{"data":{"id":"b0682a61-33d6-4497-9b32-efe7d2f4f590","title":"Model routing is a fix for AI overspending. That's a problem for OpenAI and Anthropic","summary":"Companies are implementing model routing, a technique that directs simple tasks to cheaper AI models and complex tasks to expensive ones, to control skyrocketing AI costs. This shift is forcing major AI providers like OpenAI and Anthropic to reconsider their business models, since they previously earned revenue from all queries regardless of task complexity, but now may only get paid for the most difficult work that requires their most powerful models.","solution":"Model routing is presented as the emerging solution: according to the source, routing is a tool that matches the job to the model, sending hard problems to expensive frontier models (advanced, state-of-the-art AI systems) and easy ones to cheaper, faster alternatives. The article also mentions that Cognition announced an AI productivity guarantee, where if their Devin agent delivers less engineering value than a customer pays for, Cognition will fund usage up to $10 million until performance improves, framing this as a way to measure return on investment (value delivered) rather than just activity metrics like tokens consumed.","labels":["industry"],"sourceUrl":"https://www.cnbc.com/2026/06/05/model-routing-on-ai-is-a-problem-for-openai-and-anthropic.html","publishedAt":"2026-06-05T17:06:49.000Z","cveId":null,"cweIds":null,"cvssScore":null,"cvssSeverity":null,"severity":"info","attackType":[],"issueType":"news","affectedPackages":null,"affectedVendors":["OpenAI","Anthropic"],"affectedVendorsRaw":["OpenAI","Anthropic","Cognition","Devin","Glean","Cisco"],"classifierModel":"claude-haiku-4-5-20251001","classifierPromptVersion":"v3","cvssVector":null,"attackVector":null,"attackComplexity":null,"privilegesRequired":null,"userInteraction":null,"exploitMaturity":null,"epssScore":null,"patchAvailable":null,"disclosureDate":"2026-06-05T17:06:49.000Z","capecIds":null,"crossRefCount":0,"attackSophistication":"moderate","impactType":null,"aiComponentTargeted":null,"llmSpecific":true,"classifierConfidence":0.85,"researchCategory":null,"atlasIds":null}}