mukund jha

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.

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.

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.

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.

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.