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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.

Measure the real impact of AI coding tools on software delivery with Datadog AI Impact

Engineering teams have rapidly adopted AI coding tools, but organizations still struggle to understand their impact. Existing dashboards focus on activity, such as daily active users, acceptance rates, or lines of generated code, but these metrics don’t answer a more important question: Are teams actually shipping more, faster, and with fewer issues?

Run your first microbuild in 5 minutes

AI coding agents produce code faster than most teams can validate it. Without a validation step between the agent and CI, every problem gets caught after the push, and feedback arrives long after the agent has lost context. Agents need consistent feedback while they’re working so that small failures get fixed locally and CI stays focused on moving code into production.

Building a Defensible AI Compliance Framework

Organizations have moved past theoretical conversations about AI adoption. Models, agents, and autonomous workflows are entering production environments. Business leaders are optimistic about potential gains in efficiency, decision support, and operational scale. Yet beneath this momentum, compliance and risk teams feel a different pressure.

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.