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How AI-Powered College Quiz Tools Are Changing the Way Students Choose Their Path

Choosing a college major or a career direction used to feel like guesswork for most students. You would talk to a school counselor for fifteen minutes, take a personality test from a textbook, or simply pick whatever your parents or friends suggested. Today, that process looks very different. Many students now start their search with a college quiz match, an online tool that asks a series of questions about interests, strengths, and goals, then suggests majors, career paths, or even specific schools that fit the answers.

Skills as Guardrails: Contributing to Apache Kafka with AI, Without Knowing Every Module

Let me start with something most Kafka contributors think but rarely say out loud: nobody understands all of Kafka. I'm not a core committer and have only contributed a few times, but those contributions I have made have been in part thanks to using coding assistants. There are some issues with this approach though, the Apache Kafka project is huge. It's split into many parts: the core, the server, the client libraries, the streams engine, the storage layer, the consensus code, and more.

What your AI SRE can't see (and what you can do about it)

AI SRE is having a moment. The category pulled in massive funding rounds over the last two years, Gartner published its first market guide, and vendors are promising everything from 90% faster resolution to fully autonomous incident response. If you run an engineering organization, someone has probably pitched you an AI SRE in the last quarter. And let’s be honest: faster triage, less alert fatigue, and automated frontline response are wins for understaffed teams.

Building trusted agentic AI in financial services: From data to autonomous action

As financial institutions move from AI experimentation to autonomous operations, trusted context, governance, and observability become the foundation for enterprise-scale Agentic AI. Artificial intelligence in financial services is entering a new era. Historically, financial services companies have focused on deploying generative AI to improve productivity, enhance customer experiences, accelerate software development, and streamline operations.

Are AI Coding Agents the New CI Bottleneck?

AI coding agents are moving the software bottleneck from writing code to validating it. Here’s what that means for CI infrastructure, capacity planning, and software quality. This topic is explored in more detail in “CI Can’t Keep Up With AI,” an episode of Uplink, where Aditya “JP” Jayaprakash, Co-founder and CEO of Blacksmith, discusses how AI coding agents are reshaping CI and software delivery. Table of Contents.

Kubernetes GPU Scheduling for MLOps and GPU Sharing

The default Kubernetes scheduler was built for stateless services: web servers, APIs, databases. It schedules a pod, checks that a node has enough of whatever resources were requested, and binds it. For CPU and memory, that model works fine. For GPUs, it falls apart in three specific ways. First, GPUs are treated as an opaque integer resource.

AI Provider Outages: An On Call Playbook

On the morning of August 5, 2026, a major AI provider went dark for roughly seven and a half hours, and thousands of engineering teams learned in real time what an AI provider outage actually costs them. Anthropic's Claude models returned elevated error rates and failed API requests starting around 3:00 AM Eastern, and applications that quietly route user traffic through a large language model suddenly had no model to route to. Chatbots stopped answering. Summarization pipelines stalled.