How Tempr works, why it works that way, and what we learn running one product across every AI provider.
Every AI lab names its reasoning controls differently, and the same model can behave differently on two hosts. How Tempr gives you one setting that works everywhere, and what we found testing it.
OpenAI's pro, codex and newest gpt-6 models do some things, or everything, only on its Responses API. How Tempr bridges chat completions requests to them, one request at a time, so your tools and agents keep working.
Some MCP servers now charge per tool call, through x402 or MPP. What an agent does when a tool asks to be paid, why Tempr doesn't pay, and how it makes the refusal clear instead of a confusing error.
The Tempr CLI reads stdin, writes stdout and exits with a code that means something, so an AI agent fits into a shell pipeline or a CI job like any other command. Patterns that work, and what we fixed so they do.
An agent run is a loop of model calls whose cost you can't know in advance. How Tempr lets you, and your organization, cap what one run may spend, and see which runs cost the most.