AppGenie
"Cursor for Product Managers"
An AI-native product development platform that facilitates the creation and maintenance of quality software.
Ian Lancaster · Founder · ian@appgenie.ai · YC S26 Applicant · Pre-Seed
The Problem
The largest cost in the technology industry is developers — and building software is still a game of telephone.
The Handoff Chain
Product owners define. Designers reinterpret. Engineers reinterpret again. QA guesses. At every handoff, intent is lost — and the cost is rework, regressions, and eroded trust.
Fragmented Tooling
Product lives in Jira. Design in Figma. Code in VS Code. Tests in CI. No single system holds a structured, testable definition of what the product actually does.
AI Agents Without a Source of Truth
AI coding agents are entering this workflow — powerful builders with no structured definition to build from and no reliable way to validate their output.
The Insight
Code is being commoditized
Cursor, Claude Code, Codex, and Devin already produce production-quality code. Tens of billions are flowing into solving implementation — and that race has a finish line.
The real bottleneck
What becomes dramatically more valuable as code gets cheap is the ability to precisely define what should be built and reliably prove it was built correctly. Almost nothing is flowing into this layer.

AppGenie owns the definition and validation layer — the bottleneck that remains when AI writes all the code.
What AppGenie Does
Define what your product does in structured, plain-language detail — and automatically compile those definitions into executable end-to-end tests.
1
Point A — Define
A living model of every feature, every user flow, every scenario — in a format AI agents can read and act on. Not a ticket. Not a PRD.
2
AI Agents — Build
Coding agents read what to build from AppGenie, implement it, validate against generated tests, and self-heal when something breaks. No developer required.
3
Point B — Validate
Self-healing Playwright tests generated directly from scenario definitions. Run during development, in CI, and continuously in production.
What's Built
Working Product
Built solo over the past year. After researching 30+ competitors — no other product connects structured product definitions to executable E2E tests.
Feature Hierarchy
Structured user stories, UX flows, scenarios, and test instructions with automatic Gherkin BDD compilation.
Self-Healing Tests
Playwright test generation and execution via MCP server connecting coding agents to feature definitions.
Hybrid App
Web + Electron desktop app with local-first architecture, real-time multi-agent sync, and enterprise multi-tenant infrastructure.
Genie Assistant
Scaffolds features from natural language conversation. The hardest piece to build — and the most defensible.
Where This Goes
A platform where a product leader describes what they want — and tested, validated, working software comes out the other end.
Collect
Feedback, telemetry, and analytics from Pendo, Datadog, and idea portals.
Decide
AI-assisted prioritization based on real user data — not intuition.
Define
Features and scenarios compiled into structured specs and executable tests. This is what exists today.
Build
AppGenie dispatches work to AI coding agents. No tickets. No sprints. No standups.
Validate
Self-healing tests run continuously. Regressions caught automatically.
Document
Living documentation generated automatically — always current.
Why Now
Code is Being Commoditized
Cursor, Claude Code, and Codex are production-capable. The cost of writing code is collapsing. The cost of knowing what to write is not.
The Developer Bottleneck Is Breaking
As AI takes over code translation, the entire cost structure of software development shifts — value accrues to whoever controls definition and validation.
Serious Capital Validates the Thesis
Tessl (Guy Podjarny, Snyk founder) raised $125M at $750M for spec-driven dev. Amazon launched Kiro. The market believes — but every player approaches from the developer side.
YC Is Asking for This Exact Product
"Imagine a tool where you… ask 'what should we build next?' and get the outline of a new feature… The tool would also propose specific changes to your product's UI, data model, and workflows, and would break down the development tasks so they could be handled by your favorite coding agent." — Andrew Miklas, YC Partner
Market
The addressable opportunity isn't just dev tools — it's the cost of building software itself. Worldwide IT spending reaches $6.15 trillion in 2026, with 28 million professional software developers globally and engineering labor as the single largest line item.
Dev Tools
$7.6B → $29.6B by 2035 (14.5% CAGR)
Test Automation
$20.6B → $84.2B by 2034 (16.8% CAGR)
Product Management Software
~$5.9B, 7–10% CAGR
The AI-enabled testing tools segment alone is projected to grow from $687M (2025) to $3.8B by 2035.

73% of QA professionals cite AI-powered test generation as their top priority.
Competition
Billions flow into "how to build." Almost nothing flows into "what to build."

AppGenie is the only platform connecting the full pipeline: product intent → structured definition → UX flow modeling → executable BDD specs → self-healing E2E tests → coding agent orchestration via MCP.
Business Model
Free
Limited features, scenarios, and test runs — enough to evaluate
Pro
$20–30/editor/month — full platform access, AI credits for Genie Assistant and test generation
Team
$30–50/editor/month — collaboration, shared AI credits, MCP server access, agent orchestration
Enterprise
Custom — SSO, RLS, dedicated support, volume AI credits
Only editors (PMs, QA leads) are paid seats. Developers, stakeholders, and AI agents are free — removing friction from the highest-value integration point.
AI Consumption Pricing
Token-intensive operations (Genie Assistant, test generation, test healing, agent orchestration) draw from per-seat credits; additional credits purchased on demand.
Growth Motion
Land with PM team ($30–50/editor/mo) → expand via test automation → full org adoption as AppGenie becomes the system of record.
Why This Works
PM tools price at $10–20/seat; test automation at $250–8,000+/month. AppGenie enters at PM-tool pricing and grows revenue per account naturally as usage expands.
Founder
Ian Lancaster
Founder-Market Fit
Joined BuildOps at ~$500K ARR, led frontend engineering through growth to a $1B+ valuation. Lived the product-engineering communication breakdown for 8+ years. Built AppGenie to solve the problem I couldn't solve there.
Technical Depth
Principal Software Engineer, 8+ years. Built the entire AppGenie MVP solo — monorepo, local-first database, AI agents, hybrid web/desktop app.
Education
BS Business Administration & Marketing, CU Denver. Turing School of Software & Design.
Seeking a business co-founder to own GTM, fundraising, and operations.
The Ask
Raising a pre-seed round to deploy AppGenie to market, onboard design partners, and hire.
The endgame: an application that generates the applications it describes. The company that owns the definition and validation layer becomes the control plane for how all software gets made.
Foundation Built
Working product, solo-built, no comparable competitor.
Market Shifting
The largest cost in tech is about to be disrupted by AI.
Get in Touch
ian@appgenie.ai
linkedin.com/in/ianclancaster
Sources
  1. Gartner, "Worldwide IT Spending Forecast," February 2026
  1. Statista, "Global Software Developer Population," 2025
  1. Business Research Insights, "Software Development Tools Market Size," 2025
  1. Fortune Business Insights, "Automation Testing Market Size," 2025
  1. Market Research Intellect, "Product Management Software Market Size," 2024
  1. Research and Markets, "AI-Enabled Testing Tools Market," 2025