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

AI, Platforms, and the Future of Value Delivery: A Conversation with ServiceNow

How do enterprises turn AI from experimental potential into real-world software delivery value — without slowing down, breaking security, or sacrificing reliability? At {unscripted} 2025, Amit Zavery — President, Chief Product Officer, and COO of ServiceNow — joined Harness CEO and Founder Jyoti Bansal for a candid fireside chat on the future of AI in the enterprise, the role of platforms in unlocking developer productivity, and why"AI-native" only works when speed, security, and reliability move together.

Cursor Cloud Agents Are Incredible - Until You Need Production Governance

Cursor Cloud Agents are the best AI coding environment for individual developers. But for enterprises that need AI-written code to ship through staging to production with audit trails, RBAC, and compliance - there's a gap. Romaric founded Qovery to make Kubernetes accessible to every engineering team. He writes about platform strategy, developer experience, and the future of cloud infrastructure.

What cloud portability actually means and how to achieve it

Takeaway: Having workloads on two clouds is not the same as being able to move workloads between them freely. Portability is about the friction of movement, not the number of providers in use. Most teams that call themselves multicloud are not portable. They have separate workloads siloed on separate providers, each with its own toolchain, deployment pipeline, and set of operational conventions. Moving anything between those environments means starting from scratch. That is not portability.

The "Free" AI Tool That Will Ruin Your Code#speedscale #aiagents #aicoding #devops #softwareengineer

Relying on AI and interns to build custom traffic replay tools is a scalability nightmare that introduces security risks, brittle code, and massive maintenance costs...use Speedscale instead. Learn more: speedscale.com.

There's an npm-shaped hole in the AI tooling stack

I've had this same conversation with 60+ engineering teams in the last six months. A team adopts AI tooling. One developer figures out how to use it well, builds up a vault of skills, MCP configs, and slash commands that 10x their output. The rest of the team has whatever they can scavenge from a shared Notion doc.

Why agentic AI development needs reliability guardrails

AI has massively accelerated code deployment. In fact, since the introduction of agentic coding, GitHub has seen exponential growth in PRs, commits, and new repos. What they originally predicted would require 10X capacity, they’re now estimating it’s going to require 30X capacity, and the biggest driver is agentic development. Companies across industries are building agentic pipelines to ship features faster than ever before. That acceleration isn’t without risk.

Anthropic Shipped An Enterprise Analytics API. We Shipped the Claude Adapter Today.

Anthropic just shipped an Enterprise Analytics API with user-level token and cost data. Today, we're shipping the CloudZero adapter that maps that data to teams, budgets, and cost centers — so Claude spend gets the same accountability as the rest of your stack. Anthropic released the first beta of its Enterprise Analytics API this week. Admins can pull token usage and dollar cost through a programmatic endpoint, broken down by user, model, context window, region, and product surface.

Teamwork Collection - Power the era of human-AI collaboration | Team '26 | Atlassian

As organizations work to bring humans, agents, and automation together, teamwork is getting even more complex. If your AI strategy feels like a collection of one-off experiments layered onto disconnected tools and siloed knowledge, join Atlassian leaders to see how Teamwork Collection brings together Jira, Confluence, Loom, and Rovo into a connected foundation for human-AI collaboration at scale.