Infrastructure
The technical layer that enables (or blocks) agents. From shared Jenkins to ephemeral agent sandboxes.
Maturity →
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July 2026 update: infrastructure became the answer to a question May made urgent - how do you depend on AI without being owned by it.
The runtime moved off the shared cloud and onto hardware-isolated, often self-hosted ground. AWS launched Lambda MicroVMs (June 22, Firecracker, built explicitly for AI-generated code, up to 8h runtime), AWS/Google/Azure all moved agent execution to hardware-enforced isolation, and self-hosted E2B/Daytona now keep the agent's code inside the customer VPC for data residency. "Enterprise AI agents are leaving the server" stopped being a slogan. The sovereign endpoint of that path is a full local stack: open-weight models (GLM-5.2, Kimi K2.7-Code, DeepSeek V4) running on your own hardware via llama.cpp/vLLM - the same capability, none of the vendor lock-in that disabled Fable 5 worldwide in 72 hours.
The supply chain hardened to match. PolicyLayer's State of MCP scanned 2,031 servers and found 42% expose a destructive tool while 96.1% never warn the agent; "Agentjacking" showed a malicious tool or error response treated as trusted remediation. Mitigations went mainstream - MCP Tool Search and lazy tool-loading cut both token overhead (~90% through gateways) and the live attack surface, and Dapr 1.18 Verifiable Execution (June 11) added cryptographic, tamper-evident provenance to every agent run. On the cost side the market turned from tokenmaxxing to efficiency: local token-compression proxies (prompts never leave the machine) report 60-95% savings, and Anthropic and OpenAI shipped enterprise usage analytics and spend controls. Infrastructure, not the model, still decides whether your fleet scales gracefully or burns the budget on a Tuesday night - and now it also decides whether you still have a fleet when your vendor goes dark.