EA’s ReefGPT Backfires: Hallucinating Code Forces Developers to Fix — Costs Rise

Electronic Arts’ much‑touted in‑house AI assistant, ReefGPT, is failing to do the one thing it was supposed to: save time and money. According to a report published Oct. 25 by Business Insider, EA’s generative model has been producing erroneous code and so‑called “hallucinations” that professional developers must manually correct — a process that, in some cases, costs more than the work it was meant to replace. The problems, the report says, have left studio programmers frustrated and reluctant to use the tool. Rather than accelerating development, ReefGPT’s errors are creating new work: engineers spend hours tracking down and repairing AI‑inserted bugs. Some developers told the outlet they worry that by fixing the system’s mistakes they are effectively training a future replacement — a deep anxieity at a company that has already leaned into automation as a route to cost savings. EA first demonstrated its generative tool publicly last year with a staged demo that suggested users could assemble aspects of a game through prompts. The demo drew scrutiny at the time for producing dull, derivative results; the current report suggests the internal reality is far messier. Hallucinations — confident but incorrect outputs — are a known limitation of current large‑language and code models, and the symptoms described mirror problems seen across industries trying to bolt generative AI onto complex, safety‑critical workflows. The timing of the report matters. EA is in the middle of a proposed $55 billion acquisition by a consortium of investors, a transaction that market watchers expect will trigger renewed pressure to cut costs, consolidate studios, and squeeze efficiencies out of development pipelines. That environment makes rapid, risky AI deployment more likely — and potentially more damaging if the technology doesn’t deliver the promised gains. For now, the math looks ugly. The Labor and engineering time spent auditing and rewriting ReefGPT’s output can outstrip the savings of automating lower‑value tasks, company insiders and external observers say. Fixing a generative tool that regularly injects broken code requires investment in model fine‑tuning, guardrails, validation systems, and new testing pipelines — all of which add up. The report also touched on workplace dynamics: developers’ reluctance to rely on ReefGPT stems partly from trust and partly from survival instinct. When a tool produces plausible but wrong code, the burden of proof falls on humans; over time that shifts both the nature of engineering work and the perceived value of senior technical staff. Unions and staff representatives have already raised questions about the buyout’s implications; a widely adopted but unreliable AI assistant would only sharpen those concerns. If the Business Insider account is accurate, EA faces a choice now familiar to tech companies that rushed to deploy generative systems: slow the roll‑out and invest in safety, quality assurance, and integration, or push forward and hope short‑term experimentation yields long‑term payoff. Either path requires money — ironically, the same budgetary pressures that likely motivated a fast AI push in the first place. The broader lesson for the games industry is plain: generative AI can be a force multiplier when tightly constrained to narrow, verifiable tasks, but it remains brittle in complex engineering contexts. For EA and its developers, ReefGPT’s growing bill of work underscores that AI hype rarely translates to immediate cost savings — and that fixing an over‑ambitious AI can be a far more expensive proposition than the feature it was supposed to replace.