Back to Lenny's Podcast

AI’s third era: the rise of persistent AI coworkers | Tara Seshan (OpenAI’s product lead)

Lenny's PodcastAugust 30, 20261h 21m
Topics68
The Three Eras of AI Products0:00Building Strategy in a Fast-Moving Market0:30Adapting as a Product Manager0:30Surprises Working at OpenAI1:00OpenAI's Open Culture4:30Static vs Dynamic Markets6:30The Shift from Theoretical to Empirical8:00The Core PM Role That Has Not Changed9:30The Future of Work: Steering vs Rowing11:00The Human Element as Competitive Advantage13:00The Process of Figuring Out What a Product Should Be15:00The Next Shift in How Knowledge Workers Operate16:00The Slow Takeoff Scenario18:00The Need for Ambition20:30The New Capability Horizon23:28Building New Mental Habits24:02Elevating Ambition as Product Management24:30OpenAI's Internal Memes25:00Additional Cultural Memes26:31Building for Future Model Capabilities27:00Research-Product Alignment28:31The Worst Models Will Ever Be29:00ChatGPT App Interface and Modes29:31Current Mode Distinctions30:30Work Mode Capabilities31:00Work Mode vs Codex32:00Meeting Users Where They Are33:01Balancing Scale and Innovation34:01Three Eras of AI Products35:00Done is Better Than Perfect36:00Iteration Model37:30What Shifted Codex's Trajectory39:30The Operation Hasn't Changed41:00Role Fluidity and Accountability42:00The Craft Question44:30Where Human Brains Remain Valuable46:01Human Value in Expression47:01The Human Elements That Remain Essential47:23The Capability-Usage Gap48:30Building Sites with AI49:01How Sites Work50:30The Visualize Feature52:00Two Types of Writing at Work53:00The Brief Process55:00Evolution from Docs to Prototypes56:00Getting Feedback on Documents57:30Avoiding AI Brain Rot58:32The Start and End Principle59:31Experience at Sutter Hill Ventures1:00:30Reticle Tool1:02:00Product Marketing Fit1:03:00Knowledge Work vs Coding1:05:03Context Requirements1:07:00Book Recommendations1:08:00Anna Karenina1:09:00Slow Reading Approach1:10:30The Odyssey as AI Commentary1:11:13Rashomon and Creative Constraints1:11:31Favorite AI Products1:13:30GATS Social Network1:14:31Podcast App Feature1:15:00Tony Morrison's Work Philosophy1:15:31Teal Fellowship Experience1:16:30Ari Weinstein Connection1:17:01Teal Fellowship Program Details1:17:30Dylan Field1:19:02Product Recommendations1:19:30Mobile Work Feature1:20:00
In a Nutshell

Tara Seshan describes AI's third era: persistent AI coworkers that act as teammates, handling work at higher abstraction levels while humans provide steering and direction. The key to building in this fast-moving market is staying 2-3 months ahead of model capabilities—neither building for current limits nor a year out—and operating through rapid empirical testing rather than theoretical planning. The competitive advantage shifts to human ambition, opinionation, and expression, as the gap between what AI enables and what people actually attempt is the biggest constraint on progress.

AI-Generated Notes

These notes were generated by AI and may contain inaccuracies.

The first era of AI products was chat. The second era involves products working with agents. The third era, which may come soon, is working with a persistent co-worker who is able to get things done with you.

There is an overhang between what AI is capable of and what we are actually doing with it. It is hard to understand what will emerge in the future. You fail if you build for where the models are now. You fail if you build for where you think the models will be in a year. Both outcomes are equally wrong. The only way to build is 2 to 3 months ahead.

Being prolific and empirical is way more important than being academic or theoretical. Rather than writing out some long reasoning doc, the approach is to get to something that can be tried out and tested with users as fast as possible. It feels like not only are we able to be more ambitious, we almost need to be more ambitious, which is not natural for a lot of people.

Elevating others' ambitions or reminding them of what is possible is a huge part of the product management role.

Tara Seshan has been at OpenAI for just about a year. In most places this would be a very short amount of time, but in AI time it is like a lifetime.

Many things about working at OpenAI felt familiar because she had worked at other high growth, high talent, high intensity, hyperscaling mode places before. The part that actually felt most surprising is that OpenAI is not founder-led in the traditional sense. Everyone inside the company, especially in their area, is in essence kind of a founder to some extent.

Sign in to read the full notes

Get access to AI-generated notes, topic timestamps, and more.