The Useful AI Product: Turn Repetitive Work into Software People Actually Need

Most AI products begin with a chatbot because chatbots are easy to demonstrate. The user types a request, the model produces an answer, and the real work remains unfinished.

The Useful AI Product presents a different method. Start with a repeated task. Study how people currently perform it. Identify the records, decisions, rules, exceptions, permissions, and handoffs involved. Then build the smallest system that produces a result people can actually use.

This book explains how to:

• identify repeated work worth turning into software
• observe real processes instead of inventing ideal workflows
• map roles, records, relationships, states, events, actions, and permissions
• separate exact software rules from uncertain AI interpretation
• decide whether a language or vision model belongs in the product
• choose forms, uploads, tables, queues, buttons, and background processes instead of defaulting to chat
• define structured outputs with source references and failure behavior
• test the service manually before investing in a full application
• build reliable capture, validation, transformation, review, and routing pipelines
• create test cases from real failures and corrections
• design clear human review and escalation paths
• protect customer data and restrict automated actions
• calculate operating costs, support requirements, and sustainable prices
• sell a narrow result rather than a vague promise about artificial intelligence
• maintain the product as models, vendors, prices, and capabilities change

The book also includes twenty product patterns for underserved work, practical worksheets, evaluation scorecards, research prompts, and a thirty-day sprint for testing an idea before committing to a full build.

The goal is not to add AI everywhere. The goal is to remove repeated work, reduce mistakes, preserve human control, and create software that earns its place in a real process.