SOBRE ESTE EPISÓDIO

Inglês
Estados Unidos da América

TRANSCRIÇÃO 🔗

PESQUISAR EPISÓDIOS PASSADOS

Pesquisar episódios anteriores de Agentic AI in DevOps.

OUTROS EPISÓDIOS NESTE PODCAST

If you work in data, "semantic layer" means one precise thing: the place where "active customer" or "recurring revenue" gets defined once so every dashboard agrees. If you build agents, the word starts doing two jobs at once — and a second term, "context layer," shows up claiming the same ground. T…
Loop engineering solves the coding-agent babysitting problem by giving DevOps teams a way to run larger tasks with evidence, constraints, and a clear definition of done. Andrey Devyatkin, Vladimir Samoylov, and Fernando Gonçalves unpack outer loops around agents, context-window limits, unattended r…
Loop engineering solves the coding-agent babysitting problem by giving DevOps teams a way to run larger tasks with evidence, constraints, and a clear definition of done. Andrey Devyatkin, Vladimir Samoylov, and Fernando Gonçalves unpack outer loops around agents, context-window limits, unattended r…
GitHub outages and agent-scale workloads are exposing the limits of centralized development platforms—learn where Cursor Origin and Entire could help, and which bottlenecks they cannot fix. Andrey Devyatkin, Vladimir Samoylov, and Fernando Gonçalves examine AI-native Git forges, distributed mirrors…
cmux terminal workflows: when iTerm slows down AI-agent work, Viktor Vedmich shows how workspaces, session restore, and socket APIs make Claude Code more practical. Andrey Devyatkin and Fernando Gonçalves talk with Viktor Vedmich about his terminal-first agentic stack, Obsidian vault setup, Claude …
Aviso: O podcast e a arte incorporada nesta página são de Sirob Technologies, que é propriedade de seu proprietário e não é afiliado ou endossado por Listen Notes, Inc.