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mukund jha

T2 · manager / operator

Twin brother co-founder of Emergent (YC S24). Previously ran Dunzo (hyperlocal quick commerce in India, 300 engineers), dropped out of PhD, worked at Google. PhD background in deep learning.

1 call·1 name·100% bull·last heard 6 months ago·Y Combinator
track record

no scored calls yet — needs a stated position or a categorical verdict, with a matured window vs SPY

top calls

highest conviction · one per company
1sthigh conviction
$EMERGENTEmergentposition

Emergent founders detail 7M apps in 8 months, 80% non-technical users

Emergent's AI agent platform enables non-technical domain experts to build and deploy production-ready full-stack applications, unlocking a massive long-tail market of personalized software that would never be built through traditional dev shops.

Y Combinator2026-03episode →

most discussed · click a bar to filter

  • $EMERGENT

recurring themes

  • AI Economics & Business Models1
  • AI Coding Agents1
  • AI Infrastructure1
  • Enterprise AI Adoption1
  • SaaS Business Models1
1 total
$EMERGENT
Emergent
HIGHmukund jha·Y Combinator·6 months ago·AI Is Unlocking Millions Of New Builders· position
Emergent founders detail 7M apps in 8 months, 80% non-technical users
Emergent's AI agent platform enables non-technical domain experts to build and deploy production-ready full-stack applications, unlocking a massive long-tail market of personalized software that would never be built through traditional dev shops.
"In 8 months since launch, 7 million apps have been built with Emergent... today 80% of users who are on the platform are non-technical users with zero programming knowledge. And t…"
0:38
9
AI Economics & Business Modelstailwind
Jevons paradox drives expanding software market as build cost drops 100x
Lowering custom software cost from $500K to $5K unlocks a Cambrian explosion of niche applications (e.g., clinical psychology + horse riding app); non-developers become builders, roles merge (PM+engineer+designer), and total software demand grows rather than shrinking.
8
AI Coding Agentstailwind
Second-mover advantage in AI coding agents via model-agnostic platform layer
New model generations (Opus, Codex, Gemini) create opportunities to reimagine the product from a higher starting point; Emergent leverages model spikes (Opus for long-horizon, Codex for backend, Gemini for frontend) and adds verification, memory, and infra layers to deliver production-ready apps for non-technical users.
8
AI Infrastructuretailwind
Co-designed agent-infrastructure loop enables reliable deployment and continual learning
Building proprietary Kubernetes sandbox infra that serves both build-time and deploy-time eliminates environment drift; tight feedback loops between agent and infra plus cross-session memory (auto-generated skills via CI/CD) compound agent capability over time.
8
Enterprise AI Adoptiontailwind
Non-technical SMB owners are the primary adopters of AI app builders
Primary users are small/medium business owners currently running operations on email, WhatsApp, spreadsheets; they would have paid dev shops but now build themselves, creating a new category of 'personal software' and solopreneur ventures that raise funding on AI-built products.
7
SaaS Business Modelsheadwind
Agentic software disrupts traditional SaaS by enabling custom internal tools at 1% of cost
Traditional SaaS faces two headwinds: workflows consumed by agents and demand for customized software; companies like Emergent let users build tailored tools (e.g., Asana clone saving $3-4K/mo) shifting software from buy-to-build for niche workflows.