Contributing to Glare

Glare gets better when people use it in real work.

The framework was built from patterns we kept seeing across product and design teams. It should keep improving the same way: through real decisions, real signals, useful Skills, and honest examples from people doing the work.

You do not need a polished case study to contribute. Bring what you are already working through:

A decision that felt unclear
A hunch your team tried to shape
A signal that helped a review move forward
A Skill that made the work easier to repeat
A moment where the framework broke down or needed more clarity

Those examples make Glare sharper.

As Lyndon Cerejo put it, teams need:

A common set of metrics that Product & UX work toward together.

That shared language does not appear on its own. It gets built through use.

Join the Community

Glare gets stronger when people use it in real work and share what they learn.

This is more than a framework to read. It is a growing community of product, design, research, and engineering leaders working to make decisions clearer, faster, and easier to trust.

By joining, you can:

Connect with peers facing the same decision challenges
Compare signals, methods, and AI Skills across teams
Share examples of how Glare works in real projects
Help shape an open playbook for evidence-based design

The best contributions are often simple:

Use a Skill
Apply it to one decision
Create or strengthen a signal
Share what happened

Glare only works if people bring their real examples into it. Add your ideas. Add your perspective. Help shape the Skills, patterns, and practices that make design decisions easier to prove.

Join the Glare community today →

Share your ideas, add your voice, and help shape the open playbook for evidence-based design.

Who Glare is for

Glare is built for teams responsible for shaping direction and making decisions.

It supports product, design, research, engineering, and leadership teams that need to move quickly while keeping decisions clear, explainable, and connected to measurable outcomes.

The framework is especially useful for teams that:

Work across multiple stakeholders and perspectives
Need faster feedback loops around product decisions
Struggle to align around evidence and tradeoffs
Want clearer ways to connect design work to outcomes
Are integrating AI into product and design workflows
Need more confidence before scaling ideas

Glare helps teams create shared decision structures so ideas can be evaluated, discussed, and improved with more clarity as work moves forward.

<table xmlns="http://www.w3.org/1999/xhtml" style="min-width: 532px;"><colgroup><col style="min-width: 25px;"><col style="width: 174px;"><col style="width: 156px;"><col style="width: 177px;"></colgroup><tbody><tr><td colspan="1" rowspan="1">Roles</td><td colspan="1" rowspan="1" colwidth="174">How</td><td colspan="1" rowspan="1" colwidth="156">Apply Skills</td><td colspan="1" rowspan="1" colwidth="177">What They Need</td></tr><tr><td colspan="1" rowspan="1">Design Leaders</td><td colspan="1" rowspan="1" colwidth="174">Design leaders need their decisions to be understood and trusted.Signals show how design choices influence user behavior and outcomes, giving them a clear way to explain and defend direction.</td><td colspan="1" rowspan="1" colwidth="156">Use AI Skills to structure evaluations, compare directions, and communicate results consistently across teams.</td><td colspan="1" rowspan="1" colwidth="177"><ul><li>Connect design decisions to business outcomes</li><li>Build alignment with product and engineering</li><li>Show how design influences what gets built</li></ul></td></tr><tr><td colspan="1" rowspan="1">Product Leaders</td><td colspan="1" rowspan="1" colwidth="174">Product leaders are responsible for deciding what moves forward.Signals reveal which directions are working, helping them move from discussion to clear decisions.</td><td colspan="1" rowspan="1" colwidth="156">Use AI Skills to frame decisions, evaluate options quickly, and maintain alignment across roadmap and planning.</td><td colspan="1" rowspan="1" colwidth="177"><ul><li>Evaluate multiple directions with clarity</li><li>Reduce debate in roadmap and planning</li><li>Connect user behavior to product priorities</li></ul></td></tr><tr><td colspan="1" rowspan="1">Engineers and Technical Teams</td><td colspan="1" rowspan="1" colwidth="174">Engineers build against decisions that are often still evolving.Signals provide clearer inputs on what should be built and why, reducing ambiguity during implementation.</td><td colspan="1" rowspan="1" colwidth="156">Use AI Skills within prompts and workflows to structure ideas, evaluate them early, and reduce mid-stream changes.</td><td colspan="1" rowspan="1" colwidth="177"><ul><li>Reduce shifting requirements</li><li>Work with clearer decision inputs</li><li>Avoid mid-stream changes</li></ul></td></tr><tr><td colspan="1" rowspan="1">Research Leaders</td><td colspan="1" rowspan="1" colwidth="174">Research leaders need their insights to shape what happens next.Signals connect findings directly to decisions, making research usable in the moment it matters.</td><td colspan="1" rowspan="1" colwidth="156">Use AI Skills to structure research outputs so they can be applied in fast-moving product conversations.</td><td colspan="1" rowspan="1" colwidth="177"><ul><li>Shorten the distance between insight and action</li><li>Make findings usable in fast-moving conversations</li><li>Ensure research shapes what happens next</li></ul></td></tr><tr><td colspan="1" rowspan="1">Founders and Executives</td><td colspan="1" rowspan="1" colwidth="174">Leaders are responsible for prioritization and risk.Signals provide fast, directional evidence that shows how ideas are likely to perform before committing resources.</td><td colspan="1" rowspan="1" colwidth="156">Use AI Skills to frame key questions, evaluate options quickly, and make decisions with clearer inputs.</td><td colspan="1" rowspan="1" colwidth="177"><ul><li>Prioritize with confidence</li><li>Evaluate investments</li><li>Understand and manage risk</li></ul></td></tr><tr><td colspan="1" rowspan="1">Designers</td><td colspan="1" rowspan="1" colwidth="174">Designers need their thinking to influence decisions, not just outputs.Signals show how their work performs with users, making their reasoning visible and grounded in behavior.</td><td colspan="1" rowspan="1" colwidth="156">Use AI Skills to test concepts, refine ideas, and connect design decisions to measurable outcomes.</td><td colspan="1" rowspan="1" colwidth="177"><ul><li>Explain why a direction works</li><li>Show how users respond</li><li>Influence decisions beyond output</li></ul></td></tr></tbody></table>

Why Contribution Matters

Product and design teams are moving faster than ever.

AI can generate more ideas, more options, and more directions. But faster output does not automatically create better decisions. Teams still need clear signals, stronger questions, and better ways to connect user behavior to business outcomes. That is where the community matters.

Every real example helps make Glare easier to use. Every signal helps clarify how decisions move. Every Skill that gets used, questioned, or improved makes the system stronger for the next team.

Glare grows through use.

1. Use a Skill in Real Work

The easiest way to contribute is to use a Glare Skill inside work you already have. Skills turn the framework into action. They help teams:

Frame decisions
Clarify user needs
Connect business goals
Shape design signals
Interpret what users are showing

When you use a Skill, notice what changed.

Did it help you:

Frame the decision faster?
Clarify the user need?
Connect the business goal?
Create a stronger signal?
Explain the next step?

That feedback matters. A Skill becomes stronger when people use it across different teams, contexts, and decisions.

Obed Rosas described one of the core challenges well:

Design impact is challenging because of the consistency in how my team delivers the outputs of their research and makes non-UXers understand it.

Skills help create that consistency. They make the work easier to repeat, easier to explain, and easier for others to use.

2. Share a Design Signal

Signals are the core of Glare. If a signal helped your team make a decision, share the shape of it.

You can share:

The hunch you started with
The UX metric you used
The user need it connected to
The business goal it supported
The decision it helped guide
What changed after the decision

The signal does not need to be perfect. Rough signals are often more useful because they show where teams actually struggle. They make the work real. They show how decisions are made when the inputs are messy, the timeline is tight, and the team still has to move.

Hermen Wijbenga pointed to one of the hardest parts:

The hardest part is getting feedback from the right real users with real high quality feedback.

That is why shared signals matter. They show how teams are grounding decisions in real input, not just opinions.

3. Improve a Skill

Some Skills will feel clear right away. Others will need pressure from real work. If a Skill feels hard to use, that is useful feedback.

Where it slowed down
What input was missing
What language felt unclear
What output would have helped
Where the Skill broke in your context

The goal is to build repeatable Skills that help teams and AI systems make better decisions faster. This matters more as teams work with prompts, agents, and automated workflows. Skills give that work structure. Your feedback helps make that structure easier to trust.

Mirjam Amoah captured the larger challenge:

The biggest challenge is figuring out together what design is actually supposed to achieve and how to measure that in a meaningful way.

Improving Skills helps make that work clearer. It gives teams a better way to connect what they are doing to what they are trying to achieve.

4. Add an Example

Examples make Glare easier to understand. A good example shows how a team moved from uncertainty to direction.

It might explain:

What decision was on the table
What Skill helped structure the work
What signal became visible
What tradeoff changed the conversation
What decision was made

Examples help people see how Glare works in practice.

They also help AI systems understand how the framework should be applied in different situations. The clearer the examples, the easier it becomes for people and systems to reuse the thinking.

Clara Soon described why this matters:

Design contributes value in ways that are often distributed across teams and phases rather than tied to a single visible output.

Examples make that distributed value easier to see. They show how signals, decisions, and outcomes connect across the work.

5. Push on the Framework

Contributing also means questioning the system. If something feels unclear, call it out. If a term does not hold up in real work, challenge it. If a Skill works in one context but breaks in another, share that.

Glare should be used, stretched, and improved. The best contributions are often simple notes from someone trying to make a decision with imperfect information.

That is where the framework gets better.

What Contribution Creates

When people contribute, Glare becomes more useful for everyone.

Over time, contributions create:

Stronger Skills
Clearer signal examples
Better decision patterns
More useful prompts
Shared proof across teams
Stronger language for design impact

This is how Glare grows: as a working framework shaped by the people using it.

Karline Segan put the larger goal in clear terms:

We need to learn to translate and narrate all our invisible work into understandable business value or it will not exist.

That is what contribution helps create. It turns hidden work into shared proof. It makes signals easier to see, decisions easier to explain, and design impact easier to carry forward.

Start Small

Start with one Skill and one decision your team is already working through.

Use the Skill to bring structure to the moment. Let it help you clarify the hunch, connect the user need, shape the signal, or explain what happened next.

Then share what you learned. It does not need to be polished. A rough signal, a small example, or a note about where the Skill helped or broke down is enough. That is how Glare improves.

The work gets better when more people help make it clearer.

Join the Glare community today →

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