Technical Analysis

Why Retry Loops Happen

Your AI agent is stuck in a loop, hitting the same error over and over. Developers call it a "doom loop" or "retry storm." Here's exactly why it happens and how governance breaks the cycle.

The Retry Inflation Cascade

When an AI coding agent fails at a task, it retries. Each retry adds the failed attempt to the context window. This makes the next attempt harder, not easier, because the context is now polluted with failure history.

1

First attempt fails

The initial approach hits an error. Context usage: 15%.

2

Agent retries with error context

The error message and failed code now occupy context space. Usage: 30%.

3

Second retry compounds

Two failed attempts now pollute context. Agent tries increasingly complex solutions. Usage: 55%.

4

Context reaches critical

Multiple failures crowd out original instructions. Agent can no longer "see" the correct approach. Usage: 85%.

5

Session collapses

Context is full. Agent restarts session, losing all progress. The cycle begins again with fresh context but no memory.

6

Cost compounds exponentially

Each restart adds 200K tokens. Five restarts = 1M+ tokens burned. $30+ on a single task.

Why This Affects Every Agent

Retry inflation is not specific to Claude Code. It affects every AI coding agent that operates within a finite context window:

Claude Code
No retry limit, no cost cap, no context pruning
Cursor
Retries with full error context, no escalation trigger
Windsurf
Cascade mode amplifies retry depth across files
Cline / Roo Code
Auto-approve mode enables infinite retry loops

How Governance Breaks the Cycle

  • Retry ceiling (streak breaker) — maximum 3 attempts before mandatory human escalation. No more doom loops.
  • Context pruning — remove failed attempt history to prevent context pollution and retry storms
  • Cost monitoring — halt execution when cost-per-retry exceeds threshold
  • Session reset — guided session restart preserving architectural context
  • Escalation routing — notify human with failure summary and recommended approach
Deploy Retry Inflation Control →Read Incident Reports

Frequently Asked Questions

Why doesn't Claude just stop retrying?
Claude is designed to persist until the task is complete. Without an explicit retry limit or streak breaker, it will continue attempting the task indefinitely — creating a doom loop where each retry makes the next retry more likely to fail.
Is this the same as an "infinite loop" or "doom loop"?
A doom loop (or retry storm) is a specific agent behavior pattern where each failed retry adds error context that makes the next attempt harder. It's not a code bug — it's a compounding cascade. When your agent is stuck in a loop hitting the same error over and over, this is what's happening.
My agent keeps failing with the same error. How do I fix it?
If your agent keeps failing on the same task, it is in a retry inflation spiral. The fix is a streak breaker — a hard limit of 3 attempts before mandatory human escalation. Without this, the agent will burn $25-$1,100 in tokens with no forward progress.
How much does retry inflation actually cost?
Documented incidents range from $25 (caught early) to $1,100 (unattended overnight). The average ungoverned doom loop incident costs $80-$150.
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