Tool selection
2 stories filed under Tool selection on Beyond Market Intelligence. The newest of them: “See Why AI Agents Pick the Tools They Do with Kiji Inspector” and “Choosing Between LangChain and LangGraph for Smarter Agentic Workflows”. Hannes Hapke shows how Dataiku's open-source Kiji Inspector applies Sparse Autoencoders directly to decision tokens, exposing *why* an AI agent picks one tool over another. Choosing between LangChain and LangGraph doesn't have to stall your agentic workflow. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work… The list below is every Tool selection story on Beyond Market Intelligence, newest first.
See Why AI Agents Pick the Tools They Do with Kiji Inspector
Hannes Hapke shows how Dataiku's open-source Kiji Inspector applies Sparse Autoencoders directly to decision tokens, exposing *why* an AI agent picks one tool over another. This moves past superficial chain-of-thought narratives into causal ablation and layer activation extraction. For architects and engineering leaders building production monitoring workflows, it's the kind of transparency that turns agent behavior from guesswork into something you can actually inspect.
Choosing Between LangChain and LangGraph for Smarter Agentic Workflows
Choosing between LangChain and LangGraph doesn't have to stall your agentic workflow. This guide cuts through the overlap to highlight four key differences, helping you match the tool to the task. It's a practical read for anyone tired of guessing which framework fits. We appreciate the clarity here, especially since it complements our earlier exploration of distributed training algorithms. If you're building systems that need structure, start with this breakdown. It's a straightforward step toward more intentional design.