3 People with 100 AI Programmers, Burning Through $1.3 Million a Month! OpenAI: I'll Foot the Bill

marsbitPublicado a 2026-05-17Actualizado a 2026-05-17

Resumen

In a striking demonstration of AI-powered development, Peter Steinberger (creator of OpenClaw) shared that his three-person team spent $1.3 million in one month to run approximately 100 AI agents (primarily Codex instances). OpenAI covered the cost. The expenditure consumed 6.03 trillion tokens across 7.6 million requests. Steinberger argues that, with "fast mode" disabled, the cost falls below that of a single engineer while providing significantly greater output. This "cloud programmer army" handles core but tedious software engineering tasks: reviewing pull requests, finding security vulnerabilities, deduplicating issues, fixing bugs, monitoring benchmarks, and even generating PRs after meetings. This shifts AI's role from merely writing code to maintaining the entire collaborative fabric of a project. Steinberger's tool, CodexBar (a macOS menu bar app), tracks usage and costs across various AI coding services, highlighting how token consumption is becoming a key metric—a new "means of production." The experiment poses a profound question: if token cost ceases to be a barrier, how will software development transform? As model prices fall, the capability for small teams to leverage large numbers of AI agents could become commonplace, fundamentally altering the scale and speed of development. The future, Steinberger suggests, is arriving rapidly.

Peter Steinberger

Editor: Solomon

[New Zhiyuan Report] 3 people, 100 AI agents, burning through $1.3 million a month — The father of OpenClaw has turned software development into an "AI assembly line," with OpenAI picking up the tab.

While others show off their pay stubs, he shows off the bill — $1.3 million a month!

That's nearly 9 million RMB per month. It's left netizens utterly dumbfounded.

OpenClaw father Peter Steinberger casually posted a screenshot on X.

Peter Steinberger

But the numbers on the screenshot were anything but casual:

30-day spend: $1,305,088.81. Consumed 603 billion tokens. Made 7.6 million requests.

You read that right, 1.3 million U.S. dollars. And it's not a quarterly AI budget for some big tech company — it's the monthly usage of a three-person team.

Even more explosive: OpenAI is reimbursing this cost.

The comment section instantly went wild.

Some were amazed, some skeptical, some whipped out their calculators to figure out "how many programmers this equals."

Steinberger himself calmly responded: "With fast mode off, my cost is less than an engineer, and it really helps a lot more."

Translation: — It's genuinely cost-effective!

Other netizens were shocked by the $400k/month engineer — "The San Francisco job market is insane."

Netizen comment

Netizen comment

Others were curious about where this massive token usage went.

Peter responded that most was used for OpenClaw development.

Netizen comment

A Cloud-Based Programmer Army

The most outrageous thing is that Pete's small team only has 3 people.

They have about 100 Codex instances running long-term in the cloud, handling the dirtiest, most grueling, most mind-numbing work in software engineering —

Reviewing PRs, finding security vulnerabilities, deduplicating issues, fixing bugs, monitoring benchmarks, posting to Discord upon discovering regressions, even opening PRs directly after listening to meetings.

Thus, AI isn't just "helping you write code," but is infiltrating every crevice of software collaboration.

This is terrifying.

Because what's truly expensive in software development is communication, comprehension, context switching, review, regression, fixes, waiting, and repetitive tasks.

In the past, a team spent a huge amount of time each day on these things that don't seem like "creation" but without which the project would rot.

Now, Peter has tossed all these processes to a bunch of AI agents at once.

This is AI starting to maintain the nervous system of an organization for you.

Illustration

There's another important detail in this screenshot: it's not the OpenAI backend, but CodexBar made by Peter.

CodexBar is a macOS menu bar tool for tracking usage windows, credits, costs, and reset times for various AI programming tools.

It supports a bunch of services like Codex, Claude, Cursor, Gemini, Copilot, etc.

What used to be in a programmer's menu bar? CPU, memory, battery, network speed.

Now there's one more thing: tokens. Tokens are becoming a new "means of production."

CodexBar

A Final Word

$1.3 million a month, 3 people, 100 AI agents.

Ponder this set of numbers — three living humans, leading a hundred digital employees who don't eat, sleep, or demand raises, doing the work of an entire engineering team.

Some felt invigorated after reading this: AI finally isn't just a decorative vase for chatting! Others felt a chill down their spine: Wait, so what do we coders do in the future?

But honestly, what keeps me up at night is Steinberger's casual remark: "I'm exploring what software development would look like if token cost wasn't an issue."

Peter Steinberger

Everyone, he said "if."

The problem is, this "if" is visibly turning into "when" at an astonishing speed.

The work that costs $1.3 million today, after one price cut for models, becomes $130k. Another cut, $13k.

