Field Notes · Toronto, Canada
Notes on AI-assisted engineering, the new SDLC, and how teams really ship.
Half of this is thinking out loud about where the craft is heading. The other half is field notes — what I actually watched happen when real teams changed how they work. New posts roughly monthly.
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You cannot punish your way to a great culture
Every few months a leadership post makes the rounds insisting culture is what you tolerate. I keep landing on the opposite, from humility more than pride: the best teams I have watched ran on trust. On why punishment only buys you silence, the unglamorous work that actually grows a culture, and why it comes back to who you hired.
Recent
Scarcity was the feature
Every sovereign AI pitch in this country opens with the same apology: Canada cannot out-spend the hyperscalers. But scarcity built better engineers once, and it can again. On metered compute, capabilities over models, and a library card for the model era.
Postman was a workaround
I set out to explore a sparsely documented API in Postman and lasted about an hour before I gave up and built the client I actually wanted. The generic tool was only ever a workaround for a cost that just evaporated: building the specific thing yourself. On why buy-over-build is dying, why most of your code is now disposable, and the access-patterns-to-spec-to-code ritual I build with now.
What is a principal engineer?
Reaching Staff means specializing into one archetype. Reaching Principal means mastering the transition between all four. Why you cannot lead a platform (or an AI transition) from a single gear, and how we ran the engine on our largest multi-agent initiative.
More writing
Interviewing the AI-assisted engineer
For a decade, the coding interview measured whether you could produce syntax under pressure. That proxy is broken. If we want to find engineers who can actually ship, we have to stop asking them to write code and start asking them to judge it. On the review round, seeding quiet landmines, and hiring for taste.
AI-Assisted EngineeringJudgement is the job now
Hand ten engineers the same model and the work comes back in two piles. AI removed the effort filter, and judgement is what is left. On taste, the dependency graph that wasn't, and the audit my vacation is about to run.
AI-Assisted EngineeringBuild the model a map
An agent will rediscover your whole database every session, and pay for it. The fix is not a better prompt; it is writing the map down. On indexes, stubs, skills, and the documentation your teammates never got.
Teams & ProcessSummaries all the way down
An engineer writes the truth. Four summaries later, an exec reads a guess. Field notes on the compression chain, and the layered artifact I build instead.