The right kind of AI sceptic - The Engineering Manager
-
Zur Stelle im OriginalRead about AI opinion online and you get two camps: those who believe it will fundamentally reshape how software gets built, and those who see it as useful tooling but doubt the transformative claims being made around it.
-
Zur Stelle im OriginalThis article is about finding the right mixture of optimism and scepticism, and learning to hold a flexible, informed opinion that benefits both you and how you’re perceived by others.
-
Zur Stelle im OriginalYou might have used the tools extensively, kept on top of the latest research, and landed somewhere genuinely unconvinced. That’s totally fine. Or you might have absorbed your position through proximity, adopting the talking points of people around you without firsthand exposure, and stopped there. That’s not so fine.
-
Zur Stelle im OriginalIn some developer communities, dismissing AI has become a way of signalling belonging, and the position reinforces itself through repetition rather than evidence.
-
Zur Stelle im OriginalThere’s a name for this pattern: the crab bucket describes a group where no individual is allowed to escape, because the others keep pulling them down.
-
Zur Stelle im OriginalIf ungrounded scepticism is one failure mode, ungrounded enthusiasm is the other, and it’s arguably done more damage while feeding the very scepticism it dismisses.
-
Zur Stelle im Originalenthusiasts with budget authority can hurt entire organisations, because when they overcommit and underdeliver, they hand sceptics exactly the evidence they were looking for.
-
Zur Stelle im OriginalFriends and acquaintances have told me about receiving AI usage mandates from leadership at their own companies with zero guidance, no clear examples of leaders using the tools hands-on themselves, and access to only a limited set of enterprise tools chosen by people who clearly hadn’t done any real evaluation or had a single technical bone in their body.
-
Zur Stelle im OriginalThe enthusiast who dismisses every failure as “early days” is doing the same thing as the sceptic who dismisses every success as “cherry-picked.”
-
Zur Stelle im OriginalNeither is thinking clearly, and both are optimising for being right over being accurate. And, if you think about it, AI just happens to be the catalyst for seeing this behaviour, and it’s a big human bug that we need to fix if we want to be clear and rational thinkers.
-
Zur Stelle im OriginalThe first practice is the most obvious, and the one most often skipped: actually use the tools for yourself.
-
Zur Stelle im OriginalSit down with the best available model, bring it a real problem from your actual work, and spend enough time to form a genuine impression for yourself.
-
Zur Stelle im OriginalThe second is to separate capabilities from claims. “AI can generate working code from a natural language prompt” is an observable fact: you can verify it immediately. “AI will replace most software engineers within five years” is a prediction, and a speculative one at that.
-
Zur Stelle im Originalboth sides conflate these categories in surprisingly lazy ways
-
Zur Stelle im OriginalThe third is to make your scepticism specific.
-
Zur Stelle im OriginalSpecificity forces you to think about what exactly you believe
-
Zur Stelle im OriginalThe fourth, and perhaps the most revealing, is to ask yourself a simple question: what would change your mind?
-
Zur Stelle im OriginalThe fifth is to engage seriously with the strongest version of the opposing view.
-
Zur Stelle im OriginalWhat this means for your team
-
Zur Stelle im OriginalThat means resisting the temptation to mandate enthusiasm or punish scepticism, because both of those shortcuts produce compliance rather than genuine engagement
-
Zur Stelle im OriginalWhat you want is a team that’s actively experimenting, sharing what’s working and what isn’t, and building on each other’s discoveries.
-
Zur Stelle im OriginalSharing experiments like that, including the ones that produce nothing interesting, signals to your team that this is about curiosity and outcomes, not about picking a side.
-
Zur Stelle im Original“Did this tool help you ship faster, and if not, why not?” is a conversation that goes somewhere. “Do you believe in AI?” is not.