Tara Seshan

@tara-seshan · 28 positions · 0 changes of mind

Product lead for ChatGPT Work at OpenAI; previously one of the first five product managers at Stripe, head of product at Watershed, and a Thiel Fellow.

Everything they publish, on ppll ↗

Tara Seshan did not write this page.

We collected these quotes from things they published elsewhere, and every quote links to where it was said. They have no account here and have not endorsed this site. Quotes are word for word; the short line under each one is our own restatement, not their wording. Their own site. Is this you? Claim it or ask us to remove it. Or tell us what is wrong here.

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Our reading
However much theorizing is done before shipping, nothing compares to the evidence of users trying a product and iterating from there.

Their wordsthere's a lot of like theorizing that one can do before you ship something but nothing compares to like the actual empirical evidence of seeing users try it, use it, and then iterating from there.
spoken · machine transcript hear it at 1:27 · all korrents from this recording
↗Stop planning for 2027: how OpenAI builds product 90 days at a time | Tara Sesha and Nan Yu (OpenAI) (Lenny & Friends Summit, San Francisco, 10 September 2026)youtube.com 1st of 18 in this recording
Our reading
AI products should probably aim at where the models will be in two to three months, neither anchored in the present nor futuristic and unusable.

Their wordsprobably most importantly in this era is this aiming for 2 to 3 months of like where the models will be rather than being overly anchored in the present or being overly like futuristic and unusable.
spoken · machine transcript hear it at 4:41 · all korrents from this recording
↗Stop planning for 2027: how OpenAI builds product 90 days at a time | Tara Sesha and Nan Yu (OpenAI) (Lenny & Friends Summit, San Francisco, 10 September 2026)youtube.com 2nd of 18 in this recording
Our reading
Whether to build one agent or many depends far more on the use case and its practical considerations than on philosophy.

Their wordsthere there are philosophical things one could have and opine on in this topic but to me there are just so many practical product considerations like the use case matters so much in deciding this.
spoken · machine transcript hear it at 10:23 · all korrents from this recording
↗Stop planning for 2027: how OpenAI builds product 90 days at a time | Tara Sesha and Nan Yu (OpenAI) (Lenny & Friends Summit, San Francisco, 10 September 2026)youtube.com 6th of 18 in this recording
Our reading
Beyond user empathy and systems thinking, building agents needs a relentlessness to try things and keep iterating.

Their wordsthe third thing that you just really need in addition to user empathy and systems thinking is like a relentlessness to like try it out and keep iterating
spoken · machine transcript hear it at 12:11 · all korrents from this recording
↗Stop planning for 2027: how OpenAI builds product 90 days at a time | Tara Sesha and Nan Yu (OpenAI) (Lenny & Friends Summit, San Francisco, 10 September 2026)youtube.com 8th of 18 in this recording
Our reading
For a product person working with AI research, learning to write good evals is the most important thing.

Their wordslearning how to write good evals and writing evals as much as possible is like the most important thing
spoken · machine transcript hear it at 18:46 · all korrents from this recording
↗Stop planning for 2027: how OpenAI builds product 90 days at a time | Tara Sesha and Nan Yu (OpenAI) (Lenny & Friends Summit, San Francisco, 10 September 2026)youtube.com 9th of 18 in this recording
Our reading
Building exactly for today means being left behind; the ideal horizon is two to three months.

Their wordsand then at the same time if you build exactly for today you're going to get left behind. So it's like I constantly repeat this but it's like two to three months out.
spoken · machine transcript hear it at 20:22 · all korrents from this recording
↗Stop planning for 2027: how OpenAI builds product 90 days at a time | Tara Sesha and Nan Yu (OpenAI) (Lenny & Friends Summit, San Francisco, 10 September 2026)youtube.com 10th of 18 in this recording
Our reading
How far ahead to plan depends on the pace of the market a business is in; in some markets it may be appropriate to plan many months out.

Their wordsmaybe it is appropriate to plan you know many many months out but I think it involves understanding like the pace of the market you're in
spoken · machine transcript hear it at 21:22 · all korrents from this recording
↗Stop planning for 2027: how OpenAI builds product 90 days at a time | Tara Sesha and Nan Yu (OpenAI) (Lenny & Friends Summit, San Francisco, 10 September 2026)youtube.com 11th of 18 in this recording
Our reading
When an agent acts semi-autonomously, a user must be able to predict at any point what a feature will probably do.

Their wordsnow if the you know agent is doing things semi-autonomously like you actually really need to make sure that at any given point a user can like predict what is probably going to happen with a feature or a primitive that you're introducing.
spoken · machine transcript hear it at 22:58 · all korrents from this recording
↗Stop planning for 2027: how OpenAI builds product 90 days at a time | Tara Sesha and Nan Yu (OpenAI) (Lenny & Friends Summit, San Francisco, 10 September 2026)youtube.com 13th of 18 in this recording
Our reading
The usual PM craft still applies, but testing things empirically and moving faster matter more than ever.

