The AI Capability Audit
A framework for mapping current work, deciding where AI can help, naming what stays human-owned, and choosing the first workflow worth changing.
Notes and essays on AI-amplified work, workflow design, verification, and the habits that make generated output easier to trust.
A framework for mapping current work, deciding where AI can help, naming what stays human-owned, and choosing the first workflow worth changing.
A practitioner essay on token economics, model routing, and why serious AI work needs just enough intelligence for each part of the job.
A practical protocol for using Think path, Build path, Safe Lane, and local model delegation while keeping accountability intact.
A practitioner essay on AI slop, judgment, and why serious AI writing needs a repeatable review system.
A response to Fast Company's coverage of Microsoft's 2026 Work Trend Index, and why the next AI advantage comes from work design, judgment, and repeatable capability.
A framework for mapping current work, deciding where AI can help, naming what stays human-owned, and choosing the first workflow worth changing.
Notes on delegation boundaries, orchestration, and usable agentic work.
Practical writing on building AI-enabled systems with visible checks.
How real work changes when AI has a bounded job, context, and review.
Writing about local-first thinking, reusable context, and durable capture.
Operating rules for people who use AI while keeping judgment visible.