How Technology professionals use AI
Across technology, AI shows up less as a headline and more as a set of concrete, repeatable tasks. Here are the 4 roles we cover in technology and the 24 documented ways they actually put AI to work — each with the exact prompt, the workflow around it, and its sources.
4Roles
24Use cases
64Cited sources
Roles in technology
Every AI use case in technology
Jump straight to the task you need — every one includes a copy-ready prompt.
📊 Data Analysts
- SQL queries written and debugged from a described schema
- Data-