What is context engineering?
Context engineering is the practice of deciding what information a model sees at inference time — which documents, memories, tools, and instructions to place in the context window — so it produces accurate, grounded output. It has largely superseded "prompt engineering" as models and context windows have grown.
Understanding context engineering
Prompt engineering asked "how do I phrase the request?" Context engineering asks the bigger question: "what should the model have in front of it when it answers?" As context windows grew from a few thousand tokens to a million, the wording of the prompt matters less than the selection and structure of everything around it.
Good context engineering retrieves the right facts (not all facts), orders them well, includes the relevant tools, and leaves out noise that would dilute attention. Get it right and a general model behaves like a specialist; get it wrong and even a strong model hallucinates.
For a company, the raw material of context is institutional knowledge — brand, docs, policies, product data — which is exactly what a company brain organizes and feeds to agents.
Company Brain
Turn your org’s knowledge into context every agent can use.
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Company brain
A company brain is a queryable knowledge layer that holds an organization’s context — brand, documents, policies, product data — and feeds it to AI agents so their output is grounded in how the company actually works. It turns scattered institutional knowledge into agent-usable skills.
Agent memory
Agent memory is how an AI agent retains information across turns or sessions — facts, past actions, user preferences — instead of starting blank each time. It ranges from short-term (the current context window) to long-term (a persistent store the agent recalls from when relevant).
AI agent
An AI agent is a system that uses a language model to pursue a goal across multiple steps — planning, calling tools, observing results, and adjusting — rather than producing a single response. Agents can read data, run code, generate assets, and act in software on a user’s behalf.
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Agents that generate, a canvas they can see and drive, and a brain that keeps every asset on-brand. Free to start.