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Nov 3
How-toBuildersSelected08:37
Legora CTO Jacob Lauritzen on Building Legal Agents Without Viewing Client Data

Testing an agent you are never allowed to observe is a concrete engineering constraint most teams have not faced, and Legora's approach offers patterns applicable to any privacy-bound deployment in healthcare, finance or law. Developers building client-facing agents can borrow these methods to design evaluation pipelines that respect data boundaries. It also signals how confidentiality requirements shape product architecture in professional-services AI.

Official accountLatent Space (swyx)@Latent.SpaceSource
ProductsBuildersMulti-sourceSelected08:22
llm 0.37 adds GPT-6.1 models and OpenAI-compatible endpoint command

The maintainer's workflow treats AI-assisted pull requests as bug reports with attached examples, offering a working model for open source projects drowning in low-quality contributions. Developers using the CLI gain cheaper default inference and a one-command path to any OpenAI-compatible API, which is handy for wiring in regional providers or self-hosted endpoints alongside OpenAI models.

Event
Official accountSimon Willison’s WeblogSource
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How-toBuildersOfficialSelected01:28
Circle K cut DevOps incident triage to 15 minutes with Amazon Bedrock

The migration from Bedrock Flows to AgentCore shows where low-code orchestration hits its limits and when a managed agent runtime pays off — a decision many platform teams will face. DevOps and platform engineers building their own triage or on-call automation can reuse the architecture pattern and scaling lessons directly. The under-15-minute triage figure gives a concrete benchmark for setting internal targets.

Event
Primary sourceAWS Machine Learning Blog@Marek KlatowiczSource

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