Beyond Sandboxes: Building Durable AI Agents

Sandboxes are not enough for production AI agents.

Most developers build agents as a simple loop in memory. The LLM observes, decides, acts, and repeats. This works in a lab. It fails in the real world.

Why does the memory loop fail?

  • Long tasks: If an agent needs days to finish or waits for a human to approve a task, keeping a process running wastes CPU and memory.
  • No crash recovery: If the system crashes or the network drops, you lose the entire state. You cannot resume from where you left off.
  • Complexity: Multiple agents struggle to talk to each other without massive amounts of extra code.

Virein Baraiya, CTO of Orkes, suggests a better way. Separate your concerns.

Use a sandbox only for actions. Use a sandbox to run risky tool code safely.

Use a durable runtime for reasoning. The LLM provides the plan. The runtime system handles the execution and state.

He introduces two tools to solve this:

  1. Netflix Conductor This is a workflow engine. It acts as a ledger. It records every LLM call and every tool use in a database.
  • It supports on-demand suspension. If an agent waits for a human, the system pauses the workflow and releases all memory.
  • It can wake up months later to finish the task.
  1. Agent Span This is a runtime built on top of Conductor. It acts as a translator.
  • You can use existing tools like LangGraph or OpenAI SDK.
  • Agent Span converts your agent code into durable workflows without you rewriting your business logic.

This architecture provides three big wins:

  • Guardrails: The framework controls the rules, not the LLM. This stops hallucinations from causing damage.
  • Full Audit: You can see exactly why an agent made a decision months later. You can even replay the process.
  • Better Testing: You can change one LLM output and see how the rest of the system reacts.

A final tip for builders: Focus on business context. Models change. Frameworks change. But the specific way your business executes tasks is your true moat.

Source: https://dev.to/cognitalk/chao-yue-sha-xiang-wei-ai-agent-gou-jian-chi-jiu-hua-yun-xing-shi-2i9i

Optional learning community: https://t.me/GyaanSetuAi