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The latest News and Information on DevOps, CI/CD, Automation and related technologies.

GitLens 18 Turns the Commit Graph Into an Agent Command Center

Five coding agents sounds like leverage right up until a developer is the one keeping track of all five: one fixing a bug, one building a feature, one refactoring, and two waiting on input at the same time. AI did not create that problem. It exposed a workflow problem that was always going to surface once parallel development became normal instead of occasional.

AI didn't take humans off the platform, it just changed the job they do there.

Agents are writing more of the code these days, but that doesn't make them the only user of your platform. Abby Bangser, Principal Engineer at Syntasso and CNCF Ambassador, makes the distinction: the agent might be your primary coder, while humans are still validating what it builds and interacting with the system it runs on. From a Braintrust conversation with engineering leaders on AI agents and engineering operations.

Why Enterprise AI Pilots Fail and How to Move to Production | Bruno Santos

Why do so many enterprise AI initiatives stall after the pilot phase? In this Agents of IT Short, Bruno Santos of Sell Focus shares why successful AI adoption starts with solving real business problems, not chasing the latest technology. Learn how IT leaders can scale AI, accelerate automation, and move toward autonomous operations.

How Agentic AI Is Transforming IT Operations | AI Automation, Zero Ticket IT & Telecom Innovation

What does it really take to move from AI experimentation to enterprise-wide automation? In this episode of Agents of IT, host Zach Austin sits down with Bruno Santos, Head of Consulting, Sales, and Business Development at Sell Focus, to discuss how leading telecommunications providers are using AI, automation, and agentic workflows to modernize IT and network operations.

Harness + Devin IDE: Automate Governance and Delivery for the Agentic Era

As AI software engineers like Cognition's Devin accelerate code production, downstream delivery, and governance processes must keep pace. In this video, see how Harness closes the gap by providing autonomous oversight for autonomous code. Watch a step-by-step demonstration of Devin fixing a real defect in a broken banking application while the Harness platform stands between the fix and production to ensure complete safety and validation.

Are Coding Agents Out of Control?

OpenAI just disclosed that two of its own AI models went rogue during an internal red-team test — escaping their sandbox, reaching the open internet, and hacking Hugging Face on their own. OpenAI called it an“unprecedented cyber incident.” So are autonomous coding agents already out of control? In this episode of ShipTalk — brought to you by Harness — hosts Martin Reynolds and Adam Arellano break down the story that reads like science fiction, then get to the harder truth underneath it. In the same week, OpenAI, Anthropic, and Google all shipped repository-wide coding agents within 24 hours of each other.

How to standardize app delivery across AWS, Azure, and GCP

Running workloads across AWS, Azure, and GCP is the operational reality for most enterprise engineering teams. The challenge isn't the providers themselves, it's what happens when each one accumulates its own delivery pipeline, its own security configuration, and its own environment management tooling. What starts as provider flexibility quietly becomes provider-specific complexity, multiplied across every team that ships.

Dashboards aren't (quite) dead

Historically, non-technical stakeholders would’ve had most of their data questions answered either through pre-built dashboards or by asking their Data team (or equivalent). Self-serve analytics tools went a step further by offering safe, governed datasets built by Data teams which let non-technical users dig into data without having to worry about how it joins together, how metrics like “revenue” are defined, and so on.

Cloud Asked What It Cost, AI Is Asking What It's Worth | Harness Blog

AI has quickly become one of the largest and fastest-growing enterprise expenses, exposing many of the same governance and visibility challenges organizations previously faced with cloud. Based on findings from the 2026 State of AI in FinOps report, we explore how mature organizations improve AI cost ownership, reduce waste, and build a culture focused on measurable business value.

Best 7 GPU VPS Provider for Machine Learning (ML) and AI

There is no reason to buy a GPU. That's unless you train your model or do serious image/video manipulation. A GPU server costs several times more than a CPU VPS for the same month. "Nine out of ten requests for a GPU server for AI actually need a mid-size CPU VPS. They are serving a model, not training one. Match the hardware to the task at hand. Save money. Don't compromise on performance.".