Your AI bill should be bigger
For some teams. Smaller for others. See which teams have earned the right to spend more, and the evidence behind that decision.
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AI agents have changed the economics of software development. A large AI bill can mean agents are stuck in expensive loops. It can also mean a team is shipping its next major product faster than it ever could before. The invoice looks the same either way. Chase Norton sits down with Faros co-founder and CEO Vitaly Gordon, who previously co-founded Salesforce Einstein and led its engineering organization, to work through how leaders tell those two situations apart.
What you'll learn:
- What stays scarce once engineering capacity becomes elastic, and where the real constraint moves
- Whether spending caps protect the business or quietly throttle your highest-return teams
- How to read an AI bill as a signal, and separate productive investment from expensive loops
- How to run an organization where AI ability and returns vary widely from one engineer to the next
- Who should be allowed to spend more, and what evidence should earn them that freedom
