Building agents for on-call and incidents?
On Demand Event | Duration: 36 minutes | Originally aired: January 22, 2026
For Financial Services companies, managing spend, cost, and ROI is the basis of their business.
While the cost of running, maintaining, and managing the production systems that power their banking applications balloons, ROI has not kept up. Observability tools proliferate, code multiplies, and the team size to manage it all expands—without resulting in productivity, velocity, or economic gains.
AI is changing that, and this discussion explores how FinServ companies are deploying it across their stack.
Featured guests include:
To learn more about how Financial Services companies are making cost and productivity gains by moving beyond the IDE, read the AI ROI Playbook for Financial Services.
Join our engineering leads for "Behind the Build", a webinar series deep-dive into how we built agents that run software.
We benchmarked Claude Sonnet 4.6's adaptive thinking on production incident investigations. Sonnet 4.6 at medium effort came close to Opus 4.6 at a fraction of the cost.
A frontier model can produce a thousand coherent answers. Most enterprise work needs exactly one correct one, and closing that gap is not a bigger model. It is the agent architecture around it. Here are the six layers that turn open-ended capability into a defined outcome, and why production incidents are the hardest test of whether they work.
Announcing my new role at Resolve AI to lead marketing - joining a mission-driven team reimagining software operations with Agentic AI and building a category-defining company.
