Explore String AI articles about products and models, and find the right approach for you.
Lowering LLM API costs is not a price hunt; it is an ordered engineering path. Measure first, remove waste, shrink tokens, move deferrable work to cheaper paths, fix caching, right-size models, then verify nothing regressed.
Stop starting from leaderboards. Write six constraints first, converge with a small golden set, and compare failure types instead of scores. A practical guide to choosing models that survive production.
An aggregation layer is not a default and not a mistake. It is a trade against four dimensions: integration cost, replacement cost, usage visibility, and the parts of the stack you cannot outsource. Here is how to decide, and how to keep your exit open.
A provider invoice tells you what was spent, not who spent it. Two ledgers and five attribution dimensions make every request traceable to a feature, a team, and a customer.
A five-step walkthrough for your first String AI API call: get a key, set the OpenAI-compatible base URL, list models, send a chat completions request, and read the response, plus the three mistakes that break first calls.
Assign research, extraction, writing, and review clear jobs. Compare models on evidence handling, accepted output, and the work left for your team.
