AI Code Review at Scale: What Actually Works | Neeraj Deshmukh, Blitzy | TFiR
AI agents generate hundreds of thousands of lines of code per run, but review processes have not ...
Operational AI for Buildings: From Data to Action | OP Ravi, Willow | TFiR
Facility teams have more faults than technicians and dashboards that never act. OP Ravi of Willow explains ...
How AI Agents Learn Institutional Knowledge | Raviv Levi, CData | TFiR
AI agents cannot absorb the unwritten rules that experienced employees carry. Raviv Levi explains how CData's Connect ...
AI Agents for Data Pipeline Automation | Ian Alton, Airbyte | TFiR
AI agents can now build, monitor, diagnose, and fix Airbyte data pipelines in plain language. Ian Alton ...
AI Agent Governance: Stop Unseen Spend and Risk | Poonacha Kongetira, Classie | TFiR
Learn why 87% of enterprises cannot see what their AI agents are doing, how shadow AI surfaces ...
MCP Migration: What Breaks and How to Fix It | Du’An Lightfoot, Akamai | TFiR
Teams running stdio-based MCP servers face a hard break: no session IDs, no direct migration path, and ...
Semantic Search for AI Agents Explained | Jean Lafleur, Airbyte | TFiR
AI agents cannot reason across meeting notes, customer calls, and documents using keyword search alone. Jean Lafleur ...
AI Agent Routing at the Edge Explained | Dr. Robert Blumofe, Akamai | TFiR
AI agents today use the same centralized model for every request. Dr. Robert Blumofe of Akamai explains ...
Why Enterprise AI Pilots Fail in Production | Leo Brunnick, Cloudera | TFiR
Most enterprise AI pilots fail because governance rules built for humans are never extended to agents, data ...
AI Agent Context: From 65% to 98% Accuracy | Raviv Levi, CData | TFiR
Enterprise AI agents produce wrong answers when business context is missing. Raviv Levi of CData explains how ...
