DevOps Agent Kit for Trustworthy AI Answers

I have spent the better part of twenty years in marketing, watching every major platform shift go through a similar cycle. Mobile. Cloud. Containers. SaaS. The thing we are all living through now with AI. The pattern repeats every single time, and it is almost embarrassing how predictable it is. The teams that move early, who connect their tools to the new substrate before everyone else, end up with a compounding advantage that the late majority never catches up to. The teams that wait for the dust to settle find out the dust never settles, it just moves somewhere else. Agents are becoming the new interface for software delivery. That is no longer a prediction, that is a deployment decision you are either making or avoiding. The real question is whether your agent can see your pipelines, or whether it is still writing code in a vacuum while your team runs the same forty-minute scavenger hunt every single Friday afternoon. The DevOps Agent Kit gives you the scaffolding to stop running that scavenger hunt. Clone it. Connect it to the tools you already have like Anthropic Claude or Cursor. Make it yours. Then tell us what you built, because we genuinely want to see the skills your team comes up with once they start treating the whole pipeline as a first-class input to the agent. We are at the beginning of something big here!

The CloudBees vision is to continuously redefine what’s possible with software. Software delivery infrastructure and best practices are constantly being redefined with AI entering, and altering, every step of then cycle. Cloudbees Unify is designed to layer visibility and control across the cycle, acknowledging each customer’s stack and needs are different, while context-switching and release firefighting... not so much 🙃 Today is a big day, showing the power behind this architectural design. Build your DevOps agent and check it out; it’ll redefine what you think and know about shipping software. #agenticdevops #redefinesiftware #unify A shoutout to the dream team Georginia Schutte, PMP, CSM Shafiq Shivji Raj Sarkar Liz Ryan Ashley Sawatsky Johanie Marcoux Renee Gangnath Peter Winfield Kaila Chen and many more!

Two out of three developers who rely heavily on AI coding tools say AI-generated code causes deployment issues more than half the time, according to the State of DevOps Modernization 2026 Report. The more frequently teams use AI coding tools, the faster they deliver code — but it increases pressure on their delivery systems and staff. 📊 The full report from Harness lays out what this all means for modern DevOps teams: https://lnkd.in/erD_Qywm

Two out of three developers who rely heavily on AI coding tools say AI-generated code causes deployment issues more than half the time, according to the State of DevOps Modernization 2026 Report. The more frequently teams use AI coding tools, the faster they deliver code — but it increases pressure on their delivery systems and staff. 📊 The full report from Harness lays out what this all means for modern DevOps teams: https://lnkd.in/dBdvhFTZ

Two out of three developers who rely heavily on AI coding tools say AI-generated code causes deployment issues more than half the time, according to the State of DevOps Modernization 2026 Report. The more frequently teams use AI coding tools, the faster they deliver code — but it increases pressure on their delivery systems and staff. 📊 The full report from Harness lays out what this all means for modern DevOps teams: https://lnkd.in/gfr6BdBF

AI coding tools are undeniably speeding up development, but the rest of the delivery process is lagging behind. The 2026 State of DevOps Modernization Report from Harness compiles insights from 700 engineers, revealing that while AI is solving many challenges, it's also introducing new ones. 📄 Dive into the full report to explore AI's impact on DevOps: https://lnkd.in/eYu9PZNx

76% of DevOps teams added AI to their pipelines last year. The DORA report says some of them got worse, not better. Turns out AI code generation without automated testing is just shipping bugs faster. We wrote a DevOps tools guide that skips the 50-tool listicle format. Each tool is explained by pipeline stage, with picks by team size and a section on what AI tooling is actually ready for production. Come on, read it. https://lnkd.in/djg-kGv8

Developers at major enterprises spend 38% of their week debugging, verifying, and troubleshooting AI-generated code. That's two full days every week. Or 95 days a year. In a new article by Adrian Bridgwater at DevOps.com, our CEO Ilan Peleg put it simply, ”To embrace the possibilities offered by AI-accelerated engineering, we must shift runtime visibility left, and give AI agents the live execution data needed to validate code before it ever fails in production.” AI coding assistants generate code in a vacuum. They don't see what happens at runtime, no memory usage, no variable states, no live execution data. Writing blind, it takes 3 redeploy cycles for teams to deploy a single change. Lightrun closes the visibility gap. It combines AI reasoning with live runtime signals to surface root causes and validate fixes in production, in real time. Read the full article here: https://lnkd.in/daPTrTDN

AI agents can take action. That changes everything - and most teams aren't ready for it. That's why we started Humans in the Loop - a video series for engineers and DevOps teams figuring out the agentic AI era without losing control of their systems. The first episode is out. Andrey Devyatkin and Fernando Gonçalves set the stage: what agentic AI actually means, why context is everything in infrastructure troubleshooting, and what tools like Cursor, MCP, Claude Code, and Amazon Q CLI mean for DevOps engineers today. https://lnkd.in/eiSbrP7Y

We are making a series of videos explaining concepts critical to understand when it comes to agentic AI and its application in DevOps. If you are starting up with magnetic AI those episodes are for you. We will transition to more advanced topics as we finish establishing a shared glossary and a common understanding. Stay tuned for more!