- Популярные видео
- Авто
- Видео-блоги
- ДТП, аварии
- Для маленьких
- Еда, напитки
- Животные
- Закон и право
- Знаменитости
- Игры
- Искусство
- Комедии
- Красота, мода
- Кулинария, рецепты
- Люди
- Мото
- Музыка
- Мультфильмы
- Наука, технологии
- Новости
- Образование
- Политика
- Праздники
- Приколы
- Природа
- Происшествия
- Путешествия
- Развлечения
- Ржач
- Семья
- Сериалы
- Спорт
- Стиль жизни
- ТВ передачи
- Танцы
- Технологии
- Товары
- Ужасы
- Фильмы
- Шоу-бизнес
- Юмор
Build the ultimate AI stack today! 💪 #programmer #ai #coder
➡️ Try Skywork — GPT-Image-2, Nano Banana 2 & Pro in one place → https://skywork.ai/p/6gxfVj
Use code ATEFATAYA for 20% off
The agent found 88% dead code in a repo used by millions. It remembered what it found. It improved its own score from 62 to 92 in one retry. Here is how it works.
Series finale of The Context Layer. This video wires all four cognitive layers into one complete agent built from scratch — Skills (Depwire), Episodic Memory (Neo4j), Semantic Memory (in-memory cache), and Evaluation (LLM-as-judge).
The agent analyses real codebases. Demo targets: honojs/hono and drizzle-team/drizzle-orm. Real dependency graph data, real health scores, real cross-repo comparison across sessions.
WHAT YOU'LL BUILD:
→ Skills layer — Depwire CLI wired as agent tools
→ Episodic memory — Neo4j with full-text index, timestamped findings
→ Semantic cache — in-memory Map with TTL for stable facts
→ Evaluation layer — LLM-as-judge, threshold 70, retry with feedback
→ Complete agent loop — all five steps connected
Видео Build the ultimate AI stack today! 💪 #programmer #ai #coder канала Atef Ataya
Use code ATEFATAYA for 20% off
The agent found 88% dead code in a repo used by millions. It remembered what it found. It improved its own score from 62 to 92 in one retry. Here is how it works.
Series finale of The Context Layer. This video wires all four cognitive layers into one complete agent built from scratch — Skills (Depwire), Episodic Memory (Neo4j), Semantic Memory (in-memory cache), and Evaluation (LLM-as-judge).
The agent analyses real codebases. Demo targets: honojs/hono and drizzle-team/drizzle-orm. Real dependency graph data, real health scores, real cross-repo comparison across sessions.
WHAT YOU'LL BUILD:
→ Skills layer — Depwire CLI wired as agent tools
→ Episodic memory — Neo4j with full-text index, timestamped findings
→ Semantic cache — in-memory Map with TTL for stable facts
→ Evaluation layer — LLM-as-judge, threshold 70, retry with feedback
→ Complete agent loop — all five steps connected
Видео Build the ultimate AI stack today! 💪 #programmer #ai #coder канала Atef Ataya
Комментарии отсутствуют
Информация о видео
21 мая 2026 г. 22:19:44
00:00:37
Другие видео канала





















