YC Root Access

Emergent: The AI App Builder for Everyone

Emergent is building the next generation of app development, where anyone can create software with natural language. The platform lets users describe what they want, and Emergent’s AI builds it — from web apps to automations to tools used by millions. In this interview with YC Partner Nicolas Dessaigne, co-founders Mukhund and Madhav Jha share how they scaled to $15M ARR in just three months, what inspired them to make app creation accessible to everyone, and how they see a future where building software is as easy as having an idea. Chapters: 00:00 – The AI Reset: A New Era of Building 00:36 – What Emergent Is & How It Works 01:02 – $15M ARR in 3 Months 03:10 – Building Together as Twin Brothers 04:46 – From Enterprise Agents to the App Builder 07:06 – How Emergent Builds Apps from Prompts 10:02 – Builders from All Walks of Life 17:14 – Raising $23M and Scaling the Team 19:54 – The Billion Builders Future

MUMukhundguestNDNicolas DessaignehostMJMadhav Jhaguest

Oct 16, 2025·21m·Watch on YouTube ↗

📖 CHAPTERS

1. 1

   AI as a “big reset” for the next 20 years

   Mukund frames AI as a generational platform shift, comparing the current moment to “Bitcoin at $1.” The conversation sets an ambitious tone: now is the time to take risks, commit deeply, and build with conviction.

2. 2

   What Emergent is: prompt-to-production app building for non-coders

   The founders explain Emergent as an AI app builder that lets anyone create production-ready apps via prompts—without programming. They emphasize that outputs are meant to be launchable, not just demos.

3. 3

   Explosive early traction: $15M ARR, 1.7M users, 2.5M+ apps created

   They share rapid growth metrics just three months after launch and discuss deployment behavior. While not all apps are deployed through Emergent, a meaningful fraction reach production.

4. 4

   Twin founders’ background and why building together works

   Mukund and Madhav describe their paths through academia and major tech/startups, and how their twin relationship affects execution. They highlight high trust, shared context, and constant idea iteration as an advantage.

5. 5

   YC journey and the pivot: from testing agents to a general coding agent

   Emergent didn’t start as an app builder; it began as an idea for AI testing agents for web/mobile apps. As they built, they realized the broader “general coding agent” problem was more compelling and enduring.

6. 6

   Enterprise phase: benchmarking, long-horizon agents, and tight feedback loops

   They describe building a top-tier coding agent early on, including strong SWE-bench performance. Key learning: to make agents reliable, you need tight feedback loops and infrastructure designed around agent execution.

7. 7

   Why consumer app-building won: faster loops and founders’ product DNA

   After experiencing slow enterprise iteration, they leaned into consumer—aligned with their prior experience. They were already using Emergent internally to build apps, which made the consumer app-builder direction feel obvious.

8. 8

   How Emergent builds apps from prompts: routing, dev boxes, and integrated stack

   They walk through what happens after a user hits enter: Emergent clarifies intent via conversation, routes work to the right agents, and spins up a cloud dev environment. The agent writes code, installs dependencies, and gets automated lint/testing feedback within a controlled environment.

9. 9

   Differentiation: multi-agent architecture for production readiness (not just prototypes)

   Emergent positions itself against “vibe coding” tools that stop at prototypes. Their approach uses specialized agents—design, testing, security, deployment—and avoids third-party dependency for core infrastructure to improve reliability and shipping speed.

10. 10

    Complexity limits and where it’s headed

    They discuss practical ceilings in today’s AI-generated codebases and why those limits should rise. Emergent claims higher current complexity support than many competitors, while acknowledging large apps remain challenging.

11. 11

    Who’s building: entrepreneurs, small businesses, and “power users” with real ROI

    User stories illustrate that builders come from diverse backgrounds—microbiologists, jewelry store owners, gardeners, filmmakers—often solving personal or business-critical problems. They distinguish casual “tourists” from serious builders and track retention primarily among power users.

12. 12

    Go-to-market playbook: invite codes, influencer loops, and tracking conversion

    They explain a methodical launch approach in a crowded market: a small alpha, then invite-only access via influencers with trackable codes. They studied platform algorithms (TikTok/Twitter/Instagram), iterated on content, and used conversion data to refine their strategy.

13. 13

    Series A and scaling: $23M round, tiny team, and quality-focused roadmap

    They describe closing a $23M Series A quickly after launch (with strong early revenue signals) and explain how they’ll use capital. Priorities include hiring, agent research, platform quality, and surfacing under-marketed features like mobile and custom agents.

14. 14

    The “billion builders” future + parting advice for founders

    They predict a surge of new builders and startups as AI lowers the barrier to creating software. The episode closes with advice to embrace the AI reset, build boldly, and leverage tools like Emergent to accelerate idea-to-company execution.