Systems | Development | Analytics | API | Testing

Why Mocks Fail at Scale #softwareengineering #devops #softwaretesting #api #aicoding

Mocking for testing starts off easy, but once you scale to multiple teams and AI agents, handcrafted mocks become a serious form of technical liability. Instead of treating mocking as an individual software engineering task, shift your mindset to treat it as a platform engineering task focused on automation and continuously refreshed modern data. Watch to see how adopting technologies like traffic replay to simulate realistic backend sandboxes can transform your modern testing workflow!

Ep 90 | Can AI Make Sense of Pharma's Messiest Data?

Human biology is extraordinarily complex, and researchers often have only fragments of information to work with. Brian Martin compares it to looking at a skyscraper through a keyhole: you can see something clearly, but only a tiny piece of the whole. Recorded at EVOLVE26 Singapore, this episode of The AI Forecast brings Paul Muller together with Brian Martin, CTO of Applied AI at Cloudera and co-founder of Rare Hopes NFP, to explore what one of the world’s most data-intensive industries can teach us about AI and decision-making.

Which AI Analyst Holds Up Best for Your Hard Questions?

Analytics vendors claim their AI answers questions accurately, but almost none of them will show you how they checked. The standard move is a percentage with no denominator: "90%+ accuracy on internal benchmarks." No dataset you can download. No scoring method you can inspect. No competitor runs under the same conditions. You're asked to trust the grade without ever seeing the exam1 We ran the exam in public terms instead.

Tideways 2026.3 Release

This Release introduces AI Performance Insights, expanding the Tideways CLI with access to monitoring, exception tracking, Slow SQL, and trace data for agentic performance analysis. We added PHP 8.6 compatibility and improved trace views and instrumentation. We’ve also added a broad range of new framework- and ORM-specific bottleneck detections for Shopware, Magento, Laravel, Symfony, and Doctrine.

Your analytics platform is part of your attack surface

Analytics platforms are built to help organizations understand what their users are doing. Increasingly, they do much more than that: they connect behavioral data with customer context, power personalization, inform automated decisions, and provide intelligence to teams and AI systems. To do this well, analytics needs access to valuable data. That makes analytics more than a measurement layer. It makes analytics part of your security perimeter.

Start your AI agent testing with deterministic tooling

By now everyone is aware of the limitations inherent in generative AI and the AI agents that use it to complete their tasks, and the challenges involved in getting them enterprise quality. If you are planning to incorporate AI agents into your enterprise IT architecture, how are you planning to validate their quality and accuracy?

Sync Your Ometria Contacts Anywhere: Announcing the Integrate.io Ometria Connector

Push customer profiles, orders, products, and custom events into Ometria as they happen, and pull that same data back out into your warehouse or CRM, on schedule, with no engineering required. Ometria is a customer data and marketing platform built for retail and ecommerce brands. Marketing and CRM teams use it to unify customer profiles, track order history, and trigger lifecycle campaigns based on behavior like purchases, browsing, and loyalty status.

Third-Party Risk Assessments | How Confluent Helps You Move Faster with Confidence

Every organization that adopts a cloud platform takes on a shared responsibility: the assurance that its vendors are secure, compliant, and resilient. This is where third-party risk assessments (TPRAs) come in with a systematic evaluation of a vendor's security posture, operational resilience, and compliance standards. TPRAs are a cornerstone of modern security and procurement programs because they provide structured, verifiable evidence of a vendor's security posture.

AI's Impact on Automated Test Script Generation

AI-powered automated test script generation is transforming how software teams approach quality assurance. By analyzing real user behavior, code changes, and system logs, these tools reduce the time and effort needed to create and maintain tests. This shift from manual scripting to AI-generated scripts helps teams keep test coverage in sync with rapid release cycles.