specialist agents
3 stories filed under specialist agents on Beyond Market Intelligence. The newest of them: “Build a Local Multi-Agent Travel Planner with Hermes and Ollama”, “Choosing the Right AI Agent Shape for Your Data Work”, and “Intuit rebuilt its AI agents twice to find a faster path forward”. Building a local multi-agent travel planner with Hermes Agent and Ollama turns a complex workflow into something you can run on your own machine. Choosing between a single model and a team of agents isn't about picking a winner. 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 specialist agents story on Beyond Market Intelligence, newest first.
Build a Local Multi-Agent Travel Planner with Hermes and Ollama
Building a local multi-agent travel planner with Hermes Agent and Ollama turns a complex workflow into something you can run on your own machine. A coordinator directs three specialist agents: one researches destinations, another suggests stays, and a third generates real Google Flights links. This is practical AI architecture, not a theoretical demo. For more on designing agents that work without costly simulations, see our related piece on smarter AI agents.
Choosing the Right AI Agent Shape for Your Data Work
Choosing between a single model and a team of agents isn't about picking a winner. It's about matching the shape of the tool to the shape of the problem. Codex fits cleanly when the problem is well-defined, Claude Code makes more sense for open-ended exploration, and splitting five specialist agents across dense AI capacity work handles complex, multi-step tasks. It's a practical, grounded look at decision-making that most teams face too early. If you're weighing similar trade-offs, this offers a clear framework worth exploring.
Intuit rebuilt its AI agents twice to find a faster path forward
Intuit's AI VP, Nhung Ho, admits the company's path to agentic AI was messy: they scrapped their architecture twice in four months. The first failure came from an orchestration layer where natural language handoffs between agents compounded errors. Ho's team rebuilt on a skills-based system in 60 days, proving the pivot with real customer queries. It's a candid lesson in embracing failure as the fastest route to something that actually works.