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Code Story: Insights from Startup Tech Leaders

S11 Bonus: Goutham (Gou) Rao, Neubird

Code Story: Insights from Startup Tech Leaders

Noah Labhart - Startup Founder & CTO

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

4.6216 Ratings

🗓️ 21 August 2025

⏱️ 41 minutes

🧾️ Download transcript

Summary

Goutham Rao grew up in Brooklyn, a nerd all his life. Back in the day, his Dad bought him a Commodore 64, from which he started to learn to write code in BASIC. Eventually, he attended the University of Pennsylvania to get his Masters in Computer Science. Outside of tech, he is married with 2 kids. He likes to travel, and likes to run. He used to compete in half marathons, but nowadays, he does his running as more of a mental exercise.

Goutham saw that IT telemetry logs have a lot of complexity within their data. Fast forward to today, he and his co-founders noticed the way that LLMs were processing data. They thought they could build something to interpret this data, and "clone" themselves to create something that mimics issue triage.

This is the creation story of Neubird.

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Transcript

Click on a timestamp to play from that location

0:00.0

This episode is brought to you by Paddle.

0:02.5

Don't settle for less when you can have more M-O-R with Paddle, your merchant of record.

0:08.1

Eliminate the headaches of payments, grow your revenue everywhere, and focus on what you do best, building your product.

0:14.3

Get more revenue with less hassle at paddle.com.

0:19.6

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

0:22.2

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

0:25.8

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

0:29.6

are building, and my mind is blown.

0:32.9

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

0:36.3

Built around the core of the product roadmap

0:38.0

radar, i.e. Code and Jira analysis, they are building agent orchestration across the product

0:44.0

lifecycle. Picture this. You hook up this system, same as before, i.e. integrate your repository

0:49.3

and your backlog, Jira today. From that point, S Seamus agent analyzes the code base and makes suggestions

0:55.2

as to what needs to be done next and what could improve, optimize the product. Then, if those

1:01.1

tasks are routine, the agent assigns the tasks to a coding agent, think something like Devin,

1:06.7

to complete the minutia while assigning the human-in-the-loop tasks to engineers themselves.

1:12.3

What you end up with is engineers focusing on building core competency features while AI

1:17.3

handles all the rest. If you're not salivating right now, I don't think you fully understand what

1:22.0

this means. But here's what I would suggest. Right now, their product is in a closed beta,

1:26.4

and SEMA is looking for

1:27.8

folks to sign up for their product intelligence advisory board. This gives you the opportunity

1:32.5

to use the product, give feedback, help shape the future of what's built, oh, and not to mention

...

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