AI Agents at Scale: Making the Economics, Speed, and Quality Work
Many engineering teams have moved past the question of whether to adopt AI agents. The harder questions are emerging now. Token costs are climbing. Output quality is inconsistent. And the next wave – background and cloud agents that run autonomously – raises the stakes on all of it.
Join us in San Francisco for an exclusive dinner with VPs of Engineering navigating this inflection point. We'll dig into what it actually takes to extract lasting value from AI agents at scale:
- Making the economics work
AI spend scales fast and the bill doesn't always correlate with results. Model routing, caching, prompt optimization, better context… there are a dozen levers. Which ones are actually moving the needle for your team, and where are you still experimenting?
- From demo speed to team speed
Agents can generate code fast, but shipping fast is a different problem. It involves review cycles, integration, trust, and knowing which tasks to hand off in the first place. What has actually changed your team's throughput versus what just shifted the bottleneck?
- Quality at scale, especially without a human in the loop
When an agent has a developer reviewing every output, quality is manageable. But the industry is moving toward background agents that run autonomously to handle tickets, CI pipelines, migrations. What does your quality bar look like for agent-generated code today, and how does that change when there's no one watching?
This invite-only event is designed to create an intimate space for you to meet with a small peer group of high-caliber engineering executives to discuss challenges, exchange best practices, expand your professional network and more.
We hope to see you there!
Questions? Contact [email protected]
