SOBRE ESTE EPISÓDIO
Claude Code can produce more code than an engineer can comfortably review. Trusting that output takes a repeatable workflow, protected learning time and checks that catch a solution to the wrong problem.
Andrey Devyatkin and Fernando Gonçalves join Kaido Koort to explore agentic engineering training, agent-led specs, validator sub-agents, session handoffs, verification versus validation, and what Claude certifications actually demonstrate.
What you will learn:
- How six Fridays progress from brownfield orientation to parallel agents
- How competing validator sub-agents expose trade-offs before implementation starts
- How transcript-based wrap-ups turn forgotten decisions into actionable issues
- Why verification and validation need separate gates for agent output
- How autonomy, parallelism and skill usage reveal different learning gaps
Maybe try B.O.R.I.S, our context layer for AI agents: https://www.getboris.ai
Inglês
Estados Unidos da América
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PESQUISAR EPISÓDIOS PASSADOS
Pesquisar episódios anteriores de Agentic AI in DevOps.
OUTROS EPISÓDIOS NESTE PODCAST
AI adoption stalls when licenses and quotas replace trust, context, and verification. Fernando Gonçalves and Vladimir Samoylov explain how DevOps makes agentic coding safe to scale through checkable starter tasks, organization-specific context, independent tests, Terraform plans, and deterministic …
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…
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…
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EDITAR
Obrigado por ajudar a manter a base de dados dos podcasts atualizada.
