LLM seeding means putting curated, relevant information into a model’s prompt before asking it to do the task, so the output is anchored in the context you care about rather than the model’s generic priors. It is the difference between telling a writer “write about our product” and handing them a one-page brief first — […]

How AI is applied across an ecommerce business — personalization, conversational selling, and supply-chain optimization — and the trade-offs that come with it.

Standard multimodal RAG retrieves the wrong images because captions lack document context. Two fixes: context-aware summaries at ingestion, and using the generated answer to select images.

Agentic Context Engineering (ACE) is the practice of deciding what an agent sees at each reasoning step. Covers the context loop, structuring and compaction techniques, cross-session memory, and how to evaluate context quality.

A working reference for the three decisions behind any production agent: the reasoning pattern, the framework, and the memory system.