Building & Product

How founders use AI for AI in Your Product

3 questions founders actually ask, each with a straight answer and the resources worth your time.

Should my startup add AI features, and which ones actually matter to users? #

Add AI only where it removes real friction for your users, research shows customers don't buy 'AI-powered' labels, they buy outcomes like saved time or better answers. Start by looking at where users already do repetitive, judgment-heavy work in your product (summarizing, drafting, searching, categorizing) and run one small AI experiment there instead of rebuilding everything out of FOMO. If a feature would be just as good without the word 'AI' in front of it, that's usually a sign it's a genuinely useful feature.

How do founders ship their first AI feature (APIs, wrappers, RAG in plain terms)? #

You almost never train your own AI, you rent a model like GPT or Claude through an API, meaning your product sends the user's request plus your instructions to the model and shows the answer back (that thin layer is what people call a 'wrapper'). If the feature needs to know YOUR data, your docs, your customers' files, you add RAG, which just means the system looks up the relevant snippets first and hands them to the model like an open-book exam. Most first AI features ship in days: pick one narrow use case, wire up an API call with a good prompt, and put it in front of users before making it fancy.

How much does it cost to run AI features, and how do I keep costs sane? #

AI APIs charge per 'token' (roughly a word), so cost scales with usage, a typical feature costs fractions of a cent per request, and a support bot handling 10,000 queries a day on a mid-tier model can run around $500/month. The model you choose is the single biggest lever: cheap small models are often 10-30x less than frontier ones and good enough for most tasks, and caching repeated prompts and batching non-urgent work cuts bills further. Good news for planning: the cost of a given level of AI quality has been falling roughly 10x per year, so build the feature, monitor spend per user from day one, and don't let today's price sheet scare you off.