Instead of one central AI system doing everything, the model emerging here is many bounded agents operating across teams, channels and tasks.

Qdrant's $50M Series B and version 1.17 release make the case that agentic AI didn't simplify vector search — it scaled the ...

Perplexity announced Computer for Enterprise at its Ask 2026 developer conference, launching a multi-model AI agent with ...

Drug discovery has traditionally been a reductive process—narrowing down, filtering out, and optimizing within established ...

When a worker thread completes a task, it doesn't return a sprawling transcript of every failed attempt; it returns a compressed summary of the successful tool calls and conclusions.

Training standard AI models against a diverse pool of opponents — rather than building complex hardcoded coordination rules — ...

Some roads never relax, and safety can suffer. Commuter corridors funnel workers toward bridges and major employers, which ...

Microsoft is launching Agent 365 and the new Microsoft 365 Enterprise E7 on May 1 to govern and secure enterprise AI ...

To act autonomously and effectively, AI agents need optimized, AI-ready processes and the process data and operational ...

But that instinct can mislead us. AI feels like a bubble because we’re forcing something genuinely discontinuous into a ...

For agents, the value is clearer still: structured JSON output, reusable commands and built-in skills that let models ...

The big headlines on this release are efficiency, with OpenAI reporting that GPT-5.4 uses far fewer tokens (47% fewer on some ...