Hey everyone, Morgan here from aidebug.net! Today, I want to dive into a topic that keeps so many of us up at night: those sneaky, frustrating, sometimes downright baffling AI errors. Specifically, I want to talk about the often-overlooked art of debugging when your shiny new AI model starts giving you… well, not what you
Ollama vs TGI: Which One for Startups?
Ollama boasts 165,710 GitHub stars, while TGI (Text Generation Inference) has only 10,812. But, trust me, stars don’t always translate to production power, especially when you’re a startup racing against time and resources. In this showdown, I will break down both tools, showcasing which fits startups better, and
Production Deployment Checklist: 10 Things Before Going to Production
I’ve seen 5 production deployments fail this month. All 5 made the same 7 mistakes. That’s ridiculous and avoidable. If you’re a developer who’s serious about deployment quality, having a solid production deployment checklist is non-negotiable. Without it, you’re just asking for trouble.
The List
1.
Hey everyone, Morgan here, back with another dive into the nitty-gritty of AI development. Today, we’re talking about the ‘F’ word – no, not that one. I mean Fix. Specifically, fixing those maddening, elusive errors that pop up in our AI models when we least expect them. It’s 2026, and while AI has made incredible
Qdrant vs ChromaDB: Which One for Production?
Qdrant has 29,692 stars on GitHub while ChromaDB has 26,727. But more stars don’t mean it’s the best choice for your production needs. In today’s world of data-driven applications, the choice of vector database can significantly impact performance, scalability, and ease of use. This article will compare Qdrant
7 Multi-Agent Coordination Mistakes That Cost Real Money
I’ve seen 3 production agent deployments fail this month. All 3 made the same 5 mistakes. Multi-agent coordination is one of those buzz-worthy terms that sound impressive but when done poorly, it costs companies not just time and headache but serious cash.
1. Poor Communication Protocols
Why
After one year with ChromaDB, it’s handy for R&D but a pain in production.
In 2026, I’ve spent a solid year shuffling bits around with ChromaDB, using it primarily for building experimental machine learning models and handling vector embeddings in our products. Scale-wise, we tested it with datasets ranging from 10,000 to over a million
Docker vs Kubernetes: Which One for Enterprise
As of now, Docker has over 60,000 stars on GitHub compared to Kubernetes’s impressive 113,000. But really, stars don’t directly correlate to enterprise capability; practical application does. This article will lay out a thick comparison of Docker and Kubernetes to help enterprises decide between these two giants. The
10 LLM Cost Optimization Mistakes That Cost Real Money
I’ve seen 3 startups go under this month. All 3 made the same costly LLM cost optimization mistakes that turned their promising projects into financial black holes.
1. Ignoring Model Complexity
Simple models might not solve all your problems, but complex models come with complexity costs.
LangGraph vs Semantic Kernel: Choose the Right Tool for Your Enterprise Needs
LangChain has 130,068 GitHub stars. Microsoft’s Semantic Kernel, on the other hand, has 27,506. But stars don’t make or break an application — it’s the functionality and user experience that will determine what maintains your enterprise’s edge. So should your company lean toward