Systems | Development | Analytics | API | Testing

Anthropic recently published research showing that Claude behaves differently depending on the language you use. Not just translating differently. Actually expressing different values. In Arabic, Claude is warmer and more deferential. In English, it's more rigorous and cautious. In Russian, it challenges your assumptions more. When we read that, we had one question: does Kai do this too? So Jordan, our AI lead, analysed around 3,000 internal Kai sessions. The answer: yes.

At some point a product manager or a designer is going to turn to the most user-focused person on the team and say: can you run a usability test on this? That person is usually a manual tester, because manual testers already spend their days thinking about how real people use software.

Almost every infrastructure team running modern AI is wrestling with the same question. The orchestrator their AI workloads want, Kubernetes, and the orchestrator their HPC environment was built on, Slurm, pull in different directions. This piece, drawn from the HPCKP 2026 session of the same name, looks at why that tension exists, what the workloads actually look like, how teams are bridging the two today, and where the pattern is heading.

AI can now handle the slowest parts of test management, inside Jira. – The Zephyr Agent for Rovo creates test cases and links them to your work items, in the projects where your team already plans and builds. This guide covers how testing is changing in the AI age, what the agent is, where to find it, and how to run your first task.

APIs are the backbone of modern software. They connect microservices, power mobile experiences, and make integrations possible across industries. For all their importance, API testing remains one of the most fragmented, manual, and maintenance-heavy parts of the software development lifecycle (SDLC). So as development accelerates in an AI-disrupted SDLC, application integrity – continuous, measurable assurance that your software just works as intended – becomes harder to maintain, not easier.

Claude Code shipped workflows: reusable, versioned instructions an agent can follow instead of improvising a process from scratch each time. We used that feature to hand Claude Code our entire QA job. Not "write a test case." The whole loop: read the requirement, design the coverage, run it on the platform, file the defect, report back with evidence. The kind of work a QE does in a day, compressed into one skill triggered with a sentence.

Ask a Marketing Lead how the quarterly plan actually gets built. Not the strategy, the mechanics. The answer, in most teams, is a spreadsheet: spend pulled from five ad platforms with five different backends, pipeline exported from the CRM, last quarter’s numbers copied from a deck, targets negotiated in a separate thread. One customer described their version of it to us in a sentence that needs no editing.

Shopify’s MCP servers give Claude real command of your store, from storefront conversations to bulk product updates. Analytics is the one job they were never built for, and pairing them with Databox MCP closes that gap.

Implementing a PXM solution provides numerous benefits to your organization, from improving efficiency to increasing sales, reducing returns, and promoting customer loyalty. Today, we’re going to explore these benefits in more detail. Interested in the distinctions between PIM and PXM? See our breakdown of how they differ (but are also similar) here.