As AI-assisted coding becomes more common, a new pattern is emerging: multi-agent workflows. A multi-agent workflow refers to using various AI agents in parallel for specific software development life ...
Stanford's DeLM lets AI agents coordinate without a central controller, cutting multi-agent inference costs 50% and beating SWE-bench baselines by 10.5%.
Target Multiplai 2026 will spotlight multi-agent AI, bringing industry and academia together to discuss enterprise deployment ...
AI coding agents from OpenAI, Anthropic, and Google can now work on software projects for hours at a time, writing complete apps, running tests, and fixing bugs with human supervision. But these tools ...
Latest IBM Bob Updates Help Enterprises Deliver Production-Ready Software FastIBM Bob is Built to Optimize the Cost of AI-Driven Development Beyond the ModelIBM Bob Now Offers Pre-Built, Customizable ...
As artificial intelligence (AI) becomes more common in health care, from managing records to assisting with medication decisions, researchers at the Icahn School of Medicine at Mount Sinai are asking ...
CyberGym benchmark scores over time, showing the rapid improvement in AI vulnerability discovery capabilities. Microsoft’s multi-model MDASH system (top right) tops the leaderboard at 88.4%. (CyberGym ...
Paulo Arruda discusses Shopify’s evolution in AI adoption, moving from simple chat tools to a sophisticated swarm of specialized agents. He explains the transition from massive "all-in-one" prompts to ...
We just can’t seem to help ourselves. Our current infatuation with multi-agent systems risks mistaking a useful pattern for an inevitable future, just as we once did with microservices. Remember those ...
Multi-agent orchestration makes workflow more inspectable, with clear handoffs and a QA backstop. Breaking the work into discrete steps makes the output easier to audit and fix. A timestamped handoff ...
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