Smash Notes
Pooja Brown
Episodes
Notes
Code Story · S13 E9: Forward-Deployed AI: Moving Enterprise Pilots into Real…
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What Should a Young Founder Optimize for?
Pooja Brown tells a young founder to optimize for the learning. She says it is a really hard time to start something new, the space is messy, and founder journeys are hard. Things change so fast every week and every month, and what is true in March is not true in September.
Noah Labhart asks what she would tell a young entrepreneur on a plane who has just built the next big thing. Pooja Brown says the founder should meet enough real problems to hold a strong conviction that the product solves the problem. When she moved from founder to Tribe AI, she chose the place where she would learn the most and the fastest. Sometimes the answer is your own company. Sometimes the answer is going where p
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Why Does a Better Technology Stack Still Get Rejected?
Pooja Brown says DocuSign customers would not use a replacement platform that was much better than the last one, because she never brought them along from the old way of working.
She was hired at DocuSign to replace the platform and walked in thinking she already had it. She had a new team, a new city, and a new technology stack. What she missed was how people had worked with the old systems and the norms and processes they had built around them. When the new system arrived, the reaction was almost like organ rejection. She could not figure out why customers were not using something so much better. The gap was that she had not made the effort to bring them along. A good system, an amazing t
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How Does Tribe AI Decide What to Build Next?
Pooja Brown says Tribe AI decides what to build next from two places: how frontier models are developing, and the outcomes the businesses they work with want to achieve. Two years ago the models could help a person do the work. Today the models can do the work themselves, so the product has to change with them.
It started as a smart layer on top of a model. The person still did the job, and the model drafted or suggested. Now the agent does the job and the person checks it. Every time a person corrects the agent, Tribe AI learns from the correction, and the agent gets a little more room to work on its own. They measure the work against what actually happens in the business, asking whether t
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How Much Autonomy Should AI Agents Get?
Pooja Brown says the first trade-off, made every day, is how much autonomy to give the product on day one. Everybody wants fully autonomous versions running immediately, but a team earns the right to full autonomy one run at a time. She says they can aim to build a fully autonomous agent and still have to bring people along. The agents have to understand the work people already do, create output, create value, get corrections from the team, and then keep compounding on the corrections. The level of autonomy to give agents is a decision made constantly.
She learned the hard way while replatforming things at DocuSign. One of the big things the system did, she was responsible for transforming.
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What Is a Real Product at Tribe AI?
Pooja Brown says a real product at Tribe AI is the first use case in production that does real work. People usually do the job by hand. It has to run as a real system for real users who get value. A demo or a pilot does not qualify.
The push since she joined is to get one running as soon as Tribe AI enters an enterprise. The process needs a business owner and a clear metric. The steel thread is the path from an engineer's laptop all the way to production inside the enterprise security plane, governance, and guardrails. Proofs of concept are useful for getting people aligned and on the same page, but Pooja Brown calls them a pre-sales artifact. The Tribe AI version gets the first use case up
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What Is a Tribe AI Minimum Viable Product?
Pooja Brown says a minimum viable product at Tribe AI is a real product doing a job people usually do by hand. It is not a demo and it is not a pilot. As chief technology officer, she does not get to pick one minimum viable product. The goal is to make all projects successful.
Tribe AI has to get a minimum viable product in every enterprise the team walks into. Pooja Brown asks how to pick the first right use case in production that is actually doing real work. She also asks how to bring each minimum viable product to life with real systems and with real users who are getting value. She says the effort since she joined has been getting the minimum viable products out as quickly as the team