𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀 𝗛𝗮𝘃𝗲 𝗔 𝗥𝗲𝗹𝗶𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗣𝗿𝗼𝗯𝗹𝗲𝗺
AI agents are moving from software that responds to software that acts. They call APIs, move money, and update databases.
But there is a massive gap between intelligence and reliability.
We focus on better models and better prompting. We ignore the infrastructure. This mismatch causes real-world failures.
Imagine an agent processes a refund. It calls the payment API. The API succeeds. Then, a server crash happens before the agent records the success. The system retries the task. The agent calls the API again. The customer gets a double refund.
No one wrote a bug. The model reasoned correctly. The API worked. The failure happened because the infrastructure is incomplete.
Most agents work fine in demos. Demos run in a single process. They run one task at a time. They do not face crashes or concurrency. Production is different.
When you move agents to production, three things break:
• Process Imortality: Agents assume the process never dies. In reality, hosts die and deployments happen. When a process dies, the in-memory state vanishes. • Pure Tool Calls: Developers treat tool calls like simple reads. But agents perform side effects. Moving money or sending emails cannot be undone easily. • Exactly-once Execution: Retries are necessary for reliability. But retrying an in-memory loop without a durable log creates duplicate actions.
This is not a prompting problem. It is a distributed systems problem. To fix this, we need durable execution.
Reliable agents need these five pillars:
- Event Sourcing: Store an immutable log of every action. The log is the source of truth, not the in-memory state.
- Replayable Execution: Use the log to reconstruct state after a crash. Replay completed steps instead of re-running them.
- Durable Queues: Move work from memory to persistent stores.
- Idempotency Keys: Ensure performing an action twice has the same effect as performing it once. This prevents double payments.
- Compensation Patterns: Define actions to undo steps if a multi-step workflow fails halfway.
A better model produces better decisions. But a better model cannot fix a crash. Reliability is a property of execution, not a property of decisions.
The agents you can trust to act without human oversight will not just be the smartest. They will be the ones running on reliable infrastructure.
Trí tuệ quyết định việc cần làm. Cơ sở hạ tầng đảm bảo việc đó thực sự được thực hiện một cách chính xác.
Nguồn: https://dev.to/code_with_mwai/ai-agents-have-a-reliability-problem-nobody-is-talking-about-j40
Cộng đồng học tập (tùy chọn): https://t.me/GyaanSetuAi