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Author name: Alex Chen

Alex Chen is a senior software engineer with 8 years of experience building AI-powered applications. He has worked at startups and enterprise companies, shipping production systems using LangChain, OpenAI API, and various vector databases. He writes about practical AI development, tool comparisons, and lessons learned the hard way.

Machine Learning

OpenAI API vs Claude API: Which One for Side Projects

OpenAI API vs Claude API: Which One for Side Projects?

The OpenAI API and Claude API are significant players in the developer space, especially when it comes to building AI applications. In March 2023, OpenAI’s model boasted integration into over 100 products, while Anthropic’s Claude API stepped firmly into the spotlight with its own set

Machine Learning

Railway vs Render: Which One for Side Projects

Railway vs Render: Which One for Side Projects
Railway has 15,432 GitHub stars while Render sits at 8,765. But honestly, the number of stars really doesn’t tell the whole story when it comes to picking the right tool for your side projects.

Applications

RAG Systems: Navigating the Chaos of Reasoning & Generation

RAG Systems: Navigating the Chaos of Reasoning & Generation

Alright, let me just get this off my chest first—RAG systems, or Reasoning and Generation systems, are not the golden goose everyone seems to think they are. Yeah, I’ve been tinkering with these for a while now, and to be honest, they’re more often a wild goose

Machine Learning

vLLM vs TGI: Which One for Enterprise

vLLM vs TGI: Which One for Enterprise Applications?

vllm-project/vllm has 73,658 stars on GitHub, while huggingface/text-generation-inference (TGI) boasts 10,809 stars. But stars don’t equate to real-world performance and usability, especially in enterprise settings where efficiency and reliability reign supreme.

Machine Learning

Context Window Optimization: A Developer’s Honest Guide

Context Window Optimization: A Developer’s Honest Guide
I’ve watched five projects flounder this quarter because teams underestimated the importance of context window optimization. All of these failures had one thing in common: they overlooked crucial steps that could have saved their AI integrations.

The Problem This Solves
When working with language models, context window optimization

Applications

My AI Agent Debugging Led Me to Rethink Memory

Alright folks, Alex Petrov here, back at agntai.net. Today, I want to talk about something that’s been rattling around in my head for a while, especially after spending way too many late nights debugging an agent’s “understanding” of a simple task. We’re all building these AI agents, right? Autonomous systems, trying to get things done

Applications

Production ML: Stop Making These Mistakes in 2026

When a Cool Prototype Becomes a Total Disaster
So there I was, sipping my third coffee for the day, trying to untangle why our ML model was making the worst predictions possible. It’s a classic case: everything works great in the lab, then you throw it into production and BAM—chaos. If you’ve ever been here,

AI/ML

My AI Agent Got Stuck: Heres How I Fixed It

Hey there, AgntAI.net readers! Alex Petrov here, fresh off a particularly gnarly debugging session that got me thinking. We talk a lot about the grand vision of AI agents – the autonomous systems that can plan, execute, and adapt. But what about the messy reality of building them? Specifically, the part where they need to

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