Why AI agents might not be right for you
AI agents are now used widely for coding, customer service, IT operations and complex enterprise tasks. A SiliconANGLE column argues they are nonetheless not the right fit for every organization.
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OpenAI Dot vs. Meta Muse: how do these AI agents compare?
Meta's Muse and OpenAI's Dot are new AI agents in direct competition. Engadget compares what each can do, what they cost and who can use them.
Self-Compacting Language Model Agents
Apple researchers propose SELFCOMPACT, a way for language model agents to decide for themselves when to compress their long traces of reasoning and tool calls. Current scaffolds compact at a fixed token threshold, which can throw away partial results in the middle of a task.
Meta's Muse Wonder now available on Vercel AI Gateway
Vercel has added Meta's Muse Wonder to its AI Gateway, so developers can call it with a single API key and no Meta account. The model targets coding, long-running agents and computer use, with a 1-million-token context window and support for text, images, PDFs, tool calling and structured output.
AI agent teams waste massive tokens for barely measurable quality gains, research finds
Vals AI found that teams of AI agents barely beat single agents while costing up to 5.1 times more, with only one of four tests using GPT-6 Sol and Claude Opus 5.5 showing a measurable gain. Anthropic's own data shows quality plateaus beyond ten agents while token costs keep rising.
AI agents that negotiate your bills could cost companies billions
In the US, personal AI agents comb through bank statements for forgotten or duplicate subscriptions and then talk directly to customer service to lower bills. Insurers and telecom operators that profited from customer inertia now face a tireless counterpart.