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Code Story: Insights from Startup Tech Leaders

S11. Bonus: Harish Chandramowli, Flaire

Code Story: Insights from Startup Tech Leaders

Noah Labhart - Startup Founder & CTO

Tech News, News, Business, Technology, Entrepreneurship, Careers

4.6216 Ratings

🗓️ 2 October 2025

⏱️ 30 minutes

🧾️ Download transcript

Summary

Harish Chandramowli grew up in a small town in India. The goal was simple early on - study well, go to university, and get a job. After undergrad, he realized he can do so much more, eventually coming stateside to get his masters, and meet a ton of really smart people over the last 10 years. Outside of tech, he is a broadway show fanatic, seeing 1-2 on a regular basis. He also follows Manchester United, which can be difficult watching the lose on the regular.

Harish used to work for MongoDB, and spent some time on call and in the weeds. At that time, he realized how much data is used by a business. When he eventually supported the fashion industry, specifically the back office, he wanted to build a solution to make the lives of those back office individuals as easy as possible.

This is the creation story of Flaire.

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Transcript

Click on a timestamp to play from that location

0:00.0

Okay, guys, I got a serious update for you.

0:03.0

You heard me talk about SEMA and the Product Roadmap Radar.

0:07.0

I just caught up with Matt, who's the founder there, and he gave me the latest on what they are building.

0:11.0

And my mind is blown.

0:14.0

The team at SEMA are taking things to the next level.

0:17.0

Built around the core of the Product Roadmap Radar, i.e. code and Jira analysis, they are building

0:22.9

agent orchestration across the product lifecycle. Picture this. You hook up this system same as before,

0:28.9

i.e. integrate your repository and your backlog, Jira today. From that point, Seamus agent

0:33.7

analyzes the code base and makes suggestions as to what needs to be done next and what

0:38.9

could improve, optimize the product. Then, if those tasks are routine, the agent assigns the

0:44.8

task to a coding agent, think something like Devin, to complete the minutia while assigning

0:50.1

the human-in-the-loop tasks to engineers themselves. What you end up with is engineers focusing on building core competency features,

0:58.0

while AI handles all the rest.

1:00.0

If you're not salivating right now, I don't think you fully understand what this means.

1:04.0

But here's what I would suggest.

1:06.0

Right now, their product is in a closed beta,

1:08.0

and SEMA is looking for folks to sign up for their product intelligence

1:11.6

advisory board. This gives you the opportunity to use the product, give feedback, help shape the future

1:16.8

of what's built, oh, and not to mention additional free usage of the product potentially through the end of

1:22.5

2026. So if that fits your workflow and toolset, you need to reach out today.

1:28.8

Go to codestory.co slash next level, N-E-X-T-L-E-V-E-L, and reach out to Matt at Seema to learn more

1:37.4

and join the Product Intelligence Advisory Board.

...

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