Systems | Development | Analytics | API | Testing

Building the Foundation for Responsible Autonomy: Preparing for the Agentic Era of AI

Over the past two years, generative AI has transformed how we create, learn, and interact. But a more profound shift is already underway—one that changes not just how we work but who (or what) does the work itself. We are entering the era of agentic AI, where systems don’t merely answer questions—they reason, decide, and act on our behalf.

Common Kafka Anti Patterns and How to Avoid Them

Kafka is powerful—but common Kafka mistakes can quietly undermine performance, reliability, and scalability. In this video, two OpenLogic experts break down the most frequent Kafka anti-patterns they see in real customer environments—and how to avoid them. Based on hands-on experience fixing production Kafka clusters, this discussion covers: If you’re running Apache Kafka in production—or planning to—this video will help you spot Kafka mistakes early and apply proven best practices to build a more stable, scalable event streaming platform.

Running Kafka in Kubernetes: What We Learned

Apache Kafka is mission-critical for many organizations—but where you deploy it matters just as much as how you use it. In this video, two OpenLogic experts discuss why they increasingly encourage customers to move their Kafka clusters to Kubernetes and utilize the Strimzi operator, and what that shift unlocks from an operational, scalability, and resilience standpoint.

Why AI Agents Need Their Own Identity: Lessons from OWASP's MCP Security Guide

The recently released OWASP, “A Practical Guide for Securely Using Third-Party MCP Servers,” highlights a fundamental challenge in modern AI deployments: how do we govern, secure, and audit systems that are inherently non-deterministic? Unlike traditional, static software, AI agents dynamically adapt their execution paths, tool selection, and decisions based on context and real-time resources, allowing the same agent to achieve identical goals through entirely different approaches.

Best AI Test Case Generation Tools in 2026

AI test case generation tools are transforming how QA teams create, maintain, and execute tests by automating repetitive work and improving coverage. Teams that adopt AI for QA now will reduce manual test creation time while expanding their test coverage. Software testing has always been a balancing act between thoroughness and speed. You want comprehensive coverage, but you also want to ship features before your competitors do.

AI Dev Meetup on Coding Agents with OpenAI and LangChain

Last Tuesday, we kicked off our first AI developer meetup of 2026 with a packed room and over 350 signups! This was our first content-focused event since organizing AI Engineer Paris 2025, and it was a great night bringing the AI dev community together to share ideas and learn from some of the most exciting builders in the space. Want to join next time? Follow our global events calendar to stay in the loop. Our meetup's theme was coding agents. We heard from speakers at Koyeb, OpenAI, and LangChain.

Why AI can't debug your API integrations (yet)

The next generation of debugging doesn’t depend exclusively on the quality of AI models, but it’s heavily dependent on feeding AI tools the context they need to be useful. AI coding assistants have transformed how we write code. For example, GitHub Copilot, Cursor, and ChatGPT can generate Stripe integration boilerplate in seconds. They'll scaffold your payment flow, suggest error handling patterns, and even write unit tests.