Frameworks
Frameworks explain how to think about Editorial Intelligence: the models, relationships and operating logic behind the discipline. For practical sequences that show how the work gets done, explore the methods.
AI-mediated discovery is one applied layer of that system. The terminology is still unsettled — GEO, AI search, answer-engine optimisation and AI visibility are all used — so the framework here focuses on the durable editorial problem beneath the labels: which questions matter, what evidence can answer them, what is missing, how knowledge should be structured and how the response should feed back into what gets developed next.
Where to start
New to the frameworks? Read them in this order. Each one builds on the last.
Foundational
The core models. Understand these first.
Operational
Apply the model — tools for day-to-day practice and specific problems.
Applied
Context-specific models for particular industries, roles or use cases.
Turn events, conversations and research into deliberate evidence acquisition
Events, webinars, sales calls, customer interviews and video shoots are not just content-production moments. They are opportunities to acquire the knowledge an organisation needs next.
Turn fragmented customer and product evidence into better decisions
Product teams do not have an information problem. They have a synthesis problem. Editorial Intelligence helps product teams connect customer research, analytics, support feedback and market signals to improve prioritisation, product decisions and organisational memory.
What knowledge should an AI agent be built on?
Agentic AI shifts the question from what AI can generate to what work AI can complete. Editorial Intelligence focuses on the knowledge, judgement and narrative systems those agents need in order to be useful.
From AI adoption to commercial transformation
A strategic framework for understanding how AI adoption progresses from experimentation to commercial transformation — and why the critical challenge is not adoption speed but the capacity gap between time saved and value captured.
The six shifts accounting and bookkeeping firms need to make before quarterly compliance begins
MTD for Income Tax doesn't just change compliance. It changes client behaviour, workflow rhythms, pricing logic, capacity management, team collaboration and AI readiness — simultaneously. This framework maps the six operational shifts firms need to make.
How Editorial Intelligence turns research into product marketing that compounds
A framework for building product marketing programmes from shared narrative foundations — so that launches, customer evidence, sales enablement and campaigns reinforce each other rather than starting from scratch each time.
How Editorial Intelligence transforms regulatory change into a pricing strategy
A practical framework for accounting firms navigating Making Tax Digital pricing decisions — built from practitioner research, customer conversations and operational signal analysis. An example of Editorial Intelligence in action.
How customer stories become strategic evidence rather than isolated marketing assets
A framework for extracting strategic intelligence from customer stories — capturing signals about pressure, decision-making, adoption and risk, while preserving what each story teaches the next one about interviewing, evidence and editorial judgement.
The wider system
These frameworks form part of Editorial Intelligence OS.
See how the frameworks connect with assessments, applications, guides and AI workflows to make the discipline repeatable.