#ai

11 posts

  1. 01 Story points are useless when building is the easy part If an agent can build the product before you finish estimating the backlog, what exactly are you estimating for?
  2. 02 Personalization doesn’t need a six-month project anymore Adding personalization to Croozie took less than a day. Existing models and an ordinary stack make it possible to start with a useful experience, measure it, and improve.
  3. 03 Is it even worth trying to block AI or bots anymore? Blocking bots can be worth doing. But if an agent can deliver most of your product’s value by reading a few public pages, the next strategy discussion probably needs to go beyond a better CAPTCHA.
  4. 04 My AI apps keep turning into the same seven tools The product keeps changing... the infrastructure mostly doesn’t.
  5. 05 I Let AI Agents Review and Merge PRs. Then Disaster Struck. The features worked, but background jobs kept my serverless database awake. AI code review missed the operating assumption that made the design expensive.
  6. 06 OpenAI’s Dot Found Me a NYC Apartment. I Just Showed Up. I gave dot a goal, made decisions along the way, and showed up. It helped with the apartment search, viewings, paperwork, and the little things after signing.
  7. 07 Turns Out My Career Was Training for AI Engineering, product, design, and program management taught me to connect decisions from the problem through to the finished product. That experience is useful when building with AI.
  8. 08 Do You Really Need a CMS in 2026? Rethink CMS defaults: start with a typed ORM schema, generate admin UIs with AI, and reserve full CMS platforms for real governance needs.
  9. 09 AI Is Quietly Changing How You Should Pick a Tech Stack Tech stack choices now include an AI factor: training data, ecosystem maturity, and how reliably AI can help you ship and maintain code.
  10. 10 How I built this site... or should I say guided my agents to build it? Discover how to build a fast, database-driven site with a static shell and cache-driven fragments using Next.js, Cache Components, and AI-assisted workflows.
  11. 11 PM, Dev, QA Are Merging: Meet the Rise of the Product Engineer Uncover how AI merges PM, dev, and QA into a single product engineer. Learn to specify user needs, criteria, and metrics to accelerate delivery.