Date & time
17:00
Register for the panel discussion
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Agent-assisted teams ship code far more quickly than before, but most of these teams have no way to track their AI agents’ output.
Agent-assisted teams ship code faster than ever, but most can’t answer basic questions about it. The CFO needs a cost-benefit analysis while team members are asking whether their agent adds unnecessary tech debt. Neither has the data.
The more autonomy you give an agent, the more understanding you need to scale it up reliably.
During this workshop, you’ll learn how to read your agentic workflow across adoption, autonomy, activity, cost, and outcomes in real time. In a live sandbox environment, you’ll spot which models and tools are worth it, catch expensive models doing cheap work, and find where to cut spending without slowing the team down.
You’ll leave with a breakdown of your own workflow and a concrete list of what to change next: which agents to trust with more autonomy and where to swap models.
Key takeaways:
- See what your agents actually cost, produce, and whether they’re making the team faster
- Identify which models and tools are worth their cost, and where you’re overspending
- Turn AI spend into measurable results, and keep improving them over time
