Agile AI Development Lifecycle vs Wattfare

A framework and methodology for transforming pre-AI software development lifecycle into AI-native development at scale.

Users connect, set a spending cap, and you call any model through one SDK, charged to them, not you.

About Agile AI Development Lifecycle

A framework and methodology for transforming pre-AI software development lifecycle into AI-native development at scale. At first it looks like an easy-to-adopt (just drop markdown files into your repository) framework that should take one from pre-AI software development lifecycle to the AI-native future. In its nature it is very similar to compound engineering. - all of them are a collection of skills in markdown prose that rely on human-in-the-loop review. Notably both of them were introduced to the public a few months before AWS released AI-DLC, but it's hard to compete with AWS in terms of visibility.

About Wattfare

Users connect, set a spending cap, and you call any model through one SDK, charged to them, not you. OpenAI-compatible Works with the Vercel AI SDK ~5-min integration. One button connects a user's inference budget to your app, metered, capped, and revocable. The problem AI costs are the one line item you can't predict. Every AI app makes the same uncomfortable bet: price high enough to survive your power users, ration usage so nobody hurts you, or quietly lose money on the heavy ones.