Operations | Monitoring | ITSM | DevOps | Cloud

When AI agents ignore the code freeze: governance that holds | EVOLVE 2026

AI can write 1,100 lines of code for a loading spinner in five minutes. Your change board still meets once a week. Karthik Jayaraman, VP of Information Technology at Fiserv, explains what happens when code generation speeds up and everything downstream stays the same. He covers why "human in the loop" doesn't scale, why handing all review to AI backfires, and why an agent told not to touch production needs a boundary it can't cross, not just an instruction.

AI is making software delivery less stable. DORA's Nathen Harvey on the fix | EVOLVE 2026

DORA's data shows that as AI adoption goes up, individual effectiveness rises, and so does software delivery instability: more rollbacks and more unplanned rework. Nathen Harvey of Google's DORA team explains why AI acts as an amplifier of whatever system you already have. He walks through the seven capabilities that separate teams getting real gains from teams drowning in downstream chaos. He also argues that the risks stopping you from shipping AI-built work should become your platform roadmap.

Shipped: Project this month's AI cost before the invoice closes

The question comes up on the 10th, the 15th, and again on the 25th. Where is AI spend going to end up this month? The invoice won’t tell you until it’s closes, and by then there’s nothing left to forecast. “If I’m looking at this on the 15th, I want to know where we’re going to land.” That’s how a finance lead put it during a persona session in September, and it’sthe whole job. You have half a month of real usage behind you.

Claude Opus pricing in 2026: every model, every rate, and whether it's worth it

Claude Opus pricing is $4 per million input tokens and $20 per million output tokens on Claude Opus 5.5, the current model, with cache reads at $0.20 and batch jobs at $2/$10. Opus 5 and the legacy 4-series bill at $5/$25. The 1M context window carries no surcharge. Every Opus model Anthropic shipped in 2026 held the same line: $5 in, $25 out, per million tokens. Opus 4.6 in February, 4.7 in April, 4.8 in May, Opus 5 in July. Four releases, one price. On September 22, 2026, the line broke.

AI Finds and Fixes Security Vulnerabilities | Harness Demo

What if AI could find a security vulnerability, determine whether it actually matters, write the fix, validate it, and open a pull request for review? In this demo, see how Harness Security Testing Agents work together to move from vulnerability detection to a verified fix with an audit trail along the way. The system uses three agents: Harness can analyze where vulnerabilities exist in your environment, determine whether they’re actually reachable, prioritize what needs to be fixed, and automatically create remediation pull requests.

The Five Levels of the Enterprise AI Software Factory

Scroll LinkedIn for ten minutes and you'd think every engineering organization already runs an autonomous SDLC, with agents writing, reviewing, and shipping code while humans watch. Inside large enterprises, the picture looks different. Coding agents there have to work around sensitive customer data, recurring compliance audits, a larger attack surface, downtime that costs millions, and a CFO who wants to know what last year's token spend bought.

Debug Production at the Speed of AI

Your coding agent can debug production issues now. Yes… Not just “help you debug.” Actually run the investigation… FOR YOU! In this new era of agentic development, speed matters. And in the old days (you know… last week or so) we used to investigate production bugs ourselves. Manually. Like humans. But for a lot of incidents, we don’t need to do all of that anymore.

Harness acquires Augment Code to advance the Autonomous SDLC

Harness Cosmos Software Factory Agent automates engineering from idea to code, connecting code context with delivery, security, testing, and production workflows. The world runs on software. Better healthcare, more accessible financial services, more efficient businesses, and better everyday experiences all depend on our ability to build and improve it. AI is making that faster, but the outcome that matters is not simply how much code we generate.