Context Engineering

In my latest post, I how hybrid search will be utilised to significantly improve the effectiveness of a RAG pipeline. RAG, in its basic version, using just semantic search on embeddings, will be...

, I’ve kept returning to the identical query: if cutting-edge foundation models are widely accessible, where could durable competitive advantage with AI actually come from? Today, I would really like to zoom in on context engineering — the discipline...

is a fresh start. Unless you explicitly supply information from previous sessions, the model has no built‑in sense of continuity across requests or sessions. This stateless design is great for parallelism and safety,...

, context really is every thing. The standard of an LLM’s output is tightly linked to the standard and amount of knowledge you provide. In practice, many real-world use cases include massive contexts: code...

an LLM can see before it generates a solution. This includes the prompt itself, instructions, examples, retrieved documents, tool outputs, and even the prior conversation history. Context has a huge effect on answer quality....

with AI is an efficient way of accelerating coding speed. AI agents can handle numerous the straightforward and repetitive tasks, while you'll be able to act as an orchestrator in your agents. An issue...

has received serious attention with the rise of LLMs able to handling complex tasks. Initially, most discussions on this talk revolved around : Tuning a single prompt for optimized performance on a single...

, I saw our production system fail spectacularly. Not a code bug, not an infrastructure error, but simply misunderstanding the optimization goals of our AI system. We built what we thought was a elaborate...