Product Ops playbooks: Which processes, roles, integrations, and reports actually sped discovery → delivery?

Many product orgs say strategy is fine but day-to-day ops are ad hoc: no consistent discovery playbooks, brittle toolchains, unclear handoffs, and weak outcome tracking. Looking to crowdsource practical, repeatable patterns that scaled in real orgs. If you work in product, product ops, design, eng, or analytics, please share first-hand examples (what you did, context, and measurable impact):

- Playbooks/processes: discovery templates, hypothesis checklists, experiment gating, handoff rituals — what specifically reduced rework or sped validation?
- Role designs & RACI: concrete charters or role splits (Product Ops vs. PM vs. Eng vs. Design) that removed ambiguity — include org size and level of seniority.
- Tool integrations & recipes: exact integrations or automation (e.g., Productboard↔Jira, Figma↔Notion, analytics pipelines, GitHub workflows) and how they eliminated manual work.
- Reporting & dashboards: the metrics, dashboards, or signals that connected discovery work to outcomes (sample metrics, SLOs/SLIs, questions the dashboard answers).
- Governance & cadences: review gates, decision forums, or lightweight governance that prevented scope creep and improved predictability.
- What failed: anti-patterns or integrations/playbooks that created more friction.
- Artifacts you can share: templates, playbook excerpts, RACI examples, dashboard wireframes — say what format and any redactions needed.

When you post, include: company size, industry, product maturity (early-stage growth/scale/enterprise), core toolstack, and any measurable results (time saved, % fewer bugs, faster time-to-validated-learning, etc.).

I’ll summarize recurring patterns and common templates shared here if the community is interested. Please reply with direct examples or links to anonymized artifacts you’re allowed to share.