Investigate a drop in funnel conversion
Compare funnel definitions, affected customer segments, recent releases and support evidence. Produce a ranked investigation brief that separates measurement problems from plausible product causes.
A FIELD GUIDE TO AI AT WORK
Product & Engineering workflows
Explore practical AI workflows for product & engineering: inputs, implementation steps, human checks and downloadable skills to adapt to your team.
ESSENTIALS / THREE FOUNDATIONS
People. Projects. P&L.
Build the foundations with three practical skills.
Start with what your team does.
Choose your recurring activities to build a starting set.
Turn a decorative concept into a fabrication review prototype
Develop a bounded 3D concept and sample specification for a fabrication expert to inspect before physical production.
Map missing interface states before implementation
Expand a proposed product flow into an explicit matrix of normal, empty, error, permission and recovery states so designers can close gaps before development.
Refresh a storefront while preserving its existing URL map
Prepare a storefront redesign in staging with an explicit old-to-new URL map and checks for catalog, checkout and analytics continuity.
Find evidenced friction in real customer session replays
Investigate a specific customer journey using recorded sessions and product evidence. Turn verified obstacles into a focused product review queue.
Replay recorded AI responses in integration tests
Create controlled response fixtures so application tests run reproducibly without making an unplanned live model call.
Build a maths practice generator
Provide teachers and learners with a mobile interface for generating practice sets from a checked question bank.
Build a shared view of product feedback
Combine support requests, discussions, and development tasks, group them by topic, and explain recurring problems.
Bring product feedback from multiple channels together
This workflow combines messages, forms, and customer context into a shared feedback database with AI search. Designed for product teams.
Draft product updates from code changes
Turn merged code changes into concise product updates that explain the user-facing features and fixes.
Check a web release through real customer journeys
Exercise the application in a browser to catch broken navigation, forms, missing assets, and layout problems before customers encounter them. Cover desktop and mobile behavior.
Find which page resources slow the customer experience
Use a measured page trace and network evidence to locate slow loading, delayed rendering, and layout shifts. Turn confirmed causes into a prioritized improvement list.
Turn an agreed product discussion into a feature brief
Consolidate settled product decisions into a document engineering can review. Make intended behavior, exclusions, and validation decisions explicit before implementation begins.
Break a feature into independently verifiable tickets
Convert a complete feature brief into small delivery units that each demonstrate useful behavior. Keep actual dependencies visible so teams can review the order of work.
Compare interface options before building the product
Use small disposable prototypes to answer a specific interaction or layout question. Compare alternatives with stakeholders and preserve the decisions that should guide production work.
Turn an unclear request into an actionable issue
Investigate a reported problem or enhancement before placing it in the implementation queue. Check existing behavior and prior decisions, then identify the evidence or decisions still missing.
Turn a support incident into a reviewed code change
Connect a customer-reported failure to relevant logs, repository context, and a repair workflow so support and engineering work from the same evidence.
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