Agentic AI in DevOps

Sirob Technologies

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 AI agents. https://www.getboris.ai

  1. 1d ago

    #18 — AI Writes Code. What's Your Job? with Julien Bisconti

    AI writes the code, yet engineers end the day buried in reviews and unsure what shipped. Andrey Devyatkin, Vladimir Samoylov and Fernando Gonçalves talk with Julien Bisconti about reference implementations, review stopping rules, changing harnesses, token spend and the case for combining cloud expertise with industry knowledge. What you will learn: How reusable reference projects make complex agent instructions concreteHow a fixed review limit prevents endless rounds of findingsWhy local agent transcripts can become an overlooked store of credentialsWhy token spend alone cannot establish an engineer's productivityHow business knowledge helps engineers challenge the wrong technical requestMaybe try B.O.R.I.S, our context layer for AI agents: https://www.getboris.ai Episode page, show notes and links

  2. Aug 31

    #17 — DevOps Agents Need Context, Not More Tools

    Your agent can call every tool you give it and still not know which account a service runs in, what depends on it, or what changed last week. So every session starts with the same discovery work. Andrey Devyatkin, Vladimir Samoylov and Fernando Gonçalves get into Grok 4.6 in Cursor, Anthropic's Claude Tag, cloud code review and AI-driven bug bounty noise, and why all four land on the same gap. What you will learn: Why AWS Agent Toolkit gives an agent access, but not orientationWhat a CI reviewer misses when Terraform sits in another repoHow live configuration turns bug bounty noise into provable findingsWhy infrastructure state belongs in a database, not a skills fileWhat it costs to keep your context inside one vendor's memoryMaybe try B.O.R.I.S, our context layer for AI agents: https://www.getboris.ai Episode page, show notes and links

  3. Aug 14

    #16 — How DevOps Makes AI Safe to Scale

    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. Maybe try B.O.R.I.S, our context layer for AI agents: https://www.getboris.ai Episode page, show notes and links

  4. Jul 18

    #15 — Can Origin and Entire Replace GitHub?

    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. Maybe try B.O.R.I.S, our context layer for AI agents: https://www.getboris.ai Episode page, show notes and links

  5. Jul 9

    #14 — Loop Engineering in DevOps

    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 runs, greenfield versus brownfield work, alert batching with SNS and SQS, model mixing, token costs, and why bad code still gets worse when you automate it faster. Episode page (show notes and links): https://getboris.ai/insights/014-loop-engineering-in-devops/

  6. Jun 26

    #13 — cmux vs iTerm with Viktor Vedmich

    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 Code on Bedrock, AWS Kiro, spec-driven workflows, MCP search tools, rising token bills, and why open-weight model competition matters for DevOps teams. Episode page (show notes and links): https://getboris.ai/insights/013-cmux-vs-iterm-with-viktor-vedmich/

  7. Jun 12

    #12 — Semantic Layers, Context Layers, and Agents That Stop Guessing

    Two terms keep colliding in infrastructure AI: semantic layer and context layer. They're not the same thing, and conflating them is how teams end up with agents that understand vocabulary but have no idea what's actually running — or agents that know the environment but still guess wrong about what the data means. Episode page (show notes and links): https://getboris.ai/insights/012-semantic-layers-context-layers-and-agents-that-stop-guessing/

  8. Jun 5

    #11 — Base of Record for Intelligent Systems

    The hosts of Agentic AI in DevOps make the case that the "second brain" idea — long a personal-productivity meme — is exactly what AI agents need to be useful inside a real engineering environment. Without a system of reference, the agent burns its context window rediscovering what is running where, hallucinates the gaps, and needs credentials it should not have. The episode also marks a pivot: B.O.R.I.S is no longer pitched as a replacement DevOps engineer, but as a context layer for engineering systems — and the acronym now stands for Base of Record for Intelligent Systems. Fernando Gonçalves rejects pure RAG as enough on its own (the relationships are what matter), Andrey Devyatkin turns "do you take notes?" into a hiring question, and the half-hour closes with a token-maxing post-mortem and the reminder that you can outsource the legwork to agents but not the decisions. Episode page (show notes and links): https://getboris.ai/insights/011-base-of-record-for-intelligent-systems/

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About

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 AI agents. https://www.getboris.ai

Information

  • Creator
    Sirob Technologies
  • Years Active
    2026
  • Episodes
    18
  • Rating
    Clean
  • Copyright
    © 2026 Sirob Technologies OÜ
  • Show Website
    Agentic AI in DevOps

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