Agentic AI in DevOps

Sirob Technologies
  • 0.0(0개의 평가)
  • 과학 기술
  • 매주 업데이트

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

에피소드

  1. 3일 전

    #6 — The Big AI Squeeze

    LLM subsidies are drying up, subscription limits are tightening, and the astronomical data center CapEx has to be paid by someone — spoiler: it is you. In this episode, Fernando, Andrey, and Vladimir tackle what they call "the big squeeze": the two-sided pressure of rising AI costs and emerging local-inference technologies that could reshape how teams budget for and deploy AI. Along the way, they debate whether buying a Mac Mini is a rational investment or just hype, reveal the mental gymnastics required to get meaningful work out of a twenty-dollar subscription, and argue that if your AI vendor has no pricing page, that tells you everything you need to know about their business model. Episode page (show notes and links): https://getboris.ai/insights/006-the-big-ai-squeeze/

  2. 4월 17일

    #5 — Stop Your Agent Before It Breaks Prod

    Imagine your agent just deleted a production database — could you have stopped it? The hosts argue that yes, three lines of bash in a single hook could have prevented it, and yet most teams have never configured one. In this episode, Andrey, Vladimir, and Fernando pull apart the agentic loop — the repeating cycle of reason, act, observe that makes coding agents appear to "think" — and show exactly where hooks slot in to give humans deterministic or automated harness-level control over non-deterministic AI behavior, depending on the hook type. Along the way, they unpack Anthropic's rapid-fire release week (Managed Agents, Routines, Opus 4.7, and the advisor tool pattern), debate whether LLM provider commoditization is real or an illusion, and warn that the same hook mechanism that protects your infrastructure can be weaponized through supply chain attacks. Episode page (show notes and links): https://getboris.ai/insights/005-stop-your-agent-before-it-breaks-prod/

  3. 4월 13일

    #4 — Harness Engineering: What Claude Code Accidentally Taught Everyone

    A packaging mistake exposed Claude Code's full source tree to the world — and instead of scandal, the community got a masterclass in how agentic coding tools actually work under the hood. In this episode, Andrey, Vladimir, and Fernando unpack what the disclosure revealed about the engineering behind coding agents, introduce the emerging discipline of "harness engineering," and argue that the model is only the horsepower — it is the harness that determines whether the agent gallops toward the right destination or off a cliff. Along the way, they weigh in on NVIDIA's OpenShell sandboxing, Cursor 3.0's agent-first interface, and why Docker containers are not the security blanket many DevOps engineers assume them to be. Episode page (show notes and links): https://getboris.ai/insights/004-harness-engineering-what-claude-code-accidentally-taught-everyone/

  4. 3월 30일

    #3 — Skills, Powers, SOPs

    What happens when your AI coding tool quietly starts billing like a cloud service — and your team burns through a thousand dollars in a week? Vladimir returns as the hosts share their sticker-shock moment with Cursor's new pricing before diving into agent skills. From Claude Code skills to Kiro Powers to AWS Strands SOPs, the naming varies but the idea is the same — plugging structured knowledge into an agent's brain on demand. Episode page (show notes and links): https://getboris.ai/insights/003-skills-powers-sops/

  5. 3월 23일

    #2 — The Tool Layer: What Makes Agentic AI Possible

    What happens when your AI coding assistant forgets what it was just working on? Andrey and Fernando dive into the mechanics of context windows, reveal how MCP servers can silently eat 20-30% of your session before you even type a message, and explain why treating your AI agent like a micromanaged junior developer actually makes it perform worse. Episode page (show notes and links): https://getboris.ai/insights/002-the-tool-layer-what-makes-agentic-ai-possible/

  6. 3월 17일

    #1 — AI in DevOps, 2022 to 2026: From Autocomplete to Action

    What if most of the AI tools promising to revolutionize DevOps are doomed to fail because they only see a fraction of the picture? In this first episode of Agentic AI in DevOps, Andrey and Fernando walk through a timeline of AI tooling from ChatGPT's launch in late 2022 through the breakthrough year of 2025, arguing that context is king and that tools without full access to source code, logs, metrics, and documentation will inevitably hallucinate their way to irrelevance. Episode page (show notes and links): https://getboris.ai/insights/001-ai-in-devops-2022-to-2026-from-autocomplete-to-action/

  • 6개의 에피소드

소개

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

정보

  • 제작진
    Sirob Technologies
  • 방송 연도
    2026년
  • 에피소드
    6
  • 등급
    전체 연령 사용가
  • 저작권
    © 2026 Sirob Technologies OÜ
  • 웹사이트 보기
    Agentic AI in DevOps

좋아할 만한 다른 항목