The Infra Pod
The Infra Pod
The Infra Pod
What happens to your service mesh when the workloads running on it aren't written by humans? (Chat with William at Buoyant)
34 minutes Posted Jul 20, 2026 at 4:05 pm.
] Guest introductions and Buoyant founding story[03:00] Linkerd's origin: solving Twitter's monolith-to-microservices migration[07:30] How AI is (and isn't) changing Linkerd today[11:00] MCP, A2A, and agents as L7 traffic in your cluster[14:30] Why agents make endpoint-level access control non-optional[18:00] AI as amplifier: what 10–1000x more deploys means for platform teams[21:30] Running inference in Kubernetes: a pathological workload[24:45] KV cache-aware routing and the 100x performance gap[27:00] The proxy/gateway landscape: grad students vs. premature standardization[29:30] The inference proxy is a Makefile now, not Envoy[31:00] Prompt injection, sandboxing, and the security problems with no clean answer[33:00] Spicy Future: in-cluster inference becomes the default
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In this episode of The Infra Pod, hosts Tim Chen (GP at Essence VC) and Ian Livingstone (CEO of Keycard) sit down with William Morgan, co-founder and CEO of Buoyant and creator of Linkerd, to explore how AI agents are reshaping the infrastructure layer — from service security to inference routing.Will traces Linkerd's origins to Twitter's 2014 migration from a monolithic Rails app to distributed microservices — the moment function calls became network calls that could actually fail. A decade later, that same communication layer is under pressure again. Non-deterministic agents make MCP and A2A calls over L7 protocols, and for the first time, fine-grained access control isn't optional: an agent will eventually find and call every reachable endpoint, including the one that deletes your database.The conversation covers the real pressure AI coding tools are already placing on platform teams — deploy cadences going from tens to potentially thousands per day — and what running inference inside Kubernetes actually means for proxies. Will breaks down why KV cache-aware routing is a 100x performance lever, why the modern inference proxy looks less like Envoy and more like a Makefile, and shares his spicy take on where compute is heading: in-cluster inference becomes the default, with frontier models reserved only for tasks that genuinely need godlike intelligence.[00:00] Guest introductions and Buoyant founding story[03:00] Linkerd's origin: solving Twitter's monolith-to-microservices migration[07:30] How AI is (and isn't) changing Linkerd today[11:00] MCP, A2A, and agents as L7 traffic in your cluster[14:30] Why agents make endpoint-level access control non-optional[18:00] AI as amplifier: what 10–1000x more deploys means for platform teams[21:30] Running inference in Kubernetes: a pathological workload[24:45] KV cache-aware routing and the 100x performance gap[27:00] The proxy/gateway landscape: grad students vs. premature standardization[29:30] The inference proxy is a Makefile now, not Envoy[31:00] Prompt injection, sandboxing, and the security problems with no clean answer[33:00] Spicy Future: in-cluster inference becomes the default