Researchers at Google and MIT have conducted a comprehensive analysis of agentic systems and the dynamics between the number of agents, coordination structure, model capability, and task properties. While the prevailing sentiment in the industry has been "more agents is all you need," the research suggests that scaling agent teams is not a guaranteed path to better performance.Based on their findings, the researchers have defined a quantitative model that can predict the performance of an agentic system on an unseen task. Their work reveals that adding more agents and tools acts as a double-edged sword: Although it can unlock performance on specific problems, it often introduces unnecessary overhead and diminishing returns on others.These findings offer a critical roadmap for dev [...]
Google on Monday unveiled the most significant upgrade to its autonomous research agent capabilities since the product's debut, launching two new agents — Deep Research and Deep Research Max †[...]
Microsoft today announced the general availability of Agent 365 and Microsoft 365 Enterprise 7, two products designed to bring security and governance to the rapidly growing population of AI agents op [...]
Perplexity, the AI-powered search company valued at $20 billion, announced on Wednesday at its inaugural Ask 2026 developer conference that its multi-model AI agent, Computer, is now available to ente [...]
OpenAI introduced a new paradigm and product today that is likely to have huge implications for enterprises seeking to adopt and control fleets of AI agent workers.Called "Workspace Agents," [...]
Jensen Huang walked onto the GTC stage Monday wearing his trademark leather jacket and carrying, as it turned out, the blueprints for a new kind of monopoly.The Nvidia CEO unveiled the Agent Toolkit, [...]
Artificial intelligence agents powered by the world's most advanced language models routinely fail to complete even straightforward professional tasks on their own, according to groundbreaking re [...]
While Silicon Valley debates whether artificial intelligence has become an overinflated bubble, Salesforce's enterprise AI platform quietly added 6,000 new customers in a single quarter — a 48% [...]
Enterprise AI agents today face a fundamental timing problem: They can't easily act on critical business events because they aren't always aware of them in real-time.The challenge is infrast [...]