Sangeet Choudary: Who Learns Wins

25 snips

Feb 13, 2026

Sangeet Choudary, author and platform strategist who advises Fortune 500s and teaches at UC Berkeley, breaks down how AI is rewriting SaaS, workflows, and firm boundaries. He explains translation across silos, why redesigning systems beats automating old tasks, who captures value through learning, and how platforms and nations vie for advantage in an AI-driven economy.

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INSIGHT

Job Value Depends On Economic Logic

The important change is capability revaluation: tasks that once conferred value can be commoditised quickly.
Being 'someone using AI' won't save you if the job's logic (not tasks) loses value.

ANECDOTE

Typist Versus Word Processor Example

He uses the typist and word-processor story to show how a tool can erase the value of a skill.
Good typing mattered until editing costs collapsed with word processors.

INSIGHT

Above Versus Below The Algorithm

The decisive divide will be those above the algorithm versus below it; owners of learning systems capture capital-like returns.
Workers whose skills are absorbed into algorithms become commoditised labour.

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Sangeet Choudary is the best-selling co-author of Platform Revolution and the author of the new book Reshuffle. He has advised CEOs at more than 40 Fortune 500 companies and is currently a Senior Fellow at the University of California, Berkeley.

The SaaS crash isn’t cyclical — it’s structural. AI is eroding seat-based pricing, collapsing product boundaries, and destroying the old logic of defensible SaaS moats.
AI doesn’t just change tasks — it rewrites value. Focusing on “automation vs augmentation” misses the point; AI reshapes whole systems of work, competition, and advantage.
Translation is the real superpower of AI. By collapsing the cost of translating across silos, AI enables coordination without standards, APIs, or shared workflows.
Moats built on customer understanding are dissolving. When users can no-code, extend, or bypass tools — and adjacent platforms can invade workflows — retention logic breaks.
The decisive divide is above vs below the algorithm. Those who design and own learning systems capture capital-like returns; those whose knowledge is absorbed become commoditised labour.
Platforms don’t just intermediate — they absorb learning. Campaign managers, drivers, and operators trained the systems that ultimately priced them out.
Firms must be re-designed, not AI-enabled. Automating existing workflows locks in obsolete constraints; the real prize is questioning why the workflow exists at all.
The future firm is modular — but selectively integrated. AI makes context exportable, pushing work outside the firm, while pulling learning-critical activities tightly inside.
In physical AI, learning beats scale. The advantage isn’t owning assets — it’s owning the feedback loops that reveal how complex systems actually behave (the Tesla lesson).
Nations compete on where learning compounds. The US bets on intelligence concentration, China on model commoditisation plus execution, India on open standards — while Europe risks playing defence in a power game.

He leaves us with a lingering question: are you above or below the algorithm?

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