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Start with AI PM roles, pay, recruiting, portfolios, and the free check, then browse interview, career-switch, B2B, and data practice guides.
AI PM career starting point
Move from diagnosis to evidence, resume writing, and interview practice instead of collecting disconnected articles.
Find up to three priority edits with a public rubric and no file upload.
Download a reusable outline for tasks, baselines, evals, failures, and trade-offs.
Use a JD-to-evidence matrix and constructed examples without inventing outcomes.
Cover product judgment, RAG, agents, evals, cost, risk, and project deep dives.
Practice AI PM interview questions covering product judgment, RAG, agents, evaluation, failure and safety, cost and latency, project deep dives, and behavioral evidence.
A 2027 AI PM recruiting guide: use a relative timeline, turn JDs into an evidence matrix, review your portfolio, and track each application.
An AI PM portfolio guide for candidates without internships or production data: use bounded tasks, baselines, evaluations, prototypes, and honest validation plans.
A practical AI PM portfolio template covering task definition, baselines, evaluation data, failure taxonomy, prototype controls, cost, latency, risk, and launch tests.
An AI PM evaluation method for task definitions, datasets, rubrics, deterministic and model graders, human review, release gates, online metrics, and regression.
A B2B PM guide to tenant boundaries, roles and atomic permissions, data and field scope, temporary access, approval, audit logs, migration, and authorization tests.
Download a runnable PostgreSQL synthetic dataset and practice activation, funnels, cohorts, channel conversion, repeat purchase, and anomaly analysis across three tables.
A 30-day operations-to-PM plan covering role analysis, project translation, research, prototyping, metrics, portfolio, and interview practice.
A practical product manager resume guide covering role-evidence mapping, project bullets, metrics, honest portfolio work, formatting, and a final review checklist.
A practical product manager interview guide covering role evidence, project deep dives, product design and data cases, mock interviews, and retrospectives.
A practical product manager portfolio guide for students and career switchers: topic selection, evidence, case structure, privacy, and interview walkthroughs.
A practical 2026 China PM salary guide covering monthly base pay by experience, AI product roles, city differences, total compensation, and offer comparison.
Choose a realistic PM direction, translate operations work into product evidence, close skill gaps, build a portfolio case, and follow a practical transition plan.
Prepare for PM group interviews with generic exercises for framing, speaking, listening, prioritizing, resolving conflict, summarizing, and reviewing your performance.
Understand data operations responsibilities, SQL, metric governance, anomaly diagnosis, experiments, work samples, interview preparation, and entry paths.
Understand internet operations through user goals, daily responsibilities, and concrete deliverables across content, user, product, data, and growth roles.
Decode AI product manager job descriptions, daily responsibilities, required skills, evaluation work, portfolio evidence, and practical entry paths.
Decode B2B product manager responsibilities, SaaS job requirements, enterprise workflows, core deliverables, portfolio evidence, and interview preparation.
A practical guide to product manager responsibilities, role boundaries, specializations, evidence of skill, career transitions, and interview preparation.
A copyable metric dictionary covering numerator, denominator, windows, identity, sources, owners, versions, quality checks, and dashboard contracts.
A practical AI PM resume guide for mapping job descriptions to evidence, writing projects with evaluation metrics, failures, cost, and boundaries, plus a free template.
AI agent metrics for verified task success, tool use, human takeover, recovery, latency, cost, safety guardrails, and production dashboards.
A practical anomaly investigation workflow covering metric validation, data freshness, baselines, decomposition, root-cause evidence, SQL, alerts, and postmortems.
Downloadable B2B research templates for mapping buyers, admins, and end users, interviewing around real workflows, and turning evidence into product decisions.
