diff --git a/Business/Nate Corpus/2026-05-18_there-are-4-kinds-of-agents-and-youre.md b/Business/Nate Corpus/2026-05-18_there-are-4-kinds-of-agents-and-youre.md
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+---
+title: "4 типа агентов: как выбрать нужный"
+source: "https://natesnewsletter.substack.com/p/there-are-4-kinds-of-agents-and-youre"
+author: "Nate Jones"
+date_published: "2026-03-25"
+date_processed: "2026-05-18"
+type: video
+slug: there-are-4-kinds-of-agents-and-youre
+themes:
+  - "[[Agentic Workflow]]"
+  - "[[Implementation Layer]]"
+  - "[[Workflow Completion]]"
+frameworks:
+  - "[[Coding Harness]]"
+  - "[[Dark Factory]]"
+  - "[[Auto Research]]"
+  - "[[Orchestration Framework]]"
+terminology:
+  - "[[Decomposition]]"
+  - "[[Specification-as-Code]]"
+  - "[[Handoff Contract]]"
+  - "[[Evals]]"
+---
+
+# 4 типа агентов: как выбрать нужный
+
+> "The word 'agent' has become the 'cloud' of 2026. Everyone uses it. Almost nobody means the same thing."
+> *«Слово "агент" стало "облаком" 2026 года. Все его используют. Почти никто не имеет в виду одно и то же.»*
+
+## Суть
+
+Существуют **четыре архитектуры агентов**, которые используют один и тот же термин, но решают принципиально разные задачи. Ошибка в выборе архитектуры — это не просто техническая проблема, это потеря квартала. Рынок агентов: $8 млрд в 2025 → $50+ млрд к 2030 (MarketsandMarkets, BCC Research).
+
+## Четыре архитектуры
+
+| # | Тип (RU) | Тип (EN) | Суть | Принцип работы |
+|---|----------|----------|------|----------------|
+| 1 | [[Coding Harness\|Кодовый обвяз]] | Coding Harness | Агент внутри IDE, пишет/правит код в паре с разработчиком | [[Decomposition\|Декомпозиция]]: задача разбивается на тест → реализация |
+| 2 | [[Dark Factory\|Тёмная фабрика]] | Dark Factory | Автономный производственный конвейер без участия человека в цикле | [[Specification-as-Code\|Спецификация как код]]: поведение определяется тестами и контрактами |
+| 3 | [[Auto Research\|Авторесёрч]] | Auto Research | Замкнутый исследовательский цикл: сбор → синтез → вывод | [[Evals\|Метрика + барьер]]: метрика качества + guardrail |
+| 4 | [[Orchestration Framework\|Оркестрационный фреймворк]] | Orchestration Framework | Координация нескольких агентов (CrewAI и подобные) | [[Handoff Contract\|Контракт передачи]]: явные интерфейсы между агентами |
+
+## Один диагностический вопрос
+
+TBD — статья за пейволом. Судя по структуре: вопрос разделяет задачи по типу артефакта на выходе (код / данные / решение / скоординированное действие).
+
+> Открытый вопрос: **что именно является "правильным вопросом" по Nate?** Стоит выяснить из полного текста.
+
+## Ключевые ошибки (анти-паттерны)
+
+- Использовать [[Dark Factory|тёмную фабрику]] для написания романа (творческая задача ≠ производственный конвейер)
+- Тянуться к [[Orchestration Framework|оркестрационному фреймворку]] для задачи, которую решает один агент с хорошим тест-сьютом
+- Направлять [[Auto Research|авторесёрч]] на написание нового ПО с нуля — *"like pointing a profiler at an empty file"* / *«как запускать профайлер на пустом файле»*
+
+## Принципы управления (по архитектуре)
+
+| Архитектура | Управляющий принцип | Что ломается без него |
+|-------------|--------------------|-----------------------|
+| [[Coding Harness]] | [[Decomposition]] | Агент не знает, где остановиться |
+| [[Dark Factory]] | [[Specification-as-Code]] | Нет верифицируемого определения "готово" |
+| [[Auto Research]] | Metric + Guardrail | Бесконечный цикл без критерия выхода |
+| [[Orchestration Framework]] | [[Handoff Contract]] | Агенты теряют контекст на стыках |
+
+## Карта практиков (Karpathy–Lütke–StrongDM–DocuSign)
+
+TBD — за пейволом. Судя по упоминанию: каждый из них применяет **разные** архитектуры под разные задачи и не путает их между собой.
