Every episode of the Cynical Developer podcast

As building gets cheap, the bottleneck moves from “how” to “what”. We look at the rise of the product-minded engineer — someone who understands the customer, the business and the outcome, and happens to be able to build.

A fear runs under a lot of AI conversations: that experienced engineers are worth less now the machine can write code. We argue it’s close to the opposite — AI raises the floor on output but raises the ceiling on judgement far more.

If AI writes the boilerplate, tests and CRUD screens juniors used to learn on, how does anyone become senior? We look at the apprenticeship we’ve quietly automated away — and the slow, deferred bill that comes with it.

The whiteboard puzzle always tested the one mode the job never uses — alone, from memory, no help. We look at why AI finally makes that impossible to ignore, why hiring clings to it anyway, and what’s worth measuring instead.

We argue prompt engineering is already on its way out — and what’s replacing it is one of the oldest skills in software. When generating code gets cheap, deciding precisely what to build becomes the whole game.

A quiet split is forming in software teams — not junior versus senior, but developers who’ve learned to work with AI and those who’ve decided not to. We look at what the divide really is, why it compounds, and why plenty of brilliant people are on the wrong side of it.

We dig into the gap between responsibility and ownership — why so many teams are accountable for outcomes they were never given the authority to control, and how “you own this” quietly becomes “you hold the pager”.

We take on the tidy story that remote work killed productivity. It didn’t — it removed the things that were hiding weak management. We look at the presence trap, what genuinely broke, and why the easy diagnosis pointed at the wrong people.

We look at a cost that never shows up on any report: the wreckage an interruption leaves behind. Not the thirty-second question, but the twenty-minute rebuild — and why unpredictability, not volume, is what really destroys deep work.