Operations | Monitoring | ITSM | DevOps | Cloud

Bring Your Playwright Suite to Harness: No Rewrites, No Infrastructure, AI-Powered Triage Built In | Harness Blog

Key Takeaway: Harness AI Test Automation now runs existing Playwright suites without code changes, adds AI-powered failure triage, and integrates test results directly into build and deployment pipelines. ‍

The AI Agent Accountability Gap: Why Network Policies, API Gateways, And RBAC Are Not Enough

In The Five Pillars of AI Agent Accountability: A Diagnostic Framework for Engineering Leaders, we walked through each pillar of AI agent accountability (traceability, authorization provenance, identity and ownership, policy at scale, and human oversight) and argued that most enterprises today sit at Level 0 or Level 1 of the Accountability Maturity Model. The most common reaction we get when we share that framework is some version of: “We’re already covered. We have network policies.

Let AI Run Your Cloud Infra? Ex-VMware & SAP Architects Weigh In. (ft. TechWorld with Nana)

Can you trust AI to run your platform? AI can now spin up production infrastructure in minutes — but speed cuts both ways. In this episode, Nana(TechWorld with Nana) sits down with Doron Grinstein and Dan Wilson, two architects who built, broke, and fixed platforms at VMware and SAP, for a no-hype look at platform engineering in the age of AI.

AI in Insurance Claims Operations: Where Automation Delivers Real ROI

Traditional insurance claims operations are under immense pressure to change. What has shifted now is the margin for delayed results. Today's customers demand faster updates on claims, while insurers need more robust ways to detect sophisticated fraud patterns. The problem is, simply adding more people isn't a sustainable solution when teams are already dealing with complex documentation. Where most insurers rely on legacy systems that involve endless manual handoffs and document-heavy processes, the modern pace requires a change.

Top 5 AI-Powered Database Query Tools for Data Analysts

Data analysts spend a large part of their workday translating business questions into database logic. A stakeholder asks why revenue changed. A product manager wants to compare cohorts. A finance team needs a variance explained. The question may sound simple, but the path to the answer often involves finding the right tables, understanding how fields are defined, writing SQL, validating joins, checking filters, and making sure the result matches the intended business meaning.

AI-Powered Quality Control Is Changing Sustainability Reporting in Construction

Sustainability reporting is becoming a critical requirement across the construction industry as regulators, developers, and procurement teams demand more accurate environmental data from manufacturers. Environmental Product Declarations (EPDs), once considered optional documentation, are increasingly being used as a deciding factor in major construction tenders and compliance evaluations.

AI Might Break Open Source Differently Than You Think

AI coding agents may not replace open source libraries overnight. But Adam Arellano, Field CTO at Harness, thinks models like Mythos could expose a bigger problem: finding bugs, vulnerabilities, and edge cases faster than maintainers can keep up. That might be the real threat to tools and libraries.

Ameet Talwalkar on Building the AI Research Lab

"We're doing cutting-edge AI, focused on real translational impact: getting our research over the wall and into production." Ameet Talwalkar, Datadog's Chief Scientist, shares what it took to build the AI Research Lab from the ground up — and what makes DAIR different from traditional research teams. At Datadog, research ships. Recent work from the lab includes Toto 2.0, open-weights time series forecasting models ranked on leading benchmarks, and ARFBench, a new benchmark for evaluating AI on real incident data.