+
+> Открытый вопрос: **какую архитектуру использует каждый из четырёх и почему именно её?**
+
+## 3 диагностических промпта (структура)
+
+По описанию из анонса:
+1. **Классификатор** — определяет, к какой из 4 архитектур относится задача
+2. **Тест готовности** — проверяет, готова ли команда/процесс к выбранной архитектуре
+3. **Детектор несоответствия** — ловит mismatch до того, как он стоит квартала
+
+Конкретные формулировки — TBD (пейвол).
+
+## Терминология
+
+| RU | EN | Пояснение |
+|----|-----|-----------|
+| [[Coding Harness\|Кодовый обвяз]] | Coding Harness | Агентная IDE-среда (Cursor и подобные) |
+| [[Dark Factory\|Тёмная фабрика]] | Dark Factory | Автономный производственный пайплайн |
+| [[Auto Research\|Авторесёрч]] | Auto Research | Замкнутый исследовательский агентный цикл |
+| [[Orchestration Framework\|Оркестрационный фреймворк]] | Orchestration Framework | Координация нескольких агентов (CrewAI и др.) |
+| [[Specification-as-Code\|Спецификация как код]] | Specification-as-Code | Поведение системы задаётся тестами/контрактами, не документами |
+| [[Handoff Contract\|Контракт передачи]] | Handoff Contract | Явный интерфейс между агентами в мультиагентной системе |
+| [[Decomposition\|Декомпозиция]] | Decomposition | Разбиение задачи на верифицируемые шаги |
+
+## Что использовать для нашего портфеля
+
+**Контекст**: AI-интегратор, [[Implementation Layer]], [[Implementation Fabric]], [[Business Object|бизнес-объекты]], PE как канал.
+
+**Coding Harness** — инструмент разработки нашей команды, не продукт для клиента. Cursor/Claude Code для ускорения [[Harness|внутреннего харнесса]].
+
+**Dark Factory** — наиболее релевантна для клиентских внедрений: автоматизация повторяющихся операционных процессов (обработка документов, [[Systems of Record|обновление систем записей]], [[Workflow Completion|завершение рабочих процессов]]). Ключевое требование: наличие [[Specification-as-Code|спецификации как кода]] — без этого фабрика не верифицируема.
+
+**Auto Research** — применима в due diligence (PE-канал): автоматизация сбора и синтеза данных по портфельным компаниям. Требует чёткой метрики качества на выходе.
+
+**Orchestration Framework** — актуальна при построении [[Implementation Fabric|имплементационной ткани]] для клиентов со сложными интеграциями. Риск: без [[Handoff Contract|контрактов передачи]] системы разваливаются на стыках агентов.
+
+> Открытый вопрос: **есть ли у нас внутри уже примеры каждого типа, и правильно ли мы их называем?** Терминологическая путаница из статьи — это риск и при продаже, и при сдаче.
+
+## Связанные заметки
+
+- [[Agentic Workflow]]
+- [[Forward Deployed Engineer]]
+- [[Evals]]
+- [[Frontier Labs]]
+- [[_Thesaurus MOC]]
\ No newline at end of file
diff --git a/Business/Nate Corpus/2026-05-18_there-are-4-kinds-of-agents-and-youre.transcript.md b/Business/Nate Corpus/2026-05-18_there-are-4-kinds-of-agents-and-youre.transcript.md
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+You're using the wrong kind of agent. Here's the one question that tells you which one you actually need + 3 diagnostic prompts
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+You're using the wrong kind of agent. Here's the one question that tells you which one you actually need + 3 diagnostic prompts
+Dark factories aren't coding tools. Auto research isn't a dark factory. If those distinctions don't mean anything to you yet, don't worry — we'll get there.
+Nate
+Mar 25, 2026
+∙ Paid
+131
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+Share
+There are four kinds of agents. Most people think there’s one.
+I hear this confusion everywhere now. Senior engineers evaluating tools. PMs writing roadmaps that say “integrate agentic capabilities.” ICs on Twitter arguing about whether Cursor or CrewAI is “better” — as if that comparison even makes sense. Founders pitching “agent-powered” products without being able to explain what kind of agent they mean. The word “agent” has become the “cloud” of 2026. Everyone uses it. Almost nobody means the same thing.
+I’ve watched someone try to use a dark factory to write a novel. I’ve watched someone reach for CrewAI to solve a coding problem that needed a single agent and a good test suite. I’ve watched someone point an auto research loop at writing new software from scratch — which, if you understand what auto research actually does, is like pointing a profiler at an empty file. There’s nothing to optimize.
