Operations | Monitoring | ITSM | DevOps | Cloud

DORA Metrics in the AI Era: Why Deployment Isn't Faster

DORA metrics in the AI era reveal a paradox: PR volume is climbing, but deployment frequency is staying flat. In this talk, GitKraken's Director of Product Jeff Schinella breaks down why AI-accelerated code generation is creating a review bottleneck that your DORA metrics can't fully explain on their own. Jeff walks through how PR metrics (cycle time, first response time, code churn, and PR size) serve as the leading indicators behind your DORA data. If your deployment frequency is flat while PR counts go up, the bottleneck isn't your devs. It's your review capacity.

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.

When your agents hallucinate at 2 am, it is not a model problem

The first time an AI assistant suggests "restart the service" during a live incident and nobody on the bridge can tell whether that suggestion came from a current runbook, a stale wiki page, or thin air, you stop caring about model benchmarks. You start caring about what the agent actually knew, where that knowledge came from, and whether you can trust the chain of reasoning behind it.

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.