Building the Developer Platform for AI Agents

The Problem

Enterprise platforms were built for human developers working at human pace. Now that AI agents can write code, trigger workflows, and access infrastructure autonomously, the gaps are stark. Your organization management assumes developers push code on their terms. Your secrets infrastructure wasn't designed for AI processes that run unattended. Your DLP and code scanning tools have blind spots for AI-generated output. Your compute infrastructure wasn't provisioned for the workload agents actually demand.

Join us where we'll walk through:

• The shift: moving from AI as a coding assistant to AI as an autonomous contributor in your development pipeline

• The infrastructure gap: what needs to change in your org config, secrets management, DLP, and compute layer before agents arrive

• What actually works in production: implementation patterns across different stacks and platforms

• Real lessons: what Improving's clients have learned deploying agents at scale

Lunch will be provided