Building a Lab for the Model
A performance-optimization case study showing how prompt contracts, multi-agent research, trace tooling, experimental memory, and validation turn an agent harness into a working environment for capable models.
AI-assisted coding, code review, debugging, and engineering validation.
4 articles
A performance-optimization case study showing how prompt contracts, multi-agent research, trace tooling, experimental memory, and validation turn an agent harness into a working environment for capable models.
A CI/CD infrastructure case study on why raw PE .text changes can be caused by relocation-covered address values rather than code logic changes, and why AI analysis still needs engineering validation.
Why AI coding's prompt-level specs organize work but do not verify complex system design, and where system-level formal methods like TLA+, P, and runtime conformance checking fit.
Why AI code review succeeds or fails less on comment generation and more on context supply, trust, and the shared intelligence layer between developers and agents.