Tag: llm
All the articles with the tag "llm".
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Prompt engineering basics every developer needs before writing any code
A prompt is not just a question — it is an instruction set. This post covers the anatomy of effective prompts, zero-shot vs few-shot prompting, chain-of-thought reasoning, and the most common mistakes developers make when writing their first prompts.
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Choosing an AI model for your Java application — OpenAI, Anthropic, or local
With Spring AI abstracting the model layer, switching providers is mostly a config change. The harder question is which model to pick for your use case. This post gives you a practical comparison and a decision guide.
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Temperature, top-p, and model parameters — what to actually set
Temperature is not magic. It is a dial that controls randomness. This post explains temperature, top-p, max tokens, and system vs user prompts in plain terms — with concrete recommendations for different use cases.
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Tokens and context windows — what every developer must understand
Tokens and context windows are not just billing details. They are hard engineering constraints that shape how you design prompts, manage conversation history, and build RAG pipelines. Here is everything you need to know.
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How LLMs work — a developer's mental model (no PhD required)
Before writing a single line of Spring AI code, you need to understand what an LLM actually is and how it behaves. This post builds the mental model that will inform every architectural decision you make.