Insights on DevOps automation,
trust, and infrastructure AI
Practical thinking for teams building and running real systems
This is where BORIS shares what we learn from building context-aware DevOps AI.
No hype cycles. No vendor fluff. Just thoughtful perspectives on automation, reliability, and knowledge preservation.
From Frustration to Product: The Story of B.O.R.I.S
How a broken experience with AI CLI tools led us to build an AI DevOps teammate that actually knows your infrastructure.
We're a small team of DevOps engineers who built an AI teammate that actually knows your infrastructure. This is the story of how B.O.R.I.S came to be.
Read
#3 — Skills, Powers, SOPs
Agent skills sound like magic until someone uploads malware to the public hub.
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.
#2 — The Tool Layer: What Makes Agentic AI Possible
Context windows, MCP overhead, and why micromanaging your AI agent makes it worse.
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.
#1 — AI in DevOps, 2022 to 2026: From Autocomplete to Action
How AI went from clever autocomplete to agents that can act on your infrastructure — and why context is the missing piece.
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 Humans in the Loop, 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.