# AI products are becoming living feedback loops

Markdown copy of https://realalpha.app/s/ai-products-are-becoming-living-feedback-loops/ on Real Alpha, the best minutes from long interviews with the people building AI. Cite and link the page, not this copy.

- Speaker: [Asha Sharma](https://realalpha.app/people/asha-sharma/) · Asha Sharma is chief vice president of product for Microsoft's AI platform. · Ran Microsoft's CoreAI product org and Instacart's operations before leading Xbox, after scaling Messenger at Meta.
- Host: [Lenny Rachitsky](https://realalpha.app/people/lenny-rachitsky/) · Host, Lenny's Podcast · Spent seven years at Airbnb; his product newsletter has over 1M subscribers.
- Show: Lenny's Podcast
- Episode: [How 80,000 companies build with AI: Products as organisms and the death of org charts | Asha Sharma](https://realalpha.app/v/J9UWaltU-7Q/), Aug 28, 2025
- Moment: 4:20 to 9:14 of the episode (5 min), playing on https://realalpha.app/s/ai-products-are-becoming-living-feedback-loops/; the episode from there: https://realalpha.app/v/J9UWaltU-7Q/?t=260

## Quote

> “Because these models are so effective at this point, you want to start to tune them to **certain types of outcomes**, whether it's price or performance or quality.”
> — [Asha Sharma](https://realalpha.app/people/asha-sharma/) at [5:47](https://realalpha.app/v/J9UWaltU-7Q/?t=347) · Lenny's Podcast

## Takeaways

1. Products need a metabolism for data, rewards and outcomes.
2. Tune models toward outcomes such as price, performance or quality.
3. Usage data and synthetic data can both support iteration.

## About this segment

Asha Sharma argues AI products should adapt through data, reward design and testing rather than ship as static features. That makes the feedback loop a potential source of company IP.

From “How 80,000 companies build with AI: Products as organisms and the death of org charts | Asha Sharma”, Aug 28, 2025. [Watch the full episode](https://realalpha.app/v/J9UWaltU-7Q/)

## Transcript

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

[4:25](https://realalpha.app/v/J9UWaltU-7Q/?t=265) I want to start with something that we were chatting about before this that I've never heard about as a concept that I think is going to be really helpful for people to think about, which is this concept you have that we're moving from product as artifact to product as organism. Talk about what that means and what people need to understand here. It's been a pretty interesting shift, especially over the last year or so. Because when I got to Microsoft, it was kind of right after OpenAI and the large foundation models happened. And then immediately after there was this explosion of models, proprietary open frontier models that were pushing the frontier curve.

[5:07](https://realalpha.app/v/J9UWaltU-7Q/?t=307) And so they were both more efficient and then we started to see domain level expertise in a bunch of them. And then, you know, even more recently, models now can, you know, tool call and they can function call and they can take action. And I think that's just giving way to a new type of products that are starting to see some success. And so all of a sudden, products aren't just like these static artifacts that we start to ship. That's not just like, hey, come up with an idea or an insight, go solve a problem, ship it into the world, maybe make it a little bit better and then have a dashboard.

[5:38](https://realalpha.app/v/J9UWaltU-7Q/?t=338) all of a sudden, the whole KPI is what is the metabolism of a product team to be able to ingest data and then digest the rewards model and then create some sort of outcome? Because these models are so effective at this point, you want to start to tune them to certain types of outcomes, whether it's price or performance or quality. And so it's pretty exciting because all of a sudden, These are these living organisms that just get better with the more interactions that happen.

[6:09](https://realalpha.app/v/J9UWaltU-7Q/?t=369) And in many ways, I think this is the new IP of every single company. And it's a completely different way to build product and even think about, you know, products that think and live and learn, which is kind of exciting. So when I hear this, what I'm thinking about is when I had Michael Terrell on the podcast, the Cursor CEO. He talked a lot about how their big mode is the data that they capture from people using Cursor, selecting, accepting certain suggestions, not accepting other suggestions.

[6:33](https://realalpha.app/v/J9UWaltU-7Q/?t=393) is that what you're talking about here just like the proprietary data that companies gather from people using their product or is there something beyond that even i think why we're seeing like the rise of post-training happen is just that the the models themselves like are so powerful as of this year nathan lambert uh did this study that i thought was pretty interesting of all the top leaderboards and it showed that you know once a model hits 30 billion parameters the capex to actually train a model and put you know billions of tokens into a kind of pre-run kind of doesn't economically make sense and you can kind of start to optimize on the loop and so yeah in many ways I think you can I think using your own data is the best way to do that but you can synthetically generate data you have to come up with the rewards design you have to actually roll it out you have

[7:19](https://realalpha.app/v/J9UWaltU-7Q/?t=439) to a b test it rigorously you have to find the job to be done or the use case that it makes the most sense for. And then yes, like that generates data that you can learn from. I haven't ever seen it be one loop for any sort of product. I think it's multiple tracks running in parallel that are kind of like assembly lines, if you will, and kind of producing that. And so is this kind of thesis that we're moving towards product as organism, is this basically for model companies or is this also true for, I don't know, SaaS businesses and tools and user tools?

[7:54](https://realalpha.app/v/J9UWaltU-7Q/?t=474) Look, like I think that software as a primitive is changing. And kind of the artifact inside of it is a model alongside the software components itself. And so in many ways, I think that, you know, software products will all be model forward products, if you will. This reminds me why I just had Nick Turley on the podcast that we were talking about before we started recording, head of ChatGPT. And I was asking just like, how much does ChatGPT change with GPT-5 coming out?

[8:22](https://realalpha.app/v/J9UWaltU-7Q/?t=502) And he's just like, it's the same thing. They're the same product. It's just, like, the model tells us what to do in the product of ChatGPT. And it makes me think about something else of just, like, you would think, why can't just GPT-5 build its own user interface? Just, like, as you use it, it just evolved. It's sort of what it's doing with Canvas and all these things. But, like, that's, like, another way I think about when you talk about this idea of product as organism is the product.

[8:47](https://realalpha.app/v/J9UWaltU-7Q/?t=527) The UX can shift based on how you're using it and evolve automatically without having product teams have to do anything. I 100% believe that's where the world is going and that my experience should look and feel different than yours. I mean, that's kind of been the advent of personalization, but now you can do it on the fly in the future. So I think that'll be a pretty fun world. I also think it will look different for agents and it will look different for kind of power users and new users and all