Practical notes on MVP development, AI integrations, and improving existing products.
Notes from the workbench—what we are learning while building useful products.
Build or buy for your next internal business tool? A practical framework covering when vendor software wins, when custom code earns its cost, the real maintenance burden of building, and how AI has shifted the calculation.
Read MoreHow to choose a tech stack for your MVP: the questions that actually decide it, a sensible default stack for 2026, what's worth optimizing versus what to leave boring, and the decisions that are hard to reverse later.
Read MoreCustom AI development or an off-the-shelf model API? A practical framework for deciding, what "custom" really means once you look past model training, and a path that works for most teams.
Read MoreNo-code or custom development for your MVP? A practical comparison of speed, cost, limits, lock-in, and AI needs, plus a decision checklist and the hybrid approaches that often work best.
Read MoreA realistic MVP timeline: typical durations by scope, where the weeks actually go, what causes delays, and how to plan and ship your first version faster without cutting the corners that hurt later.
Read MoreA practical roadmap for adding AI features to a SaaS product you already run: choosing the first feature, fitting an AI layer into your architecture, respecting tenant permissions, testing, rolling out safely, and controlling cost.
Read More