209 summarised stories about Agent Infrastructure, each linking back to the original source. Browse all topics →
Product Hunt 3 months ago 40
Atlaso is a software platform that lets users maintain a single unified memory profile across multiple AI assistants and applications instead of managing separate memory systems for each tool.The platform integrates with various AI services to centralize user context and preferences in one place.This eliminates the friction of re-explaining preferences and context to different AI tools by providing consistent personalization across the entire AI ecosystem.
The New Stack 3 months ago 25 ● 4 sources
AI agent reliability problems stem from insufficient infrastructure around context management, tool retrieval, and execution guardrails rather than model capability limitations. Teams building production agents must implement compiled context layers that structure organizational knowledge (Karpathy's wiki reached 100 articles and 400,000 words), hypothetical-invocation matching for tool selection instead of semantic similarity, and execution isolation layers that validate every tool call before it reaches downstream systems. The differentiator between reliable and unreliable agent systems is investment in context plumbing, observability, continuous evaluation against production data, and configuration management—not upgrading to smarter models.
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24 October 2026
AI’s dominant theme today is accountability at scale: as agents get more autonomous, companies are doubling down on verification, sandboxing, and evidence—because “it worked once” is no longer good enough. Anthropic reports its merged code changes jumped from about 2,500 per day in May to over 30,000 by September as it rolled out agentic “software factory” workflows, but the growth depends on building a fast, high-fidelity verification “sensor” so agents don’t outrun what tests can actually validate. In parallel, Anthropic open-sourced its @anthropic-ai/sandbox-runtime, an OS-level sandbox (no containers) that reportedly cut internal Claude Code permission prompts by 84%—a practical nod to how real agent deployments are constrained by risk controls, not ambition.
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