# AI companies need faster decisions and relentless product work

Markdown copy of https://realalpha.app/s/ai-companies-need-faster-decisions-and-relentless-product/ on Real Alpha, the best minutes from long interviews with the people building AI. Cite and link the page, not this copy.

- Speaker: [Winston Weinberg](https://realalpha.app/builders/winston-weinberg/) · Winston Weinberg is cofounder and CEO of Harvey. · Co-founded and leads Harvey, after working as an associate in securities and antitrust litigation at O'Melveny.
- Host: [Molly O'Shea](https://realalpha.app/people/molly-oshea/) · Founder, Sourcery · Ex-Upfront Ventures investor; has interviewed Alex Karp and Palmer Luckey.
- Show: Sourcery
- Episode: [Inside Harvey AI: CEO Winston Weinberg on How a 4-Year-Old Company Is Taking on the Foundation Labs](https://realalpha.app/v/ekXJCDNEmOM/), Jun 16, 2026
- Moment: 26:54 to 30:07 of the episode (3 min), playing on https://realalpha.app/s/ai-companies-need-faster-decisions-and-relentless-product/; the episode from there: https://realalpha.app/v/ekXJCDNEmOM/?t=1614

## Quote

> “you have to just assume that most things are **two way doors**.”
> — [Winston Weinberg](https://realalpha.app/builders/winston-weinberg/) at [27:19](https://realalpha.app/v/ekXJCDNEmOM/?t=1639) · Sourcery

## Takeaways

1. Treat most decisions as two-way doors.
2. Act before reaching 90% certainty, then correct course.
3. Enterprise products must keep improving for users.

## About this segment

Winston Weinberg argues teams should make reversible decisions at roughly 51% certainty and pivot quickly. Enterprise AI also demands constant product improvement, while companies increasingly sell intelligence.

From “Inside Harvey AI: CEO Winston Weinberg on How a 4-Year-Old Company Is Taking on the Foundation Labs”, Jun 16, 2026. [Watch the full episode](https://realalpha.app/v/ekXJCDNEmOM/)

## Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

[26:59](https://realalpha.app/v/ekXJCDNEmOM/?t=1619) So you started this company post-COVID. It's nearly four years old. And it was AI native from the start. So I just want to know, like, what is fundamentally different about building a company? today in the AI era versus the SaaS cycle? Yeah, I mean, I think pace is really important. And one thing with pace that I think people struggle with is like, you have to just assume that most things are two way doors.

[27:28](https://realalpha.app/v/ekXJCDNEmOM/?t=1648) And people really hate this. Like they really like to kind of like think about a decision, get to like 90% certainty and then make a decision. The reality is like, you're probably gonna have to make a bunch of decisions at like 51% certainty, which means you're being wrong, right? And can you deal with being wrong and then quickly pivoting, right? And I think you have to do that way more than you used to in the past, A.

[27:54](https://realalpha.app/v/ekXJCDNEmOM/?t=1674) B, I think there's a huge difference on enterprise, like massive difference on enterprise, which is You cannot get away with like going in a room, building some product, and then selling it, and then never improving the product over the next like XYZ years. The users matter so much. Like the alternative is Quad, ChatGPT, these other things, like those are great products too. And so I think that the product bar for enterprise is astronomically higher than it used to be, where like you 100% have to be constantly innovating.

[28:30](https://realalpha.app/v/ekXJCDNEmOM/?t=1710) and creating the best product for the end user. And I think in the past, you could kind of get away with doing some things like really long sales cycles and things like that. And token usage is compressing margins. So how are you financing 13 trillion tokens? Yeah, I mean, so there's a lot of... Okay, a couple of things. One, I think every single company is going to sell intelligence. Like that is gonna be the core of the company.

[28:59](https://realalpha.app/v/ekXJCDNEmOM/?t=1739) and so like eventually like we were selling legal intelligence we're selling legal intelligence to lawyers right but it's still like selling intelligence and so what I mean by this is like we need to get to a point where we have models that perform as well if not better than the frontier models but cost significantly less like I basically think of this as like an intelligence allocation problem where if you look at like a model you know the new models coming out it's like mythos like 5.6 all these guys right those models come out and they're incredibly expensive and they're general.

[29:29](https://realalpha.app/v/ekXJCDNEmOM/?t=1769) And if you use them across every single legal task, like maybe they do decently well, although on our benchmarks, like a lot of them fall apart, but they're insanely expensive. And so the better thing is, can you actually create models that like do diligence, do change of control review, do contracting, do these different things at the level, if not, or better than the frontier models, and they cost a hundred times less, right?

[29:52](https://realalpha.app/v/ekXJCDNEmOM/?t=1792) And so I think that every single company is going to sell tokens. and I think that they are basically going to be selling intelligence. So you'll have like the product layer and everything like that, jubble up your data, and then you're going to be selling intelligence as well.