Notes · Generative AI

Generative AI

Working notes on large language models, retrieval-augmented generation, and agent architectures.

Retrieval-augmented chatbot answering a question with the source passages it used shown beside the answer

14 Jul 20263 min read

Why your RAG chatbot answers confidently and wrongly

Most retrieval-augmented systems fail at retrieval, not generation. Here is where they break, and the fixes that moved the needle on a bilingual assistant handling real student queries.

RAG
Vector Search
LLM

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Agent execution trace showing the sequence of tool calls taken to answer a data question

Generative AI

2 Mar 20263 min read

When an AI agent is the wrong answer

Agent frameworks make it easy to build something that looks impressive and behaves unpredictably. A practical test for whether your problem needs an agent or a pipeline.

AI Agents
LangGraph
CrewAI

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Side-by-side comparison of a base model response and a fine-tuned model response to the same instruction

Generative AI

20 Jan 20263 min read

Fine-tuning or RAG? The question is what you are missing

Fine-tuning teaches behaviour, retrieval supplies facts. Confusing the two is why people fine-tune a model on their documentation and are disappointed by the result.

Fine-tuning
LoRA
QLoRA

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