Why AI Infrastructure must evolve for Agent Experience — Akshat Bubna, Modal CTO
Modal's cofounder Akshat Bubna argues that AI agent infrastructure has matured enough to support reliable agent experiences, two years after the company's initial coverage.
- Modal's agent cloud has evolved over two years to support reliable, stateful AI agents in production.
- Advances in model capabilities and orchestration tools have made agent infrastructure viable now.
- The company emphasizes scalability and developer experience as critical for agent reliability.
- Persistent, multi-step agent workflows are now feasible with modern infrastructure.
Two years after Modal first explored the concept of agent infrastructure, cofounder and CTO Akshat Bubna returns to explain why the time is finally right for reliable agent experiences. The company has spent the intervening period building and refining its agent cloud, uncovering key lessons about scalability, reliability, and developer experience that make agentic workflows practical today.
Bubna highlights how advances in model capabilities, tooling, and orchestration have converged to create an environment where agents can operate autonomously without constant human intervention. Modal's infrastructure now supports persistent, stateful agents that can handle complex, multi-step tasks across diverse applications. The company's approach focuses on reducing friction for developers while ensuring agents remain controllable and predictable in production environments.
Source: Why AI Infrastructure must evolve for Agent Experience — Akshat Bubna, Modal CTO. Read the full piece at the source.
Provides insights into building and deploying reliable AI agents at scale.
Demonstrates how agent infrastructure can enable new automation capabilities.
Shows the maturation of AI agent technology for real-world use.
- Agent Experience
- The design and infrastructure required to build, deploy, and manage autonomous AI agents reliably.
- Agent Cloud
- A cloud-based platform designed to host, orchestrate, and scale AI agents for production workloads.
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