About this episode
Hamza Tahir discusses the simplicity of agents in ML, comparing them to while loops and introducing ZenML's new execution runtime, Kitaru.
Hamza Tahir , co-founder of ZenML, joins the show to cut through the hype around long-running agents — arguing that at the end of the day, an agent is just a while loop that talks to a model, calls a tool, and writes to a file system. He covers the architecture of agent harnesses (inner and outer), what durable execution actually guarantees (and what it doesn't), and why the ML pipeline paradigm is a cleaner mental model than transactions for most agent workloads. Hamza also announces Kitaru — ZenML's new open-source execution runtime for async Python agents — built on five years of running ML workloads in enterprise environments. What we get into: Agents are while loops: The surprising simplicity under all the tooling: a brain (LLM), hands (tool calls), and a file system, stacked recursively Inner harness vs outer harness: Why Pydantic AI owns the inner loop while production deployment needs a separate runtime layer What "long-running" actually means: Why the infrastructure we need to build is about extrapolating the future, not defining a time window today Durable execution demystified: What checkpointing actually guarantees (infra failures, pod death, network drops)…
People in this episode
Host: Demetrios
Guest: Hamza Tahir
Topics covered
- long-running agents
- ML pipelines
- agent architecture
- durable execution
- async Python agents
Keywords
- agents
- while loops
- ML pipeline
- Kitaru
- durable execution
- async Python
- agent workloads
- Pydantic AI
Mentioned in this episode
Organizations: ZenML, Pydantic AI, Anthropic
Products: Kitaru
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