Notes
Notes
Short, research-backed writing from Marc Lapointe of Lapointe Labs. Skim the takeaway. Dive only if it earns your attention.
- What is an AI Implementation Audit? — Lapointe Labs by Marc Lapointe
Lapointe Labs sells one thing: a two-week audit that turns a stalled AI pilot into a numbered, sequenced repair plan.
- The frontier is shorter than your planning cycle
Treat the model like a depreciating dependency. Own the tasks, constraints, and evals around it.
- Staying ahead is a control loop, not a tool stack
Optimize evidence latency: learn fast in the lab, change production on purpose.
- Cheap code needs a verification budget
Token price is not the cost of change. Budget review, tests, and rework like first-class spend.
- Moving upstream is not a career strategy
Upstream work is useful. Your moat is a closed feedback loop — not a higher job title.
- Why AI work stalls after the demo
Demos die from ordinary gaps: ownership, evals, and sequencing — not model quality.