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Modern Software Development For Today's Systems & Applications
Build Agentic Workflows: Expose API Orchestration as MCP Tools with Kong AI Gateway
Learn how to expose an API orchestration workflow as an MCP server using Kong AI Gateway, configure semantic guardrails, and build an agent with the Volcano SDK. We onboard GPT-4 behind /llm, orchestrate with DataKit, and debug MCP tools in Insomnia—end-to-end without adding server code.
Best 5 Tools for Monitoring AI-Generated Code in Production Environments
AI-generated code is no longer experimental. It is actively running in production environments across SaaS platforms, fintech systems, marketplaces, internal tools, and customer-facing applications. From AI copilots assisting developers to autonomous agents opening pull requests, the volume of machine-generated code entering production has increased dramatically. This shift has created a new operational challenge: how do you reliably monitor AI-generated code once it is live?
How IP Geolocation Can Help Your Law Firm's Security
Law firms are prime targets for cyberattacks. They handle sensitive client data, confidential case strategies, and privileged communications-information that's highly valuable to hackers and malicious actors. As digital threats grow more sophisticated, traditional security measures like passwords and firewalls are no longer enough on their own.
Confluent for Startups AI Accelerator Cohort-2 (November 2025)
Busie Agentic Driver and Vehicle Scheduling: Intelligent assignment of drivers and vehicles to trips using real-time data on driver location and availability, vehicle utilization, and customer sentiment to optimize efficiency, service quality, and outcomes.
This Is Bad AI Onboarding (w/ Rodrigo Fernandez)
Asking a few questions and dumping data at the end isn’t AI onboarding. It’s lazy. If AI doesn’t actively personalize the product and get users to value faster, it actually hurts trust. Your users notice and they expect more.
Hybrid by Design: The New AI Mandate
For the better part of a decade, the enterprise technology mandate was simple: “cloud first,” or more pointedly “cloud only.” Modernizing meant moving to the public cloud, and on-premises architecture was viewed as legacy infrastructure to be maintained until it could eventually be migrated. Fast forward to today, that narrative has shifted dramatically, with AI as the major catalyst.
From Qlik to Quick: How to Transform Qlik Dashboard Analysis With Hidden Insights AI
The gap between having data and getting actionable insights has always been a challenge in business intelligence. Users face dashboards filled with information but struggle to answer critical questions without exporting to Excel, waiting on developers, or missing key trends hidden in their filtered data. But with technological advancements like natural language AI agents, users can access insights and patterns they might otherwise miss.
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.