At OpenAI, the race to sustain ChatGPT’s edge has ignited a fierce internal rift between its research labs and product teams, culminating in CEO Sam Altman’s dramatic “code red” directive. Sources familiar with the matter describe how reallocating resources from product improvements to cutting-edge model training has left ChatGPT stagnant, even as rivals like Google’s Gemini close in. This tension, brewing for months, risks eroding the consumer product’s momentum at a pivotal moment for the company’s $13 billion 2025 revenue target.

The discord traces back to a subtle but alarming shift: Users stopped noticing—and caring about—increments in ChatGPT’s underlying intelligence. Over the past year, staffers observed that while OpenAI’s research group pushed boundaries in reasoning and multimodal capabilities, everyday ChatGPT interactions yielded diminishing returns for casual users. “Improvements to the underlying AI model’s intelligence—and the in-depth research or calculations it could suddenly handle—didn’t seem to matter to most people using the chatbot,” as noted in recent analysis shared on X by industry observer Stephen Loynd, linking to deeper reporting.

Roots of the Divide

OpenAI’s structure, split between a research division chasing artificial general intelligence and a product group optimizing ChatGPT for mass appeal, has long fostered friction. Insiders told The Information that researchers prioritize breakthroughs in areas like long-context understanding and agentic behaviors, often at the expense of the chatbot’s immediate usability. This misalignment peaked when Altman declared a “code red” in early December, marshaling engineers to bolster ChatGPT amid threats from Google and Anthropic, according to an internal memo reviewed by the publication.

The memo, circulated on December 2, signaled a pivot: Delay advertising rollouts and other initiatives to focus on model behavior and features. Yet, this move exacerbated tensions, as product teams saw resources diverted to research labs already strained by compute shortages and sky-high inference costs. TechCrunch reported on December 8 that despite the alarm, OpenAI touted an enterprise win, with ChatGPT Enterprise usage surging 8x year-over-year, though sustainability questions linger amid competitive pressures.

Revenue Sprint Under Pressure

OpenAI is on track to smash its ambitious $13 billion revenue goal for 2025, driven by enterprise subscriptions and API growth. However, the product’s core consumer base—its revenue engine—shows signs of fatigue. Stephanie Palazzolo of The Information highlighted on X: “What happens when increases in model intelligence don’t benefit your most important, revenue-making product? OpenAI is finding this out the hard way,” linking to a detailed exposé on the fallout.

Fortune delved into the eight-week “code red” frenzy on December 17, portraying Altman as rallying against Google’s resurgence. Silicon Valley’s history of incumbents crushing innovators weighs heavily, with Gemini’s gains forcing OpenAI to accelerate releases like GPT-5.2 for developers, as covered by TechCrunch on December 11. Yet, internal sources reveal product managers pleading for fixes to latency and hallucination issues that plague daily use, per The Information’s reporting.

Strategic Reallocations and Fallout

The code red pulled talent from nascent projects, including AI agents and ad integrations, to refine ChatGPT’s responsiveness. AP News confirmed on December 2 that Altman’s alert aimed to counter mounting competition, but it sidelined product roadmaps. Posts on X from Palazzolo underscore the irony: OpenAI’s research triumphs, like advanced scheming detection, fail to trickle down effectively.

Enterprise adoption offers a bright spot, with workers reporting an hour saved daily, per TechCrunch. Still, cost concerns mount; training frontier models devours resources, and without proportional consumer uplift, margins thin. The Information’s sources describe researchers viewing ChatGPT as a “distraction,” while product leads argue it’s the cash cow funding AGI pursuits.

Competitive Shadows Lengthen

Google’s Gemini 3 looms large, with benchmarks showing parity in coding and reasoning. Search Engine Journal noted on December 2 how Altman’s directive delayed agents to prioritize the chatbot, but Fortune warns of history repeating—first-mover advantages fading against tech giants’ scale. OpenAI’s response includes GPT Image 1.5, launched amid the warpath, promising faster generation, as TechCrunch reported on December 16.

Internally, the strain manifests in talent churn risks. Biztoc aggregated whispers of research-product clashes post-code red, with product teams feeling starved. Reuters on December 2 echoed the memo’s call to improve ChatGPT, delaying ads, but Yahoo Finance highlighted on December 4 how this refocuses amid Anthropic’s rise.

Path to Reconciliation

To bridge the gap, OpenAI must integrate research outputs more seamlessly into products. Insiders suggest dedicated integration squads, echoing Altman’s past research intern goals shared on X in October. The Wall Street Journal’s coverage of the initial code red emphasized urgency, but sustained success hinges on balancing innovation with usability.

Revenue beats provide breathing room—potentially exceeding $13 billion—but user retention demands action. As Loynd posted on X, model smarts alone won’t suffice if ChatGPT feels unchanged. OpenAI’s next moves, from enterprise expansions to consumer refreshes, will test whether it can unify its fractured teams before rivals capitalize.