Topic
Practices and controls—usage quotas, rate limits, budget caps—for managing and bounding the cost of AI model inference and agent workloads.
An autonomous coding setup on a Mac mini splits reading from writing into two agents with separate tool lists. Its operator reports guessed-API failures falling from about one task in five to one in forty.
Reality
Model identifiers are untyped strings, so a one-character slip on a multi-vendor gateway picks up a different cache-read rate with no error and nothing in the logs. A dev.to post turns the pricing page into a CI check.
Reality
The New York Times reports Meta's internal ceiling for Anthropic spending reached $10bn a year while Zuckerberg warned about doom-mongering labs, and the agent Claude helped test is set to launch on Meta's own model.
Reality
Azure starts new subscriptions at zero GPU vCPUs and raises them by hand, which puts the one step you cannot rerun at the front of a walkthrough where everything after it is just a command you can repeat.
Reality
Selection here turned on two things no leaderboard reports: whether a model flips Yang Wood to Yin Wood in English output, and whether it lets you switch reasoning off. Price only broke the remaining ties.
Reality
A dev.to writeup traces the bill to a route handler that builds prompts, calls OpenAI and parses replies in one place. The fix is a seam, and the patch target decides whether it holds.
Reality
A single deep-research request burned 194% of a rolling quota, most of it inside six minutes. The tiering rule that should have caught it never reached a decision point.
Reality