We cut our coding agent costs 73% with budget gates, not better prompts
Our coding agent burned through $347 in three days. Not because it was working on complex problems — because it kept retrying the same failed API call 847 times before we noticed.
The real problem wasn't the retry loop. It was that we had no idea it was happening until our OpenAI bill arrived.
Coding agents fail differently than other agents. They don't just hallucinate — they get stuck in expensive retry cycles, spawn infinite subprocess loops, and burn through API quotas while "debugging" phantom issues that don't exist.
Every production coding agent needs three budget gates before it needs better reasoning:
Per-task token budgets with hard stops
Set a maximum token spend per discrete task. Not per conversation — per actual work unit. When it hits the limit, the agent stops and escalates to human review with a full trace of what it attempted.
TASK_TOKEN_LIMIT=5000 RETRY_TOKEN_BUDGET=1500 ESCALATION_THRESHOLD=0.8
Our agent now stops at 4,000 tokens and asks: "I've used 80% of my budget on this task. Should I continue or hand this off?"
Retry limits with exponential backoff costs
Don't just limit retries — make each retry cost progressively more from the budget. First retry costs 100 tokens from the limit, second costs 200, third costs 400. This forces the agent to be more careful with each attempt instead of brute-forcing solutions.
retry_cost = base_cost * (2 ** retry_count)
remaining_budget -= retry_cost
if remaining_budget <= 0:
escalate_to_human(task, attempt_log)Cost telemetry that screams before it's too late
Track spend per task type, not just per session. We learned that our agent spends 3x more tokens on debugging tasks than feature implementation. Now we route debugging to cheaper models and save Sonnet for actual code generation.
Warning: Most cost overruns happen during "cleanup" tasks that agents think are simple. Set lower budgets for refactoring, documentation, and test fixes — these are where infinite loops hide.
The pattern that changed everything: Budget-first task planning. Before starting any task, our agent now estimates token cost and asks for budget approval. "This refactoring task will likely cost 2,000-4,000 tokens. Approve spend?"
Result: We cut our coding agent costs 73% and caught two infinite loops that would have cost us $200+ each.
The buyer question isn't which agent is smartest anymore — it's which workflow ships features without surprise $500 bills.