Blog
Guides for choosing software, improving workflows, and replacing spreadsheet processes carefully.
10/7/2026
OpenAI released 722 manuscripts in 372 result families from an unreleased internal model, many with Lean proofs. Here is what was published, why mathematicians want receipts, and what it means for R&D teams.
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10/6/2026
Sigma brings continuous diffusion to language modeling at 3B and 8B scale, matching discrete baselines on reasoning and coding while opening new levers for speed and sampling diversity.
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10/6/2026
A new activation-steering defense cuts indirect prompt injection success for open-weights LLM agents while keeping most benign utility. Here is how it works, where it falls short, and what builders should do now.
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Sparse MoE architectures are cutting inference costs while matching dense-model quality. Here's what R&D teams need to know about routing, specialization, and production trade-offs.
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New diagnostic work argues that solution accuracy hides weak discovery skills in large language models. Learn how to probe mathematical primitives and redesign evals and post-training around the real bottleneck.
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New papers on visual harnesses, verified self-evolving optimizers, and long-horizon agents show that infrastructure around the model often matters more than another parameter bump. Here is what product and R&D teams should change this quarter.
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New September 2026 research, including OSWorld-Pro, WorldBench, DualViewEval, and studies on scaffold confounds and LLM-judge drift, shows why agent benchmark scores mislead and how to build evaluations you can trust.
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A wave of late-2026 research, including VERSE, VISTA, harness learning, JAZ, and LatentHarness, shows that much of an LLM agent's capability now comes from the harness around the model. Here is what that means for builders.
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2026 RAG research shows fluent answers can still fail on permissions, stale evidence, and instruction adherence. Here is a practical evaluation checklist for SMB software buyers building AI on top of business systems.
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