À PROPOS DE CET ÉPISODE
Agents can produce pull requests faster than teams can review them, even while Git stays fast. Hosting platforms face real scaling pressure, but most teams hit other limits first.
Andrey Devyatkin, Vladimir Samoylov and Fernando Piviani examine GitHub, GitLab and Cursor Origin's storage changes, Anthropic's Scion, file APIs that avoid unnecessary clones, and Entire's transcript checkpoints as a way to preserve intent without overlooking secrets and access controls.
What you will learn:
- Why Git hosting scale problems rarely require ordinary teams to migrate
- Which agent lookup jobs can use file APIs instead of clones
- Why short-lived credentials and separate transcript access boundaries matter
- How intent blocks help reviewers assess agent pull requests
- Why faster pushes do not eliminate coordination around a shared ref
Maybe try B.O.R.I.S, our context layer for AI agents: https://www.getboris.ai
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États-Unis
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Rechercher les épisodes précédents de Agentic AI in DevOps.
AUTRES ÉPISODES DANS CE PODCAST
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 …
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…
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 …
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…
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…
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