LLM

How do you add observability to Hermes Agent with self-hosted Langfuse? A walkthrough of enabling the bundled plugin, the SDK gotcha that silently kills tracing, per-model cost tracking on Coolify, and what the traces actually look like.

What’s the difference between prompt engineering, context engineering, harness engineering, loop engineering, and evaluation engineering? A side-by-side comparison with diagrams for AI engineers building production systems.

How do you know if an AI agent is telling the truth? When my research agents fabricated 11 model names and 4 fake paper titles, I learned the hard way that autonomous AI research requires independent verification.

I went on a weekend trip. I came back to a new Claude, a new GPT and an existential crisis. The pace of AI is no longer monthly. It’s weekly.

I went down the rabbit hole of AI in the adult industry. I expected simple chatbots; I found a sophisticated engineering stack pushing the boundaries of edge computing, privacy and opensource AI.

How do you monitor AI systems in production? Practical strategies for instrumenting LLM applications with OpenTelemetry, tracking token costs, latency and quality metrics.

What are the hidden costs of using LLM-as-a-Judge? Learn about common biases, failure patterns and smarter evaluation strategies for LLM applications.

What is LLMOps? An introduction to Large Language Model Operations covering the lifecycle from DevOps to MLOps to LLMOps, with key differences and tooling.

What is the history of Large Language Models? From rule-based systems to transformers to GPT-4: understand the evolution of LLMs and their impact on NLP.

What is prompt engineering and how does it work? Learn zero-shot, few-shot, chain-of-thought, generated knowledge and ReAct prompting techniques for LLMs.

How to access GPT-4 from OpenAI.