BA community

🟢 The AI model race is entering a new phase: models now have to compete not only with each other, but also with their own previous versions. A good example is the new Claude Fable 5.1 , released by Anthropic only a few months after Fable 5. https://lnkd.in/p/dWPQbCxn What is especially interesting here is not another benchmark number, but the direction of travel. According to Anthropic’s own evaluations, Fable 5.1 is significantly stronger than its predecessor in agentic coding, knowledge work, and business workflows. At the same time, Anthropic is reducing the cost of using the model: typical workloads are expected to cost around 25% less, while highly agentic workloads may become up to 45% cheaper. It is almost a textbook example of the Red Queen effect from Through the Looking-Glass: you have to run as fast as you can just to stay in the same place. Anthropic has to keep improving Claude to retain users and compete with GPT, Qwen, DeepSeek, and other models. But the same competition is increasingly happening inside each vendor’s own model family: every new version has to justify why users should switch from the previous one. For business and system analysts, Fable 5.1 is interesting not simply as “a smarter chatbot.” The more relevant improvements are in scenarios where AI needs to: - maintain context across long, multi-step tasks; - analyse documentation, requirements, diagrams, tables, and large sets of files; - reconstruct end-to-end workflows across services and codebases; - investigate root causes, verify its own conclusions, and prepare outputs for subsequent human review. One early-access example shared by Anthropic describes the model mapping a change that touched more than eight services across three codebases, tracing the workflow down to individual functions, database tables, and rows. For system analysts, the direction of development here is quite clear. At the same time, the main principle remains unchanged: let’s experiment with new models — but carefully. The more powerful agentic capabilities become, and the more context we provide to AI systems, the more important questions of data classification, retention, access control, and permission to share corporate information become. Anthropic itself is changing its enterprise approach to data retention, but that does not remove the need to verify the policies and settings of your own organisation before uploading requirements, architecture, production logs, customer information, or other sensitive data. 🔵 The price of tokens is falling. The price of a data leak is not. Still, Claude Fable 5.1 is definitely worth testing on safe BA/SA use cases.