When does one AI agent stop being enough?Many enterprise AI applications begin with a simple architecture:User → LLM → AnswerAs applications become more capable, the pattern usually evolves into: User → Agent → Tools → AnswerNow the agent can decide ...
I read about a team demo about their shiny new "autonomous AI agent” leadership. It queried databases, generated reports, sent Slack notifications—all hands-free. Impressive stuff. Two weeks later? $12K in API costs, staging data accidentally pushed ...
This project, AgenticLakehouse, explores the cutting edge of "Agentic Data Analytics." I didn't just want a chatbot; I wanted a "living" interface for the Lakehouse. The result is a Multi-Agent System that intelligently orchestrates tasks, from query...
Looks great, solid LangGraph + MCP setup on Databricks Apps. Thanks for sharing, @vinaygazula!
Many enterprises today launch AI agents with high hopes but more often than not, those pilots never reach production. The culprit? Complexity, poor evaluations, ballooning costs, and governance gaps.Why do so many AI agent pilots never make it to pro...
Agent Bricks looks solid for scaling AI, and I’ve seen platforms like Agentra.io also tackle the enterprise workflow side of this challenge.
