AI for data science
Notebooks, pandas, evaluation, and ML workflows with foundation models.
8·Free resources
0 of 8 resources completed
Log in to track progressLog in to mark resources complete and sync progress across devices.
- Article35 min
a16z - The AI playbook for product teams
Essays on packaging, pricing, and roadmap tradeoffs for AI-native products.
Open resource - Article20 min
Intercom - AI product principles
Human-in-the-loop and trust patterns in support bots.
Open resource - Article35 min
Shape Up - Betting table (Basecamp)
How to scope AI bets without infinite research spikes.
Open resource - Article25 min
a16z - AI app pricing patterns
Essays on packaging credits vs seats for AI SaaS.
Open resource - Article30 min
Nielsen Norman - AI UX heuristics
Disclosure, control, and error recovery in AI UIs.
Open resource - Article18 min
GitHub Copilot - Trust & safety for devs
Lessons from shipping AI inside existing workflows.
Open resource - Article40 min
Teresa Torres - Continuous discovery
Interview loops that work for AI feature discovery.
Open resource - Article25 min
Reforge - AI product strategy syllabus
Structured frameworks for prioritizing AI bets vs core product work.
Open resource