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

How to Ship AI-Generated Code to Production

AI writes code. But shipping to production? That still takes a software engineer. In this GitKon talk, Chris Kelly from Augment Code breaks down what it actually means to use AI-assisted development to write production-ready code, not vibe code. If you've been using AI coding assistants and wondering why the output doesn't always make it past code review, this is for you. Chris covers: Key takeaway: The engineers who will thrive aren't the ones who let AI do everything. They're the ones who know how to review, direct, and architect around what AI produces.

Q1 2026 Product Update: Harness Pipeline | Harness Blog

The first quarter of 2026 introduces eight major pipeline orchestration enhancements that accelerate development, simplify validation, and strengthen governance. Execute pipelines from Git tags for immutable versioning, leverage AI to author OPA policies without Rego expertise, and gain complete visibility into queued pipelines across your account.

7 Best Practices to Improve Digital Employee Experience in Modern IT Environments

Digital employee experience isn’t just a nice to have anymore. In hybrid, SaaS heavy IT environments Digital Employee Experience (DEX) is where productivity can live or die. Employees don’t care whether the culprit is Wi‑Fi connectivity, CPU/RAM load, poor battery life, or a misbehaving cloud app. They just know work got harder.

Q1 2026 Product Update: Harness Continuous Delivery & GitOps | Harness Blog

The first quarter of 2026 introduces AI-powered continuous verification that eliminates configuration overhead, expanded deployment platform support including Azure Container Apps and enhanced Windows capabilities, and GitOps workflow improvements that align with how teams actually ship software.

Introducing Harness Release Orchestration: Enterprise Release Management, Reimagined | Harness Blog

Enterprise releases spanning multiple services, teams, and environments demand more than spreadsheets and manual coordination. Harness Release Orchestration provides a unified framework for modeling, automating, and tracking complex releases with complete visibility from planning through production deployment.

Founder keynote: Human-AI collaboration at scale | Team '26 | Atlassian

It’s time to reimagine teamwork for the AI era. Join Atlassian leaders to hear how human-AI teams collaborating in one system of work will propel your entire organization forward. About Atlassian: Behind every great human achievement, there is a team. From medicine and space travel to disaster response and pizza deliveries, we help teams all over the planet advance humanity through the power of software. Our mission is to help unleash the potential of every team.

Why database ownership is so fragmented in 2026 - and what you can do about it

In today’s cloud-driven, multi-platform environments, answering the simple question - who owns that database? - is no longer straightforward. As teams adopt open-source tools and spin up cloud services on demand, ownership is becoming fragmented across development, operations, and data teams. This shift is accelerating innovation but also creating new challenges in visibility, control, and accountability, as Grant Fritchey explains.

How a Marketing Intern Ended Up Running Claude in a Terminal

Before I ever ran Claude in my terminal, I thought I already understood AI tools pretty well. Like most people, I had used ChatGPT, Google Gemini, and Perplexity for everyday tasks. Such as helping with schoolwork, organizing ideas, summarizing information, or getting through something faster when time was tight. They were useful, but they still felt separate from how real work happened.

The paved road to production: what good internal developer platforms look like

When was the last time you asked a developer if they actually use the platform you built for them, or whether they’ve found a faster way around it? We talk with companies every day who deal with this exact scenario. They spend months or even years building their IDP. Then a new project requires a stack or workflow that the IDP doesn’t support. The developer is under pressure to deliver, so they spin up their own solution. This is why most IDPs fail quietly.