Launch HN: Laminar (YC S24) – We trained a model to catch silent agent failures
THE SO WHAT
A dedicated model like flow-1, trained via RL to detect errors in agent traces and matching GPT-6-sol on their benchmark, points to a new layer in the stack—agents watching agents. For teams going agent-heavy, you’ll need observability and meta-models as core infra, not optional tooling.
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MORE FROM THE WIRE
Applied AIPartnering with Blacksmith
If agents can write production-scale code, the new bottleneck is proving that code is safe, performant, and compliant at the same speed. Expect “agent-era CI/CD” vendors like Blacksmith to become a required layer in any serious agent deployment, not a nice-to-have devtool.
Applied AICoreWeave Upgraded to Buy at Goldman on Overblown Debt Worries
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Applied AISources: DeepSeek and Huawei are collaborating on future AI chip designs; DeepSeek plans to start using Ascend 950DT for pre-training as soon as 2026's end
A model lab shaping Huawei’s Ascend 950DT roadmap is a direct attempt to close the loop between frontier training needs and domestic silicon—reducing dependence on US-controlled GPUs. Anyone exposed to China-facing AI demand should assume a more credible non-Nvidia path by 2027 and plan for a bifurcated tooling and optimization stack.