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AI governance essays, reasoning systems notes, experiment logs, and technical writing across BioAI and engineering practice.
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Beyond M15: Why STEM BIO-AI Started Acting More Like a Governance Report in v1.8.x
STEM BIO-AI v1.8.x moved beyond M15 integration by turning its audit output into a clearer governance report with bounded scores, traceability, and release integrity.
When the Memory Gate Met a Real Archive: What 90 Experiments Taught Us About Cheap LLM Slop
How to enforce data integrity against AI-generated slop using MICA. Explore a 11-step session-start validator that locks rules, playbooks, and contracts in code before code is ever touched.
We Built AI Verification Infrastructure. Then It Found Our Blind Spots.
A technical account of the Flamehaven Verification Ledger — what it found, where it failed, and what we need the field to tell us
The README Was a Protocol. The Entrypoint Was Still Optional.
README-as-Protocol solved explicit invocation at the schema level. It did not solve entry control at the workflow level. This version adds the missing hierarchy: natural, guided, and forced activation.
From Repo Scanner to Audit Architecture: What Changed in STEM BIO-AI Through v1.7.8
A technical look at how STEM BIO-AI v1.7.8 became less Python-shaped, more semantically stable, and more inspectable across real audit output surfaces.
The Meeting Nobody Could Follow -The format of AI output is a design decision. We made it wrong for three years.
How our engineering team stopped sending 200-line Markdown files that nobody read — and what a nine-word post from an Anthropic engineer taught us about AI output format as a design decision. Includes token cost analysis, real prompt templates, and the HTML render layer approach used in production.
From Score to Workflow: Turning STEM BIO-AI Into a Local Audit System
Bio/medical AI trust should not collapse into one score. STEM BIO-AI v1.6.2 shows how deterministic auditing, evidence-led diagnostics, regulatory traceability, and bounded AI advisory can become an inspectable local workflow.
How Do You Trust the AI Auditor? STEM-AI v1.1.2 and Memory-Contracted Bio-AI Audits
STEM-AI v1.1.2 binds a bio/medical AI repository audit to a machine-checkable memory contract, then demonstrates it on a real open-source bioinformatics repository.
FLAMEHAVEN FileSearch: Why This RAG Engine Feels Different from the Usual Stack
A technical look at FLAMEHAVEN FileSearch: BM25+RRF hybrid retrieval, chunk-addressable indexing, deterministic DSP vectors, and the trade-offs behind a lower-overhead self-hosted RAG engine.
It Gets Smarter Every Scan: AI-SLOP Detector v3.5.0 and the Self-Calibration Loop
AI-built apps are starting to fail in public. Not every failure is static-analysis territory, but many share the same upstream condition: plausible-looking code passing review without carrying enough real logic. AI-SLOP Detector v3.5.0 adds a self-calibration loop to reduce that gap.
My AI Maintainer Kept Making Wrong Calls. So I Made It Report Its State Before Touching Anything.
Part 6 moves from landscape to operation. This is what MICA looks like when it is actually running inside a real maintenance workflow — session report, self-test, drift, invariants, and operator judgment.
Prompt → RAG → MCP → Agent → Harness, and What?
Why the next layer in AI may be governance infrastructure, not just better agents.
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