Build or buy? A practical guide to custom software decisions
Decide whether to buy software, connect existing tools, or build a custom application by examining workflow fit, ownership, integrations, and running costs.
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Better questions.
Better software.
Practical thinking about product decisions, AI, and design. Written for the people deciding what to build—and the people who will build it.
Product strategy · 5 min read
Prototype vs. MVP: what should you build first?
Choose between a clickable prototype, technical experiment, and working MVP. A practical guide to scope, useful evidence, and production readiness.
Read the guideHow to choose an AI use case that earns its place in your business
A practical way to evaluate AI ideas for a small business: map the workflow, check the data, measure review effort, and define a useful pilot.
Read the guideRAG, search, or fine-tuning: which does your AI application need?
Understand when to use search, retrieval-augmented generation, or fine-tuning, and how evidence, permissions, and evaluation shape a grounded AI application.
Read the guideMoving an AI prototype to production: the decisions a demo cannot answer
A practical production plan for AI applications: evaluations, permissions, human review, failure recovery, observability, model changes, and cost per completed task.
Read the guideProgressive disclosure: make complex software easier to use
Use progressive disclosure and a practical design system to simplify complex applications while keeping essential information, controls, and errors visible.
Read the guideHigh-end web motion without sacrificing usability
Plan interactive graphics, WebGL, and motion with pause controls, keyboard access, reduced motion, performance limits, and useful fallbacks from the start.
Read the guideTechnical SEO belongs in your product architecture
Plan Next.js pages, crawlable content, canonicals, structured data, and private routes together so a useful product can also have a coherent search presence.
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