The Jevons paradox: why AI creates more demand - Martin Eriksson at ProductTank SF

Martin Eriksson founded ProductTank 16 years ago in the back room of a London pub with 20 people and has watched it grow into a community active in over 200 cities worldwide. He co-authored Product Leadership, has advised nearly 150 companies on product strategy and organisation, and now works as a solo consultant and coach. His talk draws on that experience to make a counterintuitive argument: in an era defined by AI-driven speed, the ability to build is no longer what separates winning product organisations from losing ones.

Key takeaways
— The Jevons paradox applies directly to AI: when something becomes cheaper and faster, demand doesn't stay flat, it explodes — AI imaging didn't shrink radiology, it created 16% more radiologists and pushed salaries up 44%.
— Amara's Law is playing out in real time: organisations are simultaneously overestimating what AI does in the short term and underestimating the structural shift it will force over the long term.
— AI has effectively solved the feasibility dimension of product work, but value, usability, and viability are as hard as they have ever been — which means building is not the job.
— Most companies are applying AI at the opportunities layer, bolting features and integrations onto an unchanged strategy; the companies winning are the ones rethinking strategy from the top of the decision stack down.
— Intercom's move from per-seat to outcome-based pricing — 99 cents per customer resolution, with a million-dollar performance guarantee — is the model for how AI should change business models, not just products.
— Speed without direction is just burning fuel on a runway; AI gives you speed, strategy gives you direction, and alignment across the organisation gives you momentum.
— Green-field builds with AI are seeing roughly 10x productivity gains; brown-field work on legacy codebases is closer to 20% — a difference large enough to change the build-versus-refactor calculus for many teams.

Chapters

(00:00) ProductTank origin story
(01:33) Why speed is not enough
(02:09) The hype and the panic
(03:20) The radiologist prediction
(04:35) What actually happened to radiologists
(05:34) The Jevons paradox
(06:08) Amara's Law
(06:27) AI is only getting started
(07:53) The DOS era of AI
(08:19) Follow the cost curve
(09:03) What if the cost of software goes to zero?
(09:57) The SaaS-is-dead myth
(10:44) Most of the world doesn't want to build software
(12:20) Probabilistic versus deterministic software
(12:43) An explosion of SaaS is coming
(13:06) What this means for product
(14:47) Building is not the job
(15:37) Treat AI as a multiplier
(16:38) The decision stack
(18:50) Companies applying AI at the wrong layer
(19:48) The Intercom case study
(21:38) The Kive case study
(23:14) The questions worth asking
(24:43) Speed, velocity, and momentum
(25:43) Alignment versus autonomy
(27:06) Discovery at the heart of it all
(27:26) Wrap-up Receive SMS online on sms24.me

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