Getting Started & Migration
What kind of durable agent should I build first to understand Catalyst’s execution model?
Start with an agent that has a few deterministic steps plus a single LLM call, so you can observe how Catalyst replays and resumes. This pattern exposes the core mechanics of state capture and re-execution. Be aware that truly non-deterministic steps like LLM inference require explicit checkpointing to ensure consistent replay.
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- Getting Started & Migration
What does a minimal but realistic durable agent look like when I first run Catalyst locally?
A realistic durable agent prototype that progresses from a call to an LLM through a conditional action to an API, illustrating automatic state persistence.
- Getting Started & Migration
How do I iterate quickly on durable agent logic without deploying to a shared cluster?
Use a local Dapr sidecar to execute and debug agent workflows, enabling a fast edit-run-debug cycle without remote dependencies.
- Getting Started & Migration
My agent is already built with LangChain/LlamaIndex. Can I add durable execution without a rewrite?
Wrap an existing agent’s entry point in a Catalyst workflow to gain durability without modifying framework internals, then progressively refactor.