Inside $180B Co-Founder's AI Agent System
The Startup Ideas Podcast
Agents write and run code to act
Furqan shows Nebula writing Python, calling APIs, retrying on failures, and uploading files to Slides.
I sit down with Furqan Rydhan, a founding team member of Applovin and cofounder Founders Inc, as he walks me through Nebula, a Slack-like workspace where every channel holds an agent that can execute real work across the tools teams already use. We watch Nebula create and edit a Google Slides deck end-to-end, including generating an image and handling failures by retrying until it lands. Furqan shows how Nebula turns one-off work into repeatable “recipes” with scheduled triggers, like adding slides daily or publishing blog posts multiple times per day. We also talk about what “business-in-a-box” looks like in the AI era; where direction, taste, and quality loops become the edge as automation gets widely available.
Timestamps:
00:00 – Intro
01:51 –Building useful agents for real work
03:34 – Nebula: a Slack-like agent workspace
05:04 – Demo: Nebula creating a Deck with Google Slides
13:25 – The “business in a box” content dream (newsletters, affiliates, ads)
14:39 – Demo: Automate Blog Posting
15:52 – What stays valuable when everyone automates
21:23 – Agent workforce and Building quality loops
25:38 – Services and agencies: delivering work with fewer humans
28:53 – Final Thoughts
Key Points
I watch Nebula run like “cloud code for everything else,” automating real work across tools and workflows.
Agents turn one-time actions into repeatable systems via triggers and schedules.
The interface mirrors Slack because work already lives in channels, threads, and context.
Quality becomes the differentiator: critics, scoring, and iteration loops upgrade outputs over time.
Service businesses and agencies scale faster when agents handle production-heavy tasks
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Fuqan’s personal website: https://furqan.com
Nebula: https://www.nebula.gg
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