Research

AI resistance shows which part of the work system is still missing: purpose, role, skill, environment, accountability, or flow. This guide begins where diagnosis ends. If an area is red, open the relevant section and choose 1–2 actions for the next sprint. People’s positions are not personality types. The same person can be an advocate in one scenario, a productive skeptic in another, and an avoidant participant in a third. The source of resistance shows what needs to be fixed. A person’s position shows how to act. ...

Агенты уже вошли в разработку. Из каждого утюга слышно: AI пишет код, закрывает pull request, помогает с тестами, ускоряет ревью. Команды внедряют IDE-ассистентов, agentic workflows и внутренние инструменты для миграций, тестов, code review и анализа репозиториев. Метрики процесса начинают шевелиться: выше throughput, быстрее отдельные задачи, больше автоматизации вокруг delivery pipeline. Дальше включается старая продуктовая экономика. Если команда быстрее пишет код, она может быстрее выкатывать фичи. Если быстрее выкатывает фичи, она может запускать больше A/B-тестов. Если запускает больше A/B-тестов, чаще находит прибыльные гипотезы. Значит, AI должен привести к большему количеству денег. ...

This page documents the full methodology behind the Deep Research Benchmark. What Are We Comparing? Three fundamentally different approaches to AI-powered research: Perplexity Deep Research — a black-box hosted service (sonar-deep-research). You send one prompt, it autonomously plans, searches, reads, iterates and synthesises. ~50 sources, 2-5 minutes. Extended Search Pipeline — a custom 7-step pipeline where we control every stage. Each step is a separate LLM call in a separate sub-agent. Full transparency, full control. Single-Agent Pipeline — the same 7 steps, the same prompts, but executed in one continuous session without spawning sub-agents. Context grows, but there’s zero spawn overhead. We also tested optimisations (cheap models, lightContext, minimal steps) that turned out to be dead ends. ...

Having worked in the sound recognition field in mobile space (bird sounds) I know about this hard process a bit. Mostly I was using predefined algorithms and just implemented them in c#, but my poor knowledge and puny brain would never do such amazing stuff! [youtube=http://youtu.be/Nu-nlQqFCKg] Natural UI comes to life! You can always see that some awesome MS Research powered speech recognition displayed on MS keynotes almost in real-time, but yesterday’s article on The Next Web highlighted the new addition to that wonderful feature: same voice tone speech translation in Mandarin! Check this out! ...