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  1. Presentation: Context Engineering at LinkedIn: How We Built an Organizational Context Layer for AI Agents with MCP

    LinkedIn built a “Contextual Agent Playbooks and Tools” layer that wraps internal services (code search, docs, feature flags, etc.) behind the open‑source Model Context Protocol (MCP). By feeding LLM‑powered coding agents the exact internal artifacts they need, the agents can diagnose incidents, generate PRs, and update incident tickets in minutes, delivering a reported 20 % productivity gain wit…

    InfoQinfoq.com28 mintalk
  2. Laya the open source version of Jev

    Laya is an open‑source, bidirectional‑encoder model family for ultra‑fast, calibrated decision‑making (choice, score, boolean) over structured schemas. It runs 6‑8× faster than the closed‑source Jev, supports 100+ languages via three checkpoints, and includes a lightweight router that selects the appropriate checkpoint before inference. Benchmarks show higher accuracy, far better calibration (ECE…

    Hacker News front pageconvaiinnovations.com8 minreleaseHN1291310lobste.rs2
  3. AWS Lambda Pushes Serverless Toward Long-Running Workloads

    AWS Lambda Managed Instances now allow functions to run up to 90 minutes, six times longer than before, and add Graviton5 support. The longer timeout requires careful handling of connections, credentials, and idempotency, and may shift some workloads from ad‑hoc workarounds to Lambda but also invites cost‑aware alternatives.

    InfoQinfoq.com2 min
  4. Human brain is two separate organs, Stanford Medicine-led research finds

    Stanford researchers discovered that the human brain develops from two separate progenitor lineages—one for forebrain/midbrain (Otx2) and one for hindbrain (Gbx2)—and used this insight to grow functional hindbrain neurons from pluripotent stem cells. This breakthrough provides a platform for studying brain‑stem diseases such as SMA and ALS and reshapes our understanding of brain evolution.

    Hacker News front pagestanford.edu5 minreleaseHN640255
  5. RADAR: Catch gray failures with anomaly detection

    Databricks built RADAR, a four‑stage, metric‑agnostic pipeline that uses streaming anomaly detection (SPOT) to surface gray failures in minutes with >90% precision. The blog shows how to recreate the system on Databricks for any metric, from billing to model drift.

    Databricksdatabricks.com7 min
  6. Serving Markdown for AI Agents, Now as a Jekyll Plugin

    The author turned a one‑off script that rendered each Jekyll page to Markdown and added a `<link rel="alternate" type="text/markdown">` tag into a reusable Jekyll plugin (jekyll‑md). The gem hooks into the build, extracts the main content (defaulting to `<main>` or `[role="main"]`), converts it to Markdown, injects the discovery link, and requires no per‑page front‑matter. Configuration is option…

    Daniel Doubrovkine (dB.)dblock.org2 min