Learn how to build interactive AI evaluation reports in .NET to communicate model quality, boost transparency, and engage your team.

Using the JNI to call native code from Java

When building AI applications with LLMs, many teams are still "vibe testing" their way to production. This guide shows how file-based prompts and comprehensive test scenarios build reliable review analysis systems that handle real-world complexity, allowing you to build a solid set of repeatable automated regression tests.

Examples of calling native code from several modern languages

LLMs produce non-deterministic outputs, making traditional exact-match testing ineffective. How can you verify an application response is contextually accurate when the response can vary with every request? Let's take a look at promptfoo!

When an unexpected pause disrupts a project, getting back on track can be harder than it seems. In this post, we share lessons from our own two-week project interruption, the challenges we faced on resuming work, and 7 practical steps for regaining momentum—from strong leadership alignment to rebuilding team connection and purpose. These strategies can help any team recover faster, stronger, and with greater resilience.

In this post we'll about why browser-based performance testing is critical for your business, and we'll explore how to use Lighthouse for browser-based performance testing, focusing on Core Web Vitals and actionable insights to improve user experience.

A review of Aspire for JavaScript, an orchestration framework for polyglot applications, including current state, personal experiences, and future aspirations.

A look at the recently published Aspire roadmap for 2025, focusing on its code-first DevOps evolution, polyglot aspirations, and AI orchestration, and more.

Discover how GitHub Copilot Agents can function as AI developers on your team, automating development while complementing human developers' strategic skills.