Atlassian

Teams periodically assess themselves against eight health attributes.

How it works

Teams assess themselves against eight health attributes using a shared red–amber–green view.

Why it is used

Makes unspoken issues visible in a safe, repeatable way.

Trade-off

Scoring produces diagnosis without improvement unless tied to action.

Best fit

Cross-functional teams that struggle to discuss collaboration quality.

Driver, Approver, Contributors and Informed roles are explicit.

How it works

Driver, Approver, Contributors and Informed roles are assigned before the decision.

Why it is used

Makes decision ownership and contribution boundaries visible.

Trade-off

Becomes heavy if used for every decision and the Approver can become a committee.

Best fit

High-impact, multi-stakeholder decisions needing one final approver.

Goals, success signals and measures are separated.

How it works

Goal, signal of progress and measure of that signal are defined separately.

Why it is used

Separates delivered output from created outcome.

Trade-off

Risks overfocusing on what is measurable and losing qualitative signal.

Best fit

Projects and product initiatives with ambiguous success definitions.

Completed work is systematically reviewed to generate improvements.

How it works

A facilitated retrospective surfaces what worked, what did not and what should change.

Why it is used

Turns experience into organizational learning and concrete improvement.

Trade-off

Stays superficial without trust and becomes actionless ceremony when overused.

Best fit

Teams with recurring delivery cycles and trackable improvement ownership.

Each quarter Atlassian takes product managers and designers out of day-to-day work for four days to build with AI. Day one is inspiration (customer and internal showcases, outside speakers), day two is skills (reusable agents, evaluations, a dev environment), day three is building in one of seven groups with live mentoring, and day four is a demo day that includes what failed. In the latest week 77% of Product Management and 80% of Design attended.

How it works

A quarterly four-day event planned by program managers, craft experts, mentors and IT, with volunteers helping. Participants use Atlassian’s own AI and developer tools first and build end-to-end workflows instead of studying theory; outputs are shared as prototypes, templates and processes others can remix.

Why it is used

To learn AI by building rather than discussing it, and to let product and design roles move into producing code and agents. The stated principle is to experiment openly and share failures as well as successes.

Trade-off

Hundreds of people leave day-to-day work, and the curriculum is technically demanding and relies on volunteer support. The results are self-reported (298 agents, higher usage, 96% positive ratings) and do not show long-term product impact; no process is described for carrying outputs back into regular team work.

Best fit

Large companies whose product and design roles can move toward shipping code, that have AI tools of their own to use and the capacity to mentor.