Give AI the right context
Break work into useful pieces, communicate constraints, and provide the context that makes an answer relevant to the system you actually have.
04 / AI ENGINEERING & MENTORING
Better tools help. Knowing how to direct them, question them, and take responsibility for the result matters just as much.
Break work into useful pieces, communicate constraints, and provide the context that makes an answer relevant to the system you actually have.
Use AI across exploration, implementation, testing, and review. Keep humans responsible for the decisions and the release.
Learn to challenge an answer, check it against existing decisions, and verify the result. Confident output still needs evidence.
Consider when AI adds value, when it creates unnecessary work, and how to avoid repeated prompting that consumes time without improving the result.
Practical working sessions grounded in your team’s real tasks, with reusable habits and guidance you can apply after the session. Scope depends on your experience and goals.
I have used AI in my day-to-day engineering since 2023 and train and guide other engineers in doing the same. My approach combines early hands-on adoption with lead engineering responsibilities and an emphasis on verification, cost, and accountability.
A FEW USEFUL ANSWERS
Yes. AI changes the workflow, not the need for engineering judgement. Sessions can focus on architecture discussions, context management, agent-assisted work, and reviewing outputs against existing systems.
The starting point is your work and the tools available to you. The emphasis is on transferable engineering practices rather than selling a particular subscription.
We can discuss your starting point and goals. For a founder with an AI-built app, an initial code review may be more useful; for an engineer, guided work on a real task may be the right first step.
LET’S FIND A USEFUL STARTING POINT.
A short description, your timeframe, and the budget you have in mind are enough to start.