◆ Research
A body of visible work, not a CV.
Independent write-ups on secure GenAI, governance, and the psychology of adoption — grounded in primary sources, no hype, uncertainty shown.
◆ The cornerstone piece
The AI Engineering Pipeline
The whole path, mapped end to end — idea to monitoring — with the frameworks, the SDKs, and the trichotomy I keep coming back to: Prompt vs Context vs Loop engineering. Plus a working shootout of Claude Code vs Codex vs OpenCode.
LifecycleFrameworksContext engineeringAgent loopsTooling shootout
Read the pipeline →Essays & write-ups
On the blog
Longer-form pieces — secure GenAI deployment, governance, and the human side of adoption — are published as dated posts.
Secure GenAIGovernanceAdoption
The receipts
Projects
Real, running systems and honest notes on where each one actually got to — including the design decisions I would defend and the ones I would not repeat.
Open sourceHonest statusLive