OpenAI’s long-standing leadership in artificial intelligence is facing its sharpest test yet. In an internal memo revealed across multiple reports, CEO Sam Altman admitted that Google’s rapid progress with its newly launched Gemini 3 model has created “rough vibes” and “temporary economic headwinds” for OpenAI. The leaked communication marks a rare moment of vulnerability inside the company that once appeared unstoppable, signaling a shift from confident supremacy to a high-pressure race to regain lost ground.
Altman’s remarks have surfaced at a critical time: enterprise AI enthusiasm is cooling, competitive benchmarks are turning against OpenAI, and internal challenges with pre-training have slowed the company’s ability to maintain its former technological edge. The memo, described as unusually candid, paints a picture of a company preparing for a difficult but determined fight ahead.
Key Takeaways: OpenAI–Google Rivalry Intensifies with Gemini 3’s Rise
- Google’s Gemini 3 has overtaken OpenAI across nearly all major AI benchmarks, pressuring OpenAI’s technological lead.
- Sam Altman warned staff that the company faces “temporary economic headwinds” and a period of “rough vibes.”
- OpenAI is reportedly struggling with progress in pre-training, a core phase of model development, especially during GPT-5 scaling.
- A new model codenamed “Shallotpeat” is under development to fix foundational pre-training issues.
- Revenue growth could slow dramatically to 5–10% by 2026, a major drop from previous hypergrowth.
- Enterprise demand shows signs of cooling, with key partners like Microsoft and Salesforce scaling back certain AI deployments.
- OpenAI forecasts a significant long-term cash burn, contrasted with Google’s far greater financial capacity to sustain AI investments.
- Despite setbacks, Altman insists OpenAI is “catching up fast” and doubling down on ambitious long-term research bets.
Google’s Gemini 3 Reshapes the Competitive Landscape
Google’s launch of Gemini 3, described as its most capable multimodal and reasoning model so far, has shifted the AI landscape dramatically. The model has been integrated across Google Search, developer tools, and core applications, and early responses from analysts position Gemini 3 as a clear leader in performance.
Independent benchmarks reflect the same reality: Gemini 3 Pro has taken the top spot in reasoning, coding, and other high-value AI tasks. This rise directly challenges OpenAI’s once unquestioned leadership, marking the first time Google has surpassed OpenAI so decisively.
Altman’s memo acknowledged Google’s “excellent work recently in every aspect,” particularly highlighting their advancements in pre-training—an area where OpenAI has been facing internal hurdles.
Pre-Training Becomes the Core Battleground
The memo revealed an important, previously unseen challenge: OpenAI’s struggle with the pre-training phase of model development. Pre-training, where large AI models learn from massive datasets, had been believed by some researchers to be nearing diminishing returns. But Google’s significant progress proved otherwise.
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Reports indicate that OpenAI encountered optimization issues during GPT-5’s development, where scaling efforts stopped delivering expected gains. This pushed OpenAI to explore alternative strategies, such as focusing more heavily on “reasoning” models.
Altman’s note frames this as a temporary slowdown, but one significant enough to impact product performance, enterprise perceptions, and internal momentum.
OpenAI’s Countermove: The “Shallotpeat” Model
To address the underlying pre-training issues, OpenAI is developing a new language model internally codenamed “Shallotpeat.” According to individuals familiar with the project, Shallotpeat directly targets the bugs and inefficiencies that have emerged in OpenAI’s recent training pipelines.
The name itself appears symbolic: shallots do not grow well in peat soil. The codename suggests a model designed to thrive even in difficult technical “terrain,” representing an attempt to rebuild OpenAI’s pre-training capabilities from the ground up.
Altman assured staff that despite short-term setbacks, OpenAI is focused on “very ambitious bets,” including attempts to automate AI research itself, which he believes will accelerate breakthroughs.
Financial Alarm: From Hypergrowth to Possible Stagnation
Internally, the most alarming revelation is Altman’s projection that OpenAI’s revenue growth could slow to single digits by 2026. This would be a sharp decline from the explosive growth that helped the company reach a reported $13 billion annual revenue run rate.
The slowdown comes at a time when OpenAI is forecasting massive long-term spending, including a projected $74 billion operating loss by 2028.
This stands in stark contrast to Google, whose far stronger profitability allows it to sustain intensive AI development at scale. Investors who once viewed OpenAI as the inevitable frontrunner may now reconsider, especially if the company’s hypergrowth narrative slows before its infrastructure build-out is complete.
Rumors of a possible hiring freeze have also surfaced, further reflecting the changing internal mood.
Enterprise Reality Check and the Cooling AI Hype
Another core theme of Altman’s memo is the cooling enterprise demand for generative AI.
Key examples include:
- Microsoft reportedly delayed certain Azure AI integrations because of capacity challenges and ROI uncertainties.
- Salesforce scaling back custom GPT pilot projects.
- Reports indicate that 95% of enterprise GenAI pilots fail to reach production, leaving behind costly “shelfware.”
This slowdown directly threatens the logic behind the industry’s massive data-center spending, which analysts say is nearing $400 billion annually.
Despite this, OpenAI’s leadership remains committed to the philosophy that “compute is king,” insisting that cutting back now would be more damaging than overspending.
Spiritual Perspective by Saint Rampal Ji Maharaj
As tech giants race for AI supremacy, the uncertainty surrounding economic trends, competitive pressures and shifting global priorities highlights how fragile material progress can be. In contrast, the spiritual knowledge of Saint Rampal Ji Maharaj emphasises stability, truth and inner clarity—qualities that remain unchanged regardless of external fluctuations. His teachings explain that real security comes not from technological leadership but from understanding the eternal path shown in our scriptures.
At a time when industries experience turbulence and rapid change, this spiritual wisdom provides a grounded perspective, reminding humanity that lasting peace arises only through true devotion and the pursuit of the Supreme God.
A Turning Point for the Global AI Power Race
The revelations from Sam Altman’s memo mark a defining turning point for OpenAI. For the first time, the company publicly acknowledges that Google’s Gemini 3 has taken the lead, enterprise demand is cooling, and internal development challenges require urgent correction. Yet this moment of vulnerability may also serve as the catalyst for renewed focus. With the Shallotpeat model under development and long-term research bets intensifying, OpenAI is positioning itself for a comeback — one that could significantly reshape the future trajectory of the AI race.
FAQs on Sam Altman’s Internal Memo and Google’s Gemini 3 Lead
1. What did Sam Altman reveal in the leaked internal memo?
Sam Altman admitted OpenAI faces temporary economic headwinds, rough internal vibes, and intensified competition after Google’s Gemini 3 reclaimed AI leadership across major benchmarks.
2. Why is Google’s Gemini 3 considered ahead of OpenAI?
Gemini 3 leads OpenAI in reasoning, coding, multimodal performance, and benchmark scores, showing Google’s strong progress, especially in the pre-training phase of AI development.
3. What internal challenges is OpenAI facing in model development?
OpenAI is struggling in the pre-training phase, with scaling issues during GPT-5, prompting the development of a new model codenamed Shallotpeat to fix foundational training problems.
4. What financial concerns were raised inside OpenAI?
The memo warned revenue growth could fall to 5–10% by 2026 while long-term projections show a possible $74 billion operating loss due to rising compute and infrastructure spending.
5. How is enterprise demand affecting OpenAI’s growth?
Enterprise enthusiasm is cooling, with Microsoft and Salesforce delaying or reducing AI deployments, contributing to slower adoption and increasing pressure on OpenAI’s business outlook.
