Jericco

An AI business idea can change shape quickly. A prompt pack becomes a consulting offer, extension, course, bot, or subscription tool. Fast learning is useful, but only if you can remember why each change happened. A product decision log records the choices you make while testing an idea. It captures the hypothesis, evidence, decision, owner, date, and threshold for continuing or stopping. It helps you avoid rewriting history after the fact. If you are still shaping the offer, start with the basics: who it is for, what problem it solves, and what promise you are testing. These guides on how to write a buyer line before a product page and test a promise before a format give you the raw material for a useful decision log. Why AI ideas need a decision log AI tools make it easy to generate options: names, landing pages, workflows, and feature lists. That speed can create a false sense of progress. If you do not record decisions, you may keep changing the offer without learning whether...

The easiest part of an AI side hustle is often the part people spend the most time on first. You can generate the draft. You can format the worksheet. You can assemble the landing page. You can write the sales copy. You can make the product look finished before you have answered the question that matters most: Can you point to people who already want this problem solved? That question is less exciting than a weekend build sprint. It is also the question that keeps a small idea from turning into a week of polished guesswork. Demand is not the same as attention A popular post about an AI workflow proves that people paid attention to the post. It does not automatically prove that buyers exist for the product you are thinking about making. Attention is broad. Demand is narrower. Demand means someone has a problem, recognizes it, has tried to solve it, and is willing to take a meaningful step toward a better answer. That meaningful step might be a purchase. It might also be a request...