Their wordsall the usual stuff still applies except the importance of testing things empirically and moving faster has only increased.
spoken · machine transcript hear it at 23:19 · all korrents from this recording
↗Stop planning for 2027: how OpenAI builds product 90 days at a time | Tara Sesha and Nan Yu (OpenAI) (Lenny & Friends Summit, San Francisco, 10 September 2026)youtube.com 14th of 18 in this recording
Our reading
Product people should be in direct contact with their users.

Their wordsof course you should be in direct contact with your users.
spoken · machine transcript hear it at 24:47 · all korrents from this recording
↗Stop planning for 2027: how OpenAI builds product 90 days at a time | Tara Sesha and Nan Yu (OpenAI) (Lenny & Friends Summit, San Francisco, 10 September 2026)youtube.com 15th of 18 in this recording
Our reading
Voice is such an intuitive interface for so many people that it changes the game.

Their wordsthe existence of voice like changed the game like it is such an intuitive interface for so many people.
spoken · machine transcript hear it at 27:16 · all korrents from this recording
↗Stop planning for 2027: how OpenAI builds product 90 days at a time | Tara Sesha and Nan Yu (OpenAI) (Lenny & Friends Summit, San Francisco, 10 September 2026)youtube.com 17th of 18 in this recording
11 days earlier
Our reading
In a fast-changing AI market, being prolific and empirical matters far more than being academic or theoretical.

Their wordsAnd so actually being prolific and being um more like empirical is way more important than being um like maybe more academic or theoretical.
spoken · machine transcript hear it at 0:07:48 · all korrents from this recording
↗AI’s third era: the rise of persistent AI coworkers | Tara Seshan (OpenAI’s product lead)youtube.com 1st of 17 in this recording
Our reading
The most important thinking a product manager does is defining the core hypothesis as pointedly as possible.

product management

Their wordsAnd what that means is the thinking you need to do is being as pointed as possible about what your core hypothesis is. And that hypothesis definition is the most important thing.
spoken · machine transcript hear it at 0:08:38 · all korrents from this recording
↗AI’s third era: the rise of persistent AI coworkers | Tara Seshan (OpenAI’s product lead)youtube.com 2nd of 17 in this recording
Our reading
The core of product management has always been finding the most essential question to ask about a product.

product management

Their wordsBut the core of it has always been about what is like the most essential question you need to ask about your product. Like what is the thing that will determine whether your product works or doesn't work?
spoken · machine transcript hear it at 0:09:27 · all korrents from this recording
↗AI’s third era: the rise of persistent AI coworkers | Tara Seshan (OpenAI’s product lead)youtube.com 3rd of 17 in this recording
Our reading
Work will increasingly look like steering rather than rowing, with agents doing the rowing.

Their wordsI do think that increasingly the future of work will look more like steering than rowing in the sense that there will be agents that you'll you'll be able to work with that do a lot of the rowing and your role increasingly becomes steering the ship in the right direction and pointing it in the right direction.
spoken · machine transcript hear it at 0:11:22 · all korrents from this recording
↗AI’s third era: the rise of persistent AI coworkers | Tara Seshan (OpenAI’s product lead)youtube.com 4th of 17 in this recording
Our reading
People may underrate the power of intuition and of deciding what they want the future to be.

Their wordsI think sometimes that we underrate like that power of like intuition or even um sort of like positive like determinism of what we want the future to be like.
spoken · machine transcript hear it at 0:12:20 · all korrents from this recording
↗AI’s third era: the rise of persistent AI coworkers | Tara Seshan (OpenAI’s product lead)youtube.com 5th of 17 in this recording
Our reading
Working with agents should ideally feel like a multiplayer game, with people steering their agents together.

Their wordsIdeally, work feels like a multiplayer game where all of us together are getting stuff done, steering our agents as our agents continue to take care of more and more of those like rowing tactical tasks.
spoken · machine transcript hear it at 0:18:03 · all korrents from this recording
↗AI’s third era: the rise of persistent AI coworkers | Tara Seshan (OpenAI’s product lead)youtube.com 6th of 17 in this recording
Our reading
Prosaic work on data access and cloud infrastructure matters, in some ways, as much as intelligence for making agents effective.

infrastructure

Their wordsbut a lot of it is also just really tactical like data access like cloud infrastructure and reliability pieces that feel um yeah, they feel much more prosaic than some of the the broader intelligence questions, but matter in some ways just as much for end effectiveness.
spoken · machine transcript hear it at 0:19:47 · all korrents from this recording
↗AI’s third era: the rise of persistent AI coworkers | Tara Seshan (OpenAI’s product lead)youtube.com 7th of 17 in this recording
Our reading
With AI tools, ambitions are no longer limited by what a person can execute or communicate themselves.

Their wordsYour ambitions are no longer limited by like what you're capable of executing yourself, what you're capable of communicating.
spoken · machine transcript hear it at 0:22:36 · all korrents from this recording
↗AI’s third era: the rise of persistent AI coworkers | Tara Seshan (OpenAI’s product lead)youtube.com 8th of 17 in this recording
Our reading
Part of a product manager's job now is to elevate everyone's ambitions.

product management

Their wordsUm, part of your job now is to elevate everyone's ambitions and say, "Actually, isn't the possibility ceiling meaningfully higher?"
spoken · machine transcript hear it at 0:24:43 · all korrents from this recording
↗AI’s third era: the rise of persistent AI coworkers | Tara Seshan (OpenAI’s product lead)youtube.com 9th of 17 in this recording
Our reading
Building for where AI models are now and building for where they will be in a year are equally wrong.

Their wordsYou 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. Like both outcomes are equally wrong.
spoken · machine transcript hear it at 0:27:25 · all korrents from this recording
↗AI’s third era: the rise of persistent AI coworkers | Tara Seshan (OpenAI’s product lead)youtube.com 10th of 17 in this recording
Our reading
When there is real conviction that a product is transformative, getting it into users' hands is far better than waiting until it is perfect.

Their wordsBut I think what's been really compelling and interesting about this era and this product experience has been getting the product in the hands of users when you have so much conviction that hey it's transformative like is way better than perfect and that urgency and that uh introduction of that product is is so important.
spoken · machine transcript hear it at 0:36:43 · all korrents from this recording
↗AI’s third era: the rise of persistent AI coworkers | Tara Seshan (OpenAI’s product lead)youtube.com 11th of 17 in this recording
Our reading
Humans will continue to be most valuable as the ones accountable for an outcome.

Their wordsI think humans will continue to be most valuable as a certainly as a um like an entity of accountability.
spoken · machine transcript hear it at 0:46:18 · all korrents from this recording
↗AI’s third era: the rise of persistent AI coworkers | Tara Seshan (OpenAI’s product lead)youtube.com 12th of 17 in this recording
Our reading
The human brain will remain valuable in how people care for and relate to one another.

Their wordsUm I also think the human brain continues to be valuable in like how we care for each other and relate to one another.
spoken · machine transcript hear it at 0:47:31 · all korrents from this recording
↗AI’s third era: the rise of persistent AI coworkers | Tara Seshan (OpenAI’s product lead)youtube.com 13th of 17 in this recording
Our reading
AI should be used as much as possible for writing as reporting, but should not replace writing as thinking.

Their wordsI think you should use the models as much as possible for writing as reporting and in as much as you think with writing as I really do and I think a lot of people do you should not use it you shouldn't replace your thinking with it
spoken · machine transcript hear it at 0:54:24 · all korrents from this recording
↗AI’s third era: the rise of persistent AI coworkers | Tara Seshan (OpenAI’s product lead)youtube.com 14th of 17 in this recording
Our reading
Something people can try, or results from a test, communicates a direction far better than a document.

Their wordsI have like results where we tried this, we ran an AB, here's like the results. This is why I think we should like go in this direction. That is a way better communication tool than like the the doc itself.
spoken · machine transcript hear it at 0:56:39 · all korrents from this recording
↗AI’s third era: the rise of persistent AI coworkers | Tara Seshan (OpenAI’s product lead)youtube.com 15th of 17 in this recording
Our reading
Unlike code, an agent's knowledge work cannot be judged by its output alone; the process, inputs and reasoning have to be examined too.

Their wordsBut knowledge work is different in that I can't simply look at the deck in the end and see the numbers. Oh, it's like 90% success or whatever in the deck and actually believe that. I really need to think about the process and the inputs and the reasoning and how it went along the way.
spoken · machine transcript hear it at 1:05:35 · all korrents from this recording
↗AI’s third era: the rise of persistent AI coworkers | Tara Seshan (OpenAI’s product lead)youtube.com 16th of 17 in this recording
Our reading
People should make software that exactly meets their own and their friends' needs.

Their wordsIt is exactly what I think the future should be which is people should make software that exactly meets their and their friends needs.
spoken · machine transcript hear it at 1:14:18 · all korrents from this recording
↗AI’s third era: the rise of persistent AI coworkers | Tara Seshan (OpenAI’s product lead)youtube.com 17th of 17 in this recording

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The shading behind a date fills in quarters: said within a month, six months, a year, or three years. Empty means more than three years ago. It says when, not whether it still holds — a change of mind is marked on the claim itself.

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