Explore TopicFolio posts tagged #product-management. 6 public posts indexed. Includes activity from Product Management. Related folio: Product Strategy Library.
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Before I trust a product strategy, I want to see a clear user problem, evidence that alternatives were considered, and a review plan tied to an outcome. If those three things are missing, the roadmap is usually just a wish list with dependencies.
Three evaluation axes to compare:
- quality of evidence behind the decision
- clarity of roadmap communication
- follow-through on outcome measurement
Review materials:
- Atlassian product management guide: atlassian.com/agile/product-management
A practical reference for planning, teamwork, and delivery rhythms.
- Opportunity solution tree guide: producttalk.org/opportunity-solution-tree/
Still one of the clearest visual frameworks for connecting discovery to roadmap choices.
- GitLab product handbook: handbook.gitlab.com/handbook/product/
One of the best public examples of product work written down in the open.
Save the strongest examples, scorecards, and decision memos in this folio so future teammates can see what good evaluation looked like at the time.
The arguments worth having are about certainty versus speed, how public internal roadmaps should be, and whether PMs should own a KPI or the quality of the decision process around it. Those are structural questions, not personality tests.
Three questions worth debating:
- when to optimize for speed versus certainty
- how much roadmap detail should be public inside a company
- whether PMs should own the KPI or the decision process
Background reading before you take a strong stance:
- Continuous discovery overview: producttalk.org/continuous-discovery/
A durable foundation for teams trying to make research continuous instead of episodic.
- SVPG article archive: svpg.com/articles/
Useful for strategy, product operating models, and decision quality.
- Lenny's Podcast video archive: youtube.com/@Lennyspodcast/videos
Product conversations that tend to stay practical instead of drifting into slogans.
When you respond, include the environment you are optimizing for. Advice changes a lot across stage, regulation, team size, and user expectations.
A useful PM starter pack should include discovery guidance, a public product handbook, a strategy archive, and one writing template that makes decisions legible. That is enough to upgrade most teams more than another prioritization framework ever will.
The kinds of materials worth saving in this space:
- discovery templates that help teams compare evidence
- strategy memos that show the decision behind the roadmap
- metric review frameworks that connect product and business outcomes
Read:
- Continuous discovery overview: producttalk.org/continuous-discovery/
A durable foundation for teams trying to make research continuous instead of episodic.
- SVPG article archive: svpg.com/articles/
Useful for strategy, product operating models, and decision quality.
- Atlassian product management guide: atlassian.com/agile/product-management
A practical reference for planning, teamwork, and delivery rhythms.
Documents and downloadable guides:
- Opportunity solution tree guide: producttalk.org/opportunity-solution-tree/
Still one of the clearest visual frameworks for connecting discovery to roadmap choices.
- Atlassian product management guide: atlassian.com/agile/product-management
A useful operating reference for discovery, prioritization, launches, and stakeholder comms.
Watch:
- Lenny's Podcast video archive: youtube.com/@Lennyspodcast/videos
Product conversations that tend to stay practical instead of drifting into slogans.
Build or inspect:
- GitLab product handbook: handbook.gitlab.com/handbook/product/
One of the best public examples of product work written down in the open.
Image references:
- Opportunity solution tree visuals: producttalk.org/opportunity-solution-tree/
A good visual shorthand for teams trying to make discovery artifacts reusable.
The best metrics are the ones that sit next to a decision, not the ones that decorate a slide. I want to know how fast a signal became a committed decision, whether the target users adopted the change, and whether the outcome metric tied to the bet actually moved.
Three metrics worth pressure-testing:
- time from research signal to committed decision
- feature adoption for the target user segment
- movement in the outcome metric tied to the roadmap bet
Source material behind the scorecard:
- Continuous discovery overview: producttalk.org/continuous-discovery/
A durable foundation for teams trying to make research continuous instead of episodic.
- Atlassian product management guide: atlassian.com/agile/product-management
A practical reference for planning, teamwork, and delivery rhythms.
If your team has a sharper dashboard, share the metric definitions and the decisions they actually change. That is what makes numbers reusable.
The sequence I trust here is: define the decision, gather enough evidence to compare options, document what you learned in a format others can search, and only then move a roadmap or staffing bet. That is slower than a hot-take roadmap and faster than undoing one.
A sequence I would actually hand to a teammate:
1. Start with the user problem, the business constraint, and the decision to unlock.
2. Capture research and evidence where the team can revisit it later.
3. Translate learning into roadmap movement, launch plans, and follow-up metrics.
Useful operating references:
- SVPG article archive: svpg.com/articles/
Useful for strategy, product operating models, and decision quality.
- GitLab product handbook: handbook.gitlab.com/handbook/product/
One of the best public examples of product work written down in the open.
If your team has a better workflow, post it with the context around team size, constraints, and exactly where the process tends to break.
Product work becomes less political when the evidence trail is visible. The best public product writing keeps pushing teams toward explicit decisions, reusable research notes, and roadmaps that explain why something matters before they explain when it ships.
Three signals I would keep in view:
- Strong product management creates alignment by making tradeoffs legible.
- Discovery quality improves when insights are stored in reusable formats.
- Roadmaps work best when they explain why, not just what and when.
Read first:
- Continuous discovery overview: producttalk.org/continuous-discovery/
A durable foundation for teams trying to make research continuous instead of episodic.
- SVPG article archive: svpg.com/articles/
Useful for strategy, product operating models, and decision quality.
Documents worth saving:
- Opportunity solution tree guide: producttalk.org/opportunity-solution-tree/
Still one of the clearest visual frameworks for connecting discovery to roadmap choices.
- Atlassian product management guide: atlassian.com/agile/product-management
A useful operating reference for discovery, prioritization, launches, and stakeholder comms.
Watch next:
- Lenny's Podcast video archive: youtube.com/@Lennyspodcast/videos
Product conversations that tend to stay practical instead of drifting into slogans.
If this post is useful, the next contribution should add a real example, a worked document, or a failure case someone else can learn from.