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Testing AI with AI: Why Deterministic Frameworks Fail at Chatbot Validation and What Actually Works | Harness Blog

Chatbots are becoming ubiquitous. Customer support, internal knowledge bases, developer tools, healthcare portals - if it has a user interface, someone is shipping a conversational AI layer on top of it. And the pace is only accelerating. But here's the problem nobody wants to talk about: we still don’t have a reliable way to test these chatbots at scale. Not because testing is new to us. We've been testing software for decades.

AI Didn't Change the Game, It Just Exposed Your Bottlenecks w/ Ganesh Datta (CTO, Cortex)

Every engineering org says they want to improve reliability — but most can't even agree on what "good" looks like. Ganesh Datta, Co-Founder and CTO of Cortex, has spent the better part of a decade helping companies confront that gap.

Why Connected Platforms Will Power the Next Generation of AI in Engineering | Harness Blog

AI is quickly becoming part of the engineering workflow. Teams are experimenting with assistants and agents that can answer questions, investigate incidents, suggest changes, and automate parts of software delivery. But there is a problem hiding underneath all of that momentum. Most engineering environments were not built to give AI the context it needs. In many organizations, the service catalog lives in one place. Deployment data lives in another. Incident history sits in a separate system.

VirtualMetric DataStream - Turn Chaos Into Clarity

Security teams lose time and detection quality to the same root cause: inconsistent, noisy, poorly structured data. VirtualMetric DataStream is a security data pipeline platform that fixes the data layer — so your SIEM, data lake, and analytics tools get clean, normalized, actionable telemetry. What DataStream delivers: The result: reliable security telemetry, faster threat correlation, and stronger detections across your entire stack.

SAS Enhances Security and Compliance with the JFrog Platform

This video features Brett Smith, a distinguished software developer at SAS Institute, discussing how the company secures its software production pipelines for its flagship AI and machine learning platform, SAS Viya 4. SAS initially utilized JFrog Artifactory for managing Java-based Maven and Ivy artifacts. To address the increasing need for robust security and compliance with global regulations, the company expanded its partnership with JFrog by integrating additional security tools to protect their delivery pipelines.

VirtualMetric DataStream: Full setup from scratch in 14 minutes (v1.8.0)

From free trial signup to live security telemetry flowing into Microsoft Sentinel — this demo covers the full DataStream setup end to end, in under 14 minutes. No pre-built environment, no shortcuts. Watch the step-by-step tutorials.

Komodor Provides Autonomous AI SRE Troubleshooting for ClusterAPI

Cluster API (CAPI) is transforming how organizations deploy and manage fleets of Kubernetes clusters by introducing declarative, Kubernetes-style APIs to automate cluster provisioning and lifecycle management. While CAPI excels at creating consistent and repeatable cluster deployments across different infrastructure providers, operating it at a massive scale introduces unique day-to-day challenges.

Export env0 Log Data to SIEM and Monitoring Platforms [2026]

Every time Terraform runs a plan, every time an environment is deployed, every time a variable is changed, env zero generates a record. env zero log forwarding sends that record to your existing SIEM or observability platform automatically. For most teams without it configured, that record lives inside env zero and nowhere else.

7 AI productivity lessons from the CTO of Superhuman

Most companies have built AI into their product by now, and many consider it the central feature of what they’re building. But plenty of those same companies are still figuring out how to get their own engineering teams to actually use AI tools day to day. When Loïc Houssier joined Superhuman as CTO in early 2025, his team was in that exact spot. The company had been shipping AI email features for years, but internal adoption of AI dev tools was still early.