I Built an AI Agent That Does X — Here's What Actually Broke

Description and use

The AI agent lost short‑term memory, looped on timeouts, and called non‑existent functions. Fixes involved separating context and memory, limiting retries, validating tool calls, and using deterministic pipelines where appropriate.

Problem

The AI agent repeatedly forgot decisions, entered infinite loops on tool failures, called non‑existent methods, and was less autonomous than expected.

Outcome

The agent became reliable, avoided infinite loops, correctly handled missing tools, and operated within clear autonomy boundaries.

Workflow

• 1. Separate short‑term context from long‑term memory store.
• 2. Add hard retry limits and exponential backoff for tool calls.
• 3. Validate every tool call against a real schema before execution.
• 4. Replace unnecessary agent logic with deterministic triggers and scripts.
• 5. Monitor agent behavior and adjust guardrails as needed.

Evidence

A few turns in, the agent would make a decision, act on it, and then reconsider the same thing later as if it had never happened.

Source

One of the agent's tools called an internal service that timed out. Instead of surfacing that as an error, my retry logic and the agent's own instinct to "try again" stacked on top of each other and turned into something close to an infinite loop.

Source

The agent confidently called an internal function that was never real.

Source