Peter Steinberger's three-person team runs 100 AI coding agents on OpenAI's tab.
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The bill covered 603 billion tokens across 7.6 million requests, all generated by roughly 100 Codex instances operated by a team of three people working on the open-source OpenClaw project. OpenAI, which employs Steinberger, covers the cost. The top model on the dashboard was GPT-5.5, dated April 23, 2026. On the day Steinberger posted the screenshot, his account logged $19,985.84 in spend and 206,000 requests.
The latest CodexBar update renders API costs wayyyy nicer. https://t.co/lJ4dxNHwzG pic.twitter.com/fCkWutJGzT May 15, 2026
Steinberger's fleet of Codex agents autonomously reviews pull requests, scans commits for security vulnerabilities, deduplicates GitHub issues, and writes fixes. Some agents open PRs based on the project's broader roadmap, while others monitor performance benchmarks and flag regressions to the team's Discord server. According to The Decoder , certain agents even attend meetings and generate PRs for features that come up in conversation.
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OpenClaw itself has had a turbulent few months in the public eye, from wiping Meta's AI Alignment director's inbox to prompting Nvidia to develop its own competitor . But Steinberger has consistently called the project a laboratory for stress-testing what AI-assisted development looks like without budget constraints.
Steinberger clarified in a follow-up post that the $1.3 million figure reflects Codex's "Fast Mode" pricing, which consumes credits at a significantly higher rate than standard execution. Disabling Fast Mode alone would reduce the raw API cost to around $300,000, he said. That itself, however, is revealing, given that a single $200-per-month Codex Pro subscription provides roughly $5,000 to $6,000 in API-equivalent value per billing cycle. By that math, Steinberger’s non-fast-mode usage would equate to approximately 60 Codex Pro subscriptions.
OpenAI estimates that Codex costs between $100 and $200 per developer per month on average, though it warns of high variance depending on factors like model choice and automation intensity. Steinberger's usage sits at the extreme end of that variance, but it puts a number on the gap between what developers pay and the underlying compute costs.
AI coding tools are currently facing growing scrutiny over their cost economics. Codex, Claude Code, and Cursor are all competing aggressively for developer adoption, and all three subsidize inference costs well below API rates to attract and retain users. OpenAI shifted Codex to token-based billing in April, a move that made such subsidies more transparent but also more variable for power users.
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- https://www.tomshardware.com/tech-industry/artificial-intelligence/openclaw-creator-burns-through-1-3-million-in-openai-api-tokens-in-a-single-month#main
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