Signal
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WDSF 2026 results are on record — 10 awards · 11 winnersSee the record →
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What’s moving in agentic workstations and workflows — drawn from a reviewed source list, scored, and kept at a permanent address you can cite.
Curated and full layers · newest first · scored, sourced, citable
The ledger as a map. Dashed edges are machine-suggested (embedding similarity and duplicate clusters); solid edges are editorial — they appear only where a blog post cites an entry.
Raw data: signal-graph.json
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3 entries in the curated layer matching the current filters
A Thoughtworks Distinguished Engineer shares hands-on experiences running small language models locally on M3 Max (48GB) and M5 Pro (64GB) machines for agentic coding, covering hardware, model choice, runtime, harness, task outcomes, and conclusions.
Firsthand practitioner report on what actually happens when you run local models for agentic coding, with specific hardware specs and task-level results worth weighing before buying a machine.
OpenAI and Broadcom announce Jalapeño, a custom AI inference chip designed to improve performance, efficiency, and scalability for large language model inference workloads.
Primary-source announcement of a custom LLM inference chip from OpenAI and Broadcom. Useful for infrastructure planning; less directly relevant to individual workstation setup.
Chips and Cheese conducts an independent technical analysis of Nvidia's GB10 integrated GPU, examining its microarchitecture, performance characteristics, and design tradeoffs in Nvidia's large iGPU effort aimed at AI workstation use.
Few outlets run their own low-level benchmarks on unreleased or niche AI silicon. Useful reference for evaluating Digits-class workstations before purchase.
