How much did Uber spend on AI agents?

Uber burned its entire 2026 AI budget in one quarter after giving 5,000 engineers Claude Code access starting December 2025.

What causes AI agent runaway costs?

Agentic loops retry failed operations indefinitely, run overnight with no human supervision, and most deployments use a single org-wide billing key with no per-agent hard cap. AI agents burn 50x more tokens than chat sessions.

What is the difference between a budget alert and a hard kill switch?

Budget alerts notify after spending occurs. A hard kill switch terminates the agent at the API-call level when a dollar or token ceiling is hit, preventing further spend instantly.

Do major agent frameworks have built-in budget controls?

No. LangChain, CrewAI, and the OpenAI Agents SDK lack built-in per-run dollar hard caps. Developers must add third-party wrappers like AgentGuard.

What product could be built here?

A drop-in SDK middleware layer that wraps any LLM API call, tracks real-time dollar spend per agent session, and terminates the agent when the budget ceiling is hit. Integrates with Anthropic, OpenAI, and Gemini APIs.

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clawsmith.com/signal/ai-agent-runaway-cost-no-hard-budget-kill-switch

⚠ IssueUnderservedLive

AI agents burn enterprise budgets overnight with no hard kill switch

Uber burned its entire 2026 AI budget by Q1 after giving 5,000 engineers Claude Code access. A 4-agent LangChain loop ran 11 days and cost $47,000. HN discussion on rising agent costs reached 306 points. Most deployments use a single org-wide billing key with no per-agent hard cap. Runtime budget enforcement that terminates agents at a real dollar threshold is nearly absent from standard agent frameworks.

Product Idea from this Signal

A web app that enforces hard dollar and token budgets per AI agent and kills runaway sessions before they blow the monthly spend

1.0k ▲

AI agents loop silently for hours and rack up thousands of dollars in token spend with no hard enforcement layer to stop them. Existing soft limits inside SDK params are advisory and bypassable; teams only discover the overage on the billing page. This app sits as a governance proxy between any agent runtime and the LLM API, evaluates per-agent dollar and token ceilings before each call completes, and terminates the session the instant a threshold is crossed.

ai-agentscost-controltoken-budgetsagent-opsfinopsdeveloper-toolsmcp

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