Blog

How AI actually does knowledge work.

Longer pieces on the patterns underneath AI at work: what it needs to retrieve, what it has to know about your organization to interpret that, and what it takes to let it act.

Thought leadership

OpenAI dots: Delegated Work Needs the Same Definitions

A team of agents can divide a campaign and still disagree about what a qualified account or a booked meeting means. Delegated work only adds up when its definitions agree.

Thought leadership

Meta Muse: The Business Should Keep What It Teaches AI

The twentieth time you explain your business to an AI, you are building a record of how it works. That record should survive the handover to the next person and the switch to the next tool.

Thought leadership

Instinct Learns You. Who Decides the Company's Rules?

An assistant that learns your preferences is easier to delegate to. At work, a personal preference, a team convention, and a company rule carry different authority, and somebody has to decide which governs.

Thought leadership

Instinct, Meta Muse, and OpenAI dots: Company Work Has No Repository

Personal agents learn the person and coding agents have the repository. Company work has no shared place for what people teach AI, so ten people end up teaching ten versions of the company.

Thought leadership

The Most Important Context Your AI Needs Was Never Written Down

Enterprise search can find what your company wrote. Most of the operating context AI needs was never written down at all, so it has to be taught or inferred, and then reconciled before AI can behave consistently.

Thought leadership

ETL Built the Assembly Line. RARE Lets AI Drive.

Retrieve, Augment, Reason, Execute: a pattern for context-aware knowledge work across APIs. Where ETL follows a route decided in advance, RARE lets the AI work the route out from live data and how your organization actually operates.

Also worth reading

Shorter, more practical pieces live in guides and comparisons, and step-by-step instructions live in the help center.

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