Layers Observed Behaviour
This is one layer in a structured approach to product research and design. It focuses specifically on staying grounded in what users actually do rather than what you assume they do. You'll either plan new research (picking from JTBD interviews, contextual inquiry, diary studies, or analyzing existing support tickets) or synthesize what you've already gathered into confidence-rated findings. The discipline here is useful: mark everything as observed, inferred, or assumed, and if you claim something is observed, you should be able to quote the evidence in the same breath. It pushes you to name research gaps explicitly instead of filling them with wishful thinking. Works best when you have some user research to make sense of or need to design a study that answers specific questions.
- skills.sh installs
- 2K
- GitHub stars
- 314
- last updated
- Aug 21, 2026
Install
$ npx -y skills add jamiemill/layers-skills --skill layers-observed-behaviour --agent claude-codeInstalls into .claude/skills of the current project.
Files
/layers-observed-behaviour
Assumes /layers-intro has been loaded. This skill is a library of techniques, not a script — see "How to use these skills" there.
The observed behaviour layer is the closest we can get to reality — what users actually do, not what we think they do or wish they would. Everything above it is interpretation; this layer is the source.
It splits into two situations. Detect which applies and say so:
- Plan — no research yet; design a study.
- Synthesise — research material exists; make sense of it.
With partial research, synthesise what exists first, then plan to fill the gaps.
The decisions this layer makes
- What specific questions we most need to answer about our users
- What evidence already exists, and how reliable it is
- How to gather what's missing
- What patterns hold with confidence vs. what remains assumption
Disciplines — what keeps observation honest
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- Repository
- github.com/jamiemill/layers-skills
- Categories
- Data Science & ML, Productivity & Planning
- First seen
- Jun 3, 2026
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