+Every one of those people thought they were using “agents.” They were. They just picked the wrong subspecies for the problem, and the reason they couldn’t tell the difference is that every landing page, every pitch deck, every hot take uses the same word to describe four architectures that have about as much in common as a forklift and a bicycle.
+Analysts project the AI agent market will grow from roughly $8 billion in 2025 to over $50 billion by 2030 (MarketsandMarkets, BCC Research). The money is real. The confusion about where to point it is the expensive part.
+Here’s what’s inside:
+The four architectures.
+Coding harnesses, dark factories, auto research, and orchestration frameworks — what each one actually does, who’s using them in production, and what breaks when you pick the wrong one.
+The Karpathy-Lütke-StrongDM-DocuSign map.
+How the people getting this right choose different tools for different problems — and why none of them confuse one architecture for another.
+The one-question test.
+One diagnostic question that cuts through the ambiguity — works whether you’re an IC choosing tools or a CTO setting strategy.
+The operating principles.
+Decomposition, specification-as-code, metric-plus-guardrail, and handoff contracts — one governing principle per architecture that determines whether it works or wastes your quarter.
+The prompts.
+Three diagnostic prompts that classify your problem into the right architecture, pressure-test whether you’re actually ready for it, and catch mismatches before they cost you a quarter.
+The taxonomy matters because the fix for each problem lives in a different place than most people are looking. Let me show you the map.
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+Nate's Notebook
+Welcome to my podcast! In these audio reviews of my newsletters, I am to break down complex AI topics in a way that's approachable and relatable. I want you to walk away with the confidence to leverage AI more effectively at home and at work!
+Welcome to my podcast! In these audio reviews of my newsletters, I am to break down complex AI topics in a way that's approachable and relatable. I want you to walk away with the confidence to leverage AI more effectively at home and at work!
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Auto research isn't a dark factory. If those distinctions don't mean anything to you yet, this article is going to be very useful.\",\"body_html\":\" There are four kinds of agents. Most people think there\u2019s one.
+I hear this confusion everywhere now. Senior engineers evaluating tools. PMs writing roadmaps that say \u201Cintegrate agentic capabilities.\u201D ICs on Twitter arguing about whether Cursor or CrewAI is \u201Cbetter\u201D \u2014 as if that comparison even makes sense. Founders pitching \u201Cagent-powered\u201D products without being able to explain what kind of agent they mean. The word \u201Cagent\u201D has become the \u201Ccloud\u201D of 2026. Everyone uses it. Almost nobody means the same thing.
+I\u2019ve watched someone try to use a dark factory to write a novel. I\u2019ve watched someone reach for CrewAI to solve a coding problem that needed a single agent and a good test suite. I\u2019ve watched someone point an auto research loop at writing new software from scratch \u2014 which, if you understand what auto research actually does, is like pointing a profiler at an empty file. There\u2019s nothing to optimize.
+Every one of those people thought they were using \u201Cagents.\u201D They were. They just picked the wrong subspecies for the problem, and the reason they couldn\u2019t tell the difference is that every landing page, every pitch deck, every hot take uses the same word to describe four architectures that have about as much in common as a forklift and a bicycle.
+Analysts project the AI agent market will grow from roughly $8 billion in 2025 to over $50 billion by 2030 (MarketsandMarkets, BCC Research). The money is real. The confusion about where to point it is the expensive part.
+Here\u2019s what\u2019s inside:
+The four architectures.
+Coding harnesses, dark factories, auto research, and orchestration frameworks \u2014 what each one actually does, who\u2019s using them in production, and what breaks when you pick the wrong one.
+The Karpathy-L\u00FCtke-StrongDM-DocuSign map.
+How the people getting this right choose different tools for different problems \u2014 and why none of them confuse one architecture for another.
+The one-question test.
+One diagnostic question that cuts through the ambiguity \u2014 works whether you\u2019re an IC choosing tools or a CTO setting strategy.
+The operating principles.
+Decomposition, specification-as-code, metric-plus-guardrail, and handoff contracts \u2014 one governing principle per architecture that determines whether it works or wastes your quarter.
+The prompts.
+Three diagnostic prompts that classify your problem into the right architecture, pressure-test whether you\u2019re actually ready for it, and catch mismatches before they cost you a quarter.
+The taxonomy matters because the fix for each problem lives in a different place than most people are looking. Let me show you the map.
+Subscribers get all posts like these!
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