Restemb
Predict employee burnout weeks before it shows up
What it does
Restemb sends your team a short daily check-in (30 seconds) and surfaces patterns that point to burnout — weeks before anyone notices. Individual answers stay always private. Unlike weekly surveys or calendar metadata tools, daily data density lets Restemb model each person's risk trajectory and predict a burnout event 4–6 weeks in advance. Managers see team-level signals only. Individual data is never exposed — enforced at the data layer, not just the UI.
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Dev tools · May 2026 · kilo.ai
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Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
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Dev tools · May 2026 · github.com