Decide which tasks belong with AI, when to connect or automate the steps, and how to help your team use the approach. Start with work you recognise.
Choosing the work
Decide which tasks belong with an AI assistant, existing software, automation or a person. A practical guide using everyday document and spreadsheet work.
Choosing the approach
Choose between an AI assistant, existing software and automation by looking at repetition, rules, review and maintenance. Start with the work you actually do.
Making it work for the team
Help colleagues repeat a useful AI workflow with clear inputs, a checked example, review criteria and ownership. Test the handover before extending it.
Investor relations guide
A practical guide for fund managers assessing AI for investor due diligence questionnaires: approved answers, source checks, review, buying decisions and measurement.
Proposal guide
How advisory firms can assess AI for proposals: approved credentials, relevant CVs, source checks, review responsibilities and a practical test before buying or building.
Definition
A practical definition of AI adoption, the difference between usage and operational change, and the evidence teams should use to judge whether it is working.
Definition
A practical definition for teams using AI at work. Learn what an AI playbook includes, how it differs from a prompt library, and how teams build playbooks that people actually use.
Definition
How teams record the context, steps and checks behind useful AI work, and what a record needs before another person can rely on it.
Comparison
A practical comparison of saved prompts versus reusable AI playbooks - and when teams need more than a prompt folder.
Team guide
What makes a playbook useful across a team, what it should include, and how to turn one person’s AI habit into shared operating knowledge.
Side-by-side looks at the tools and approaches that matter.
Comparison
A practical method for comparing the ChatGPT, Claude and Gemini products with the same representative work, review criteria and governance needs. There is no universal winner.
The right approach depends on the work, the material you can use and the people who will own the result.
You’ll speak directly with the people who’d do the work, about the problem and whether CURN is the right fit.
Any questions? Email info@curn.io to find out more.