya-type real-zero criterion. No unconditional RH claim.
Research and DOI publications hub for Hermes Labs: a Zenodo-canonical, DOI-anchored index of papers on epistemic and hermeneutic failure modes in large language models — null-result asymmetry, source-status bias, silent instruction relaxation. Each entry links its DOI, summary, and the tools that operationalize the findings.
Hermes Labs — the reliability, audit, and evidence layer for production AI. An independent research lab studying how language models fail structurally, then shipping open-source tools, evals, and audits that surface those failures before production does. EU AI Act, ISO/IEC 42001, and NIST AI RMF readiness.
Self-governing orchestration framework with 8 phases, 4 human review gates, BLAKE3 audit chain, and ethical axiom enforcement
Build spec-driven AI development with constraints, traceable decisions, and a ledger that records every change
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