AI Tool Pipeline

A structured pipeline for building AI-native tools and integrations. Covers the full build cycle: validating the AI use case, engineering the prompts, integrating the model, designing the interface, and launching.

Most AI tools fail not because the tech is wrong, but because the use case is weak or the prompts are unreliable. This pipeline forces you to solve both before writing a line of UI code.

Stages:

1. AI Use Case (4-8 hours) — validate the use case, select the right model, assess feasibility
2. Prompt Engineering (1-2 days) — build optimized prompts, chains, and error handling
3. AI Integration (1-2 days) — API connections, fallbacks, rate limiting, cost controls
4. Interface Design (1 day) — UI patterns for AI interaction, streaming, and error states
5. AI Launch (1 day) — landing page, live demos, pricing

Includes stage definitions, model selection framework, prompt architecture templates, and launch checklist.

Proven output: Stage 1 produced a complete use case validation for a freelancer invoice follow-up tool — model recommendation (GPT-4o-mini), full prompt architecture with variables, feasibility breakdown, edge cases, and a go/no-go verdict. All in one pass.

Best for: indie hackers, AI builders, solopreneurs, and developers building their first AI-native product.