structured content

How do you apply structure to creative work? These articles explore information architecture, markup, metadata and other structures that we need to consume and find content online.

32 posts

The front door to discovery: How natural language processing is the key to visibility in LLMs

a house with a white picket fence with a leafy fall lawn

To put it another way: optimizing with GEO reverse engineering tactics is like entering a house through a small attic window. GEO ignores that the research frameworks literally embedded in the outputs of the model are the keys to the front door.

How SEO ends

How SEO ends

Perpetuated primarily by startups hungry for users and the entrepreneurial agencies and thought leaders who serve them, bad data begets worse expectations. Rapid rocketship visibility graphs imply that business results will follow—almost never the case long-term.

How to plan content and forecast its impact

How to plan content and forecast its impact

You can't predict the future, especially in publishing. You never know exactly which pieces of content will be hits and which will be a waste of time and money. But you can, as the finance folks have taught us, forecast your impact.

A guide to information architecture: Form, function, and delight in website design

Everything we've ever written about navigation, information architecture, and structuring content.

Structure and disciplines: A contemporary arts website to remember

Laptop displaying the Creative Capital site

Creative Capital's website is a masterclass in how to maintain a database. Here, we dissect the exemplary information architecture strategy and explore role the site has played in revolutionizing the grant application process for artists and organizations across the contemporary arts world.

On iteration: Why digital business folks and content producers don’t always see eye-to-eye

On iteration: Why digital business folks and content producers don’t always see eye-to-eye

Iteration is a repetition of a process to solve a specific problem, and it’s a big part of how machine learning algorithms are developed. But the way devs and data scientists think about iteration doesn’t always match with editorial and entertainment industry production methodologies and norms.

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