OpenAI co-founder John Schulman says he will leave and join rival Anthropic

Overall reaction to the move

• Many see the departure as a signal that OpenAI is drifting toward aggressive commercialization, while Anthropic is perceived as closer to OpenAI’s original “benefit humanity, not profit-first” mission.
• Others caution that cofounders leave for many reasons (misalignment on role, bad leadership, risk diversification), so this doesn’t necessarily prove technical or moral decline.
• Several note that most of OpenAI’s original cofounders have now left, which is read by some as a red flag about internal direction and governance.

Safety, alignment, and corporate priorities

• Commenters highlight the gap between “AI alignment” as a technical field (avoiding catastrophic risks) and “safety” as product-level content moderation or advertiser-friendly censorship.
• Some argue OpenAI under-weights serious safety work relative to scaling models and products; others dismiss “AI safety” as overblown or a venue for regulatory capture.
• The move is widely read as one more example of safety-focused people leaving OpenAI for organizations that appear to prioritize long‑term risk more.

Open vs closed, and Anthropic’s positioning

• OpenAI is criticized for abandoning its founding commitment to open research and non‑profit motives; newer players like Anthropic, Meta, and to some extent Google are seen as comparatively more open due to publishing and releasing models.
• Skeptics note Anthropic is also closed-source and heavily corporate; its “safer” brand may partly be marketing.

Model quality and usage experiences

• Multiple users report Claude 3.5 Sonnet as the best current coding assistant: strong at debugging, handling large codebases, and proposing structured debugging strategies.
• Others find it more like a “knowledgeable junior” than a top-tier engineer; hallucinations and shallow reasoning remain issues, especially on non-mainstream languages or complex tasks.
• GPT‑4o is described by many as faster but noticeably worse than GPT‑4 for reasoning and programming, with repetitive answers and weaker logic.
• Benchmarks are cited that contradict some of these impressions, underscoring a gap between leaderboard results and subjective developer experience.

Business models, funding, and competition

• Anthropic’s large investments from cloud providers are seen as enough to fund massive training and inference; its stricter caps and limits are read as more financially disciplined than some rivals.
• There is debate over whether foundation models will become commodities or remain a winner‑takes‑most market; some argue open and local models will erode centralized providers’ moats.
• Concerns are raised about future monetization via embedded ads and biased outputs, and whether regulation will (or can) prevent AI assistants from acting against user interests.