Four steps. One platform.
Goodspeed handles the entire app lifecycle. Discovery, planning, building, and growth. Here is how each step works.
Discover
Find what to build
The discovery pipeline monitors 16 real-time signal sources every week. Hacker News, Reddit, app store reviews, ProductHunt, GitHub Issues, Google Trends, and more. Raw signals get processed through a two-pass AI extraction that identifies problems people actually have and generates 2-3 solution variants per problem.
- •~1,050 signals analyzed per cycle
- •Two-pass Sonnet LLM extraction (problem identification + solution generation)
- •Evidence clustering across weekly cycles flags recurring patterns
- •Every idea scored on a transparent 100-point rubric
- •Five scoring categories: market demand, monetization, competition, technical feasibility, solo viability
Define
Plan what to build
Before any code gets written, you work with AI to define exactly what your app should be. The requirements phase generates a full product spec from the research data, then lets you refine it interactively. Architecture decisions, user stories, tech stack choices, and 12 cross-cutting features are all evaluated for your specific app.
- •Full PRD generation from research data
- •Two-pass architecture: UX-focused pass + technical pass
- •12 cross-cutting features evaluated per app (dark mode, offline, push notifications, etc.)
- •User story mapping with priority indicators
- •You review and refine everything before the build starts
Build
Generate production-ready code
The build agent starts with a battle-tested 68-file template that handles 76% of typical app code. Auth, payments, theming, analytics, offline sync. All pre-wired. The AI generates only the 24% that makes your app unique: onboarding flows, feature screens, services, and database migrations. Three to four LLM calls, not seventy.
- •246-feature template across 22 categories
- •React Native + Expo + TypeScript + Supabase
- •3-4 LLM calls (57% fewer tokens than v1)
- •Auth, payments, dark mode, offline, analytics baked in
- •Quality gates: automated checks + human review before testing
Grow
Launch and scale
Building the app is half the work. The growth engine handles the other half. App Store Optimization generates a keyword universe and optimizes every metadata field. Multi-channel outreach targets ProductHunt, Reddit, Hacker News, Indie Hackers, Twitter, and email. The social engine creates platform-native content automatically.
- •ASO: 100+ keywords, metadata optimization, category selection
- •8 outreach channels with platform-specific content
- •Automated social posting (14+ posts/week)
- •Analytics-driven iteration loop
- •Performance data feeds back into the next content cycle