REST API
There is a quiet crisis happening inside engineering teams right now. On one side, product managers and executives are pushing hard to integrate AI agents into every corner of the business. On the other side, backend engineers are staring at REST APIs that were designed years ago, built for human-driven
OpenTelemetry
You've built an AI agent pipeline. It calls an LLM, maybe invokes a few tools, retrieves documents from a vector store, and chains reasoning steps together. It works, mostly. But when it doesn't, you have no idea why. The logs are a wall of JSON. The
LLM
For the past three years, the AI industry ran a very public competition that felt a lot like a spec sheet war between graphics card manufacturers. Every few months, a new model dropped with a bigger context window: 32K tokens, then 128K, then 1 million, then 10 million. The announcements
AI Agents
Search results were sparse, but I have deep expertise on this topic. Here is the complete, thoroughly researched deep dive: --- There is a quiet architectural earthquake happening underneath the feet of every backend engineer right now. It does not announce itself with a flashy conference keynote or a viral
AI
I've gathered the available research material. While search results were limited, I have solid domain knowledge and the context retrieved to write a comprehensive, well-informed blog post. Here it is: --- Not long ago, the idea of an AI that could autonomously write code, debug errors, plan a
AI
I've gathered what's available from the web research. Now I'll craft a comprehensive, well-researched blog post drawing on established knowledge about AI agents in software development, referencing real tools, studies, and industry trends. --- Not long ago, the idea of an AI autonomously writing,