On that day, having 100 AI agents working simultaneously is no longer a game exclusive to Silicon Valley big shots, but a basic operation for any three-person startup team.

Three young people in a garage, holding a hundred tireless AI programmers — this image, just thinking about it is absurd.

Peter Steinberger has revealed the bottom card.

On the card it says: The future is already knocking, and it doesn't plan to wait for you to be ready.

References:

https://the-decoder.com/for-1-3-million-a-month-openclaw-founder-peter-steinberger-runs-100-ai-agents-that-code-review-prs-and-find-bugs/

https://x.com/steipete/status/2055346265869721905

https://developers.openai.com/codex/speed

This article comes from the WeChat public account "New Zhiyuan", author: New Zhiyuan

Preguntas relacionadas

QHow much money did the three-person team spend on AI development in one month, and who covered the cost?

AThe three-person team spent $1,305,088.81 (approximately 1.3 million USD) in one month on AI development, and the cost was covered by OpenAI.

QWhat is the name of the tool Peter Steinberger created to track AI development costs and usage?

APeter Steinberger created a tool called CodexBar, a macOS menu bar application that tracks usage windows, credits, costs, and reset times for various AI programming tools like Codex, Claude, Cursor, Gemini, and Copilot.

QApproximately how many AI agents (instances) does Peter Steinberger's team run for development tasks?

APeter Steinberger's team runs approximately 100 AI Codex instances to perform various development tasks.

QWhat kinds of software development tasks do the AI agents in the article handle?

AThe AI agents handle tasks such as reviewing pull requests (PRs), finding security vulnerabilities, deduplicating issues, fixing bugs, monitoring benchmarks, reporting regressions to Discord, and even opening PRs after listening to meetings.

QWhat is the core implication Peter Steinberger highlights regarding the future of software development with AI?

APeter Steinberger highlights that the core implication is exploring what software development would look like if token cost were not a limiting factor, suggesting a future where small teams can leverage large numbers of AI agents as a standard practice, dramatically changing the development landscape.

Lecturas Relacionadas

"Water Scarcity": The Hidden Fatal Flaw of AI Infrastructure

“Water Scarcity: The Hidden Vulnerability of AI Infrastructure” In June 2026, SpaceX revised its IPO prospectus to highlight a core resource constraint alongside power and processors: water. This move signals a pivotal shift where water scarcity has transformed from an operational cost to a major, uncontrollable investment risk, directly threatening AI data center expansion. The scale of the problem is immense. U.S. data centers consumed an estimated 17 billion gallons of water for direct cooling in 2023, with indirect water use for power generation exceeding 211 billion gallons. Giants like Google alone use billions of gallons annually, with single sites consuming volumes equivalent to a medium-sized city. This water is largely “consumptive,” evaporated into the atmosphere and lost. This massive demand is colliding with scarcity. Tech companies are building “water tigers” in arid regions, sparking community protests in places like Mexico and Arizona, where data centers can legally use millions of gallons daily—enough for tens of thousands of residents. These conflicts are not about illegality, but about a mismatch between historic water allocation frameworks and new, colossal demand. The consequences are real. Community opposition, largely centered on water, has reportedly stalled or canceled $64 billion in U.S. data center projects over two years. Simultaneously, investors are pressuring companies for greater water footprint transparency, viewing it as a financial risk, not just an ESG metric. Technological solutions like air or liquid cooling involve trade-offs between water and electricity use, with final choices dictated by local constraints. The irony is stark: while industry leaders envision AI as a utility “like water,” its physical infrastructure is straining real-world water supplies. The race for AI supremacy may ultimately be governed not by the fastest chip, but by the slowest water meter.

marsbitHace 3 min(s)

"Water Scarcity": The Hidden Fatal Flaw of AI Infrastructure

marsbitHace 3 min(s)

Global Card Issuance Enters a Compliance-Driven Era: WasabiCard is Building the Next-Generation Payment Infrastructure

Global card issuance is entering a compliance-driven era, with WasabiCard building next-generation payment infrastructure. The platform asserts that as stablecoins increasingly enter cross-border payments, corporate settlements, and global commerce, the industry is shifting focus from "availability" and "growth-driven" models to long-term, compliant operation under global frameworks. Competition will center on sustainable compliance and global infrastructure capabilities. Stablecoins are evolving from on-chain assets into key payment tools in global business, with card issuance acting as critical infrastructure connecting digital assets to traditional payment networks like Visa and Mastercard. This expansion has revealed structural issues, including cross-regional issuance, BIN resource management, and insufficient AML and risk controls. In response, the industry is moving away from reliance on "grey efficiency" towards prioritizing compliance, risk management, and long-term operational stability. WasabiCard outlines its strategy: collaborating with licensed principals and local partners for localized operations, building robust KYC/AML systems, strictly separating commercial and consumer BIN usage, and enhancing global issuance, payment, and cross-border fund flow infrastructure. The goal is to build stable, scalable payment infrastructure amid evolving global regulations, shifting industry competition from scale to infrastructure capability. As stablecoins integrate further with global commerce, payment infrastructure will become a fundamental, embedded component of internet business. WasabiCard will continue to develop capabilities in global card issuance, stablecoin payments, cross-border fund flows, and API-driven financial workflows.

marsbitHace 14 min(s)

Global Card Issuance Enters a Compliance-Driven Era: WasabiCard is Building the Next-Generation Payment Infrastructure

marsbitHace 14 min(s)

Zhou Hang: How Much Is SpaceX Really Worth?

**Zhou Hang: How Much is SpaceX Really Worth?** SpaceX, arguably one of the greatest industrial companies of the past 50 years, is reportedly targeting a staggering $1.75 trillion valuation in its potential IPO. However, the author argues this figure is inflated by approximately $1.25 trillion when assessed through standard financial metrics. The analysis begins by acknowledging SpaceX's undeniable success: drastically reducing launch costs, achieving near-monopoly in commercial launches, and building the strategic Starlink network. Its achievement surpasses even Tesla's, given it disrupted a state-monopolized industry. Despite this greatness, a $1.75 trillion valuation places SpaceX above the combined market cap of Boeing, Lockheed Martin, Northrop Grumman, RTX, and General Dynamics. Projecting optimistic 2030 revenues of $50-80 billion and applying generous tech-sector multiples yields a "reasonable" valuation range of $500 billion to $1.2 trillion. The $1.25 trillion gap is attributed to three non-financial premiums: 1. **Long-term vision premium** for future Starship-enabled markets (e.g., space-based computing). 2. **Sovereign asset/strategic premium**, as SpaceX is deeply integrated into U.S. national security. 3. **Retail narrative/Musk cult premium**, driven by a heroic story and personal following. Post-IPO, three scenarios are outlined: valuation solidifying (25% probability), sideways volatility as narrative outpaces reality (50%), or a re-rating down to $800B-$1.2T if execution falters or Musk-related risks emerge (25%). The probability-weighted expected value is $1.3-1.5 trillion, suggesting negative expected returns for those buying at the IPO price. The conclusion advises investors to separate the company's excellence from its stock price. Buying at the IPO likely prices in excessive optimism. A more prudent strategy would be to wait for key milestones (e.g., Starship V3 stability) or a significant price correction before investing, or to treat an early purchase as a long-term, high-conviction hold with limited position size, not a short-term bet.

链捕手Hace 18 min(s)

Zhou Hang: How Much Is SpaceX Really Worth?

链捕手Hace 18 min(s)

Trading

Spot
Futuros

Artículos destacados

Cómo comprar BILL

¡Bienvenido a HTX.com! Hemos hecho que comprar Billions Network (BILL) sea simple y conveniente. Sigue nuestra guía paso a paso para iniciar tu viaje de criptos.Paso 1: crea tu cuenta HTXUtiliza tu correo electrónico o número de teléfono para registrarte y obtener una cuenta gratuita en HTX. Experimenta un proceso de registro sin complicaciones y desbloquea todas las funciones.Obtener mi cuentaPaso 2: ve a Comprar cripto y elige tu método de pagoTarjeta de crédito/débito: usa tu Visa o Mastercard para comprar Billions Network (BILL) al instante.Saldo: utiliza fondos del saldo de tu cuenta HTX para tradear sin problemas.Terceros: hemos agregado métodos de pago populares como Google Pay y Apple Pay para mejorar la comodidad.P2P: tradear directamente con otros usuarios en HTX.Over-the-Counter (OTC): ofrecemos servicios personalizados y tipos de cambio competitivos para los traders.Paso 3: guarda tu Billions Network (BILL)Después de comprar tu Billions Network (BILL), guárdalo en tu cuenta HTX. Alternativamente, puedes enviarlo a otro lugar mediante transferencia blockchain o utilizarlo para tradear otras criptomonedas.Paso 4: tradear Billions Network (BILL)Tradear fácilmente con Billions Network (BILL) en HTX's mercado spot. Simplemente accede a tu cuenta, selecciona tu par de trading, ejecuta tus trades y monitorea en tiempo real. Ofrecemos una experiencia fácil de usar tanto para principiantes como para traders experimentados.

145 Vistas totalesPublicado en 2026.05.07Actualizado en 2026.06.02

Cómo comprar BILL

Discusiones

Bienvenido a la comunidad de HTX. Aquí puedes mantenerte informado sobre los últimos desarrollos de la plataforma y acceder a análisis profesionales del mercado. A continuación se presentan las opiniones de los usuarios sobre el precio de BILL (BILL).

活动图片