Optimize AI engineering outcomes with Faros and AWS
Most teams can see what AI code tools cost, yet far fewer can see what they deliver. In this session, learn how to connect AI engineering activity to shipped outcomes with Faros.
By clicking "Register" you agree to receive occasional email updates from Faros. You also agree that your personal data will be processed in accordance with our Privacy Policy.
Most teams can see what AI code tools cost, yet far fewer can see what they deliver. In this session, learn how to connect AI engineering activity to shipped outcomes with Faros. Measure cost per verified outcome, not just token spend, and set policies that govern AI usage across teams at scale.
Amazon Bedrock runs the models and meters the tokens. Faros connects that spend to the engineering results it produces, so you can govern AI usage against delivery rather than consumption.
You will learn how to:
- Enable log collection on Amazon Bedrock so you can store AI sessions for further analysis.
- Attribute engineering work to the AI sessions you collect.
- Optimize your AI engineering for different model-harness routes.
- Enforce AI model and budget policy consistently.
