The PM Tool Landscape
The software a PM touches, by category, with the examples worth knowing. I'm deliberately brief on each, because tools are the easy-to-teach layer of the craft, the bottom of the character → competency → craft → tools hierarchy. You can learn Jira in a week; you can't learn judgment in a week. Pick a sensible default in each category, get fluent, and don't mistake tool mastery for the job.
Knowing the tools is table stakes, not a differentiator. I've never hired anyone because they knew Amplitude, and I've never rejected anyone because they didn't. Tools change; the competency they serve doesn't. Optimize for the competency, then pick whatever tool the team already uses.
#Delivery and project tracking
Where work is planned, tracked, and shipped. Serves Product Delivery and Agile Delivery and Team Cadence.
- Jira: the enterprise default; powerful, heavy, infinitely configurable.
- Linear: the fast, opinionated favorite of modern product teams.
- Asana / Trello: lighter project tracking, common at smaller orgs.
#Roadmapping and product management platforms
Where strategy and the roadmap live. Serves Building and Managing a Roadmap and Prioritization Frameworks.
- Productboard: feedback-to-roadmap with prioritization (incl. RICE).
- Aha!: roadmap- and strategy-heavy.
- Notion / Confluence: where many teams keep specs, strategy docs, and the templates from this Atlas.
#Analytics and metrics
Where you measure whether it worked. Serves Fluency with Data and Product Analytics and Metrics.
- Amplitude / Mixpanel: the two leading product-analytics platforms (funnels, retention, cohorts).
- Looker / Tableau: BI and dashboards for broader business data.
- SQL: not a tool so much as a literacy; the PMs who can self-serve a query move faster.
#Experimentation
Where you run A/B tests and feature flags. Serves Hypothesis-Driven Development.
- Optimizely / LaunchDarkly / Statsig: feature flagging and experimentation at scale.
#Design and prototyping
Where the experience gets shaped. Serves User Experience Design and Design Sense and Critique.
- Figma: the universal design and collaboration tool; PMs live in it for specs and critique.
- FigJam / Miro: whiteboarding, journey maps, workshops.
#User research
Where insight gets captured and synthesized. Serves Voice of the Customer and User Research and Discovery.
- Dovetail: research repository and synthesis; its AI Docs feature now produces evidence-backed, cited PRDs.
- Maze / UserTesting: usability testing and unmoderated research.
- Typeform / SurveyMonkey: surveys and quantitative feedback.
#AI prototyping ("vibe coding")
The newest category, and the one reshaping the job fastest, because PMs now ship working prototypes themselves. Serves AI in Prototyping and Delivery.
- v0: generates React UI from prompts.
- Lovable / Bolt / Replit: full-stack MVPs in the browser, designer/PM-friendly.
- Cursor: the bridge to a real repo when a prototype graduates.
"Vibe coding" gets you to a credible prototype fast, and then the last 30% (edge cases, security, production hardening) is exactly as hard as it ever was. Prototype to learn and align, not to ship to production. See AI in Prototyping and Delivery.
#AI spec and writing tools
Where the mechanical writing now gets a first draft. Serves Writing PRDs and Specs.
- ChatPRD: the most popular PM-specific AI tool; drafts PRDs, strategy, and reviews.
- Claude / ChatGPT: general assistants for drafting, analysis, and summarizing.
- GitHub Spec Kit: spec-driven development, where "intent is the source of truth."
#Evals tooling (for AI products)
If you build AI features, this category is becoming non-negotiable. Serves Writing Evals for AI Products.
- Braintrust / LangSmith / OpenAI Evals: datasets, scoring, traces, LLM-as-judge.
#How to choose
- Use what the team already uses: tool fragmentation costs more than any tool's marginal feature. 2. Match the tool to the competency, not the trend. 3. Spend your learning budget on the AI-prototyping and evals categories: that's where the leverage is shifting. 4. Stay swap-ready, especially on the AI layer; the landscape turns over fast (Cat Wu's "do the simple thing that works").
#Continue Reading
- Character, Competency, and Craft for why tools are the easy-to-teach layer, and what isn't.
- AI in Prototyping and Delivery for the vibe-coding category in depth.
- Writing Evals for AI Products for why evals tooling is the new must-have.
- The PM Competency Model for the competencies these tools actually serve.
- Product Management Templates for what to put into Notion, Figma, and ChatPRD.