Agentic AI in DevOps

Insights on applying agentic AI to DevOps and software development automation, by practitioners at Sirob Technologies — the team behind B.O.R.I.S, the context layer for infrastructure. https://getboris.ai

Agentic AI in DevOps is a technology podcast hosted by Sirob Technologies, with 20 episodes on record and a Required Pod Score of 80.

Sirob Technologies hosts Agentic AI in DevOps, a technology show with 20 episodes published.

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  Episode #20

  #20 — Become an Agentic Engineer with Kaido Koort

  Sep 24, 2026—

  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 Episode page, show notes and links

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  Episode #19

  #19 — AI Doom Can Wait. Your Security Alerts Can’t

  Sep 17, 2026—

  Security alerts keep piling up while AI doom dominates the headlines. LLMs can help sort the queue, but useful triage depends on evidence, limited access and spending controls. Andrey Devyatkin, Vladimir Samoylov and Fernando Gonçalves discuss GuardDuty findings, live AWS policies, read-only permission traps and tool guards, explaining why assisted investigation and batch analysis should come before unattended agents. What you will learn: How batching a week of alerts reveals rules worth tuning Why a CI/CD escalation finding needs live policy evidence Why ReadOnlyAccess can expose S3 objects and DynamoDB data How tool guards catch calls that IAM policies still allow Why separate invocation limits cannot cap spending across repeated triggers Maybe try B.O.R.I.S, our context layer for AI agents: https://www.getboris.ai Episode page, show notes and links

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  Episode #17

  #17 — DevOps Agents Need Context, Not More Tools

  Aug 30, 2026—

  DevOps agents can call every tool and still miss what is running in production; a portable context layer gives reviews, security triage, and automation evidence they can trust. Andrey Devyatkin, Vladimir Samoylov, and Fernando Gonçalves connect Grok 4.6 in Cursor, Claude Tag, cloud code review, and AI-driven bug bounty noise to the same orientation tax. They explain why live infrastructure state belongs in an automatically refreshed database rather than skills or vendor memory, and how owning that context improves accuracy, cost control, and portability across agent platforms. Episode page (show notes and links): https://getboris.ai/insights/017-devops-agents-need-context-not-more-tools/

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  Episode #16

  #16 — How DevOps Makes AI Safe to Scale

  Aug 13, 2026—

  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 gates—while exposing why token metrics, AI-written tests, and advisory Markdown can create false confidence. Episode page (show notes and links): https://getboris.ai/insights/016-how-devops-makes-ai-safe-to-scale/

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  Episode #15

  #15 — Can Origin and Entire Replace GitHub?

  Jul 17, 2026—

  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, API and Actions limits, repository sovereignty, and whether Git is even the real constraint. They weigh agent-scale throughput claims against human review, CI, internet bandwidth, and the token cost of best-of-N agent fleets, asking whether teams need to leave GitHub or simply reduce their dependence on it. Episode page (show notes and links): https://getboris.ai/insights/015-can-origin-and-entire-replace-github/

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