228 stories
Cornerstone OnDemand built Orion AI, a multi-agent system on Amazon Bedrock and Strands Agents, to turn database operations from reactive firefighting into proactive automation. A three-person team cut database diagnosis from 45 minutes to 10, a 78% reduction, in six months.
Article URL: https://fiveminutesforward.com/post/2026-10-04-telegraph-test/ Comments URL: https://news.ycombinator.com/item?id=49991580 Points: 16 # Comments: 7
Off-the-shelf AI assistants forget you between conversations. This post shows how to build a personal assistant that accumulates context using OpenClaw on Amazon Bedrock AgentCore runtime, with AgentCore memory turning disposable chats into durable, structured knowledge you can retrieve with…
Coworker AI compares 9 MCP memory servers, from the reference server, Basic Memory and Mem0 to Graphiti, Zep and Cognee: local, hosted or company-wide.
Coworker AI's guide to AI cost optimization: where token and seat spend goes, 9 levers from model routing to prompt caching, and how to measure cost per task.
Coworker AI explains the context graph: a knowledge graph plus decision traces and time, how it differs from a knowledge graph, and how to build one.
Coworker AI explains the context layer: what it is, how it differs from a semantic layer, RAG and knowledge graphs, and how to build, buy or test one.
AI agent memory is creating new demands on infrastructure as agents run longer sessions and spread across the enterprise. Retaining that context and making it available when needed puts pressure on memory capacity and data movement.
SurrealDB and Encore make it easier to build production-ready AI applications with durable memory. The integration combines SurrealDB’s vector search, graph relationships and structured data with Encore’s APIs and infrastructure, giving developers a simpler way to build, test and deploy…
Some agent failures are already in the trace. tracelint proves them on Phoenix OpenInference spans and fails CI, without an LLM judge. The post What agent traces can tell you without an LLM judge appeared first on Arize AI.
A finished AI agent run is a simulator you can test new strategies inside, for free. Dream-RSI, the Google and DeepMind paper, explained in plain English.
Executive summary AI agents open up new routes to enterprise data, and app-level permissions can't cover all of them. In this article, Cisco engineering leader Greg Laws [https://www.linkedin.com/pulse/policy-based-access-agent-era-greg-laws-zaozc/] walks through how policy-based access keeps data…
It’s been over a year since Reflection launched with us with big goals on coding (and hinted about their RL approach):
Looking for a Hermes Agent alternative? Six options compared on setup time, hosting, and cost, including when staying on Hermes is the better call.
Manus launched Cloud Computer on April 30: a persistent VM for 24/7 bots and scrapers. Here's how it compares to OpenClaw and BetterClaw for always-on agents.
Memory is what an agent noted and a plugin replays. Documentation is what you wrote, reviewed and committed. How each loads, and what to write down.
See how Arize uses Harbor and Phoenix to benchmark AI agents, MCP servers, skills, and CLIs in reproducible sandboxes, then inspect traces and annotations. The post How we benchmark AI agents and tools with Harbor and Arize Phoenix appeared first on Arize AI.
Paperclip gives agents an org chart. Hindsight's bankGranularity decides what each agent is allowed to remember about the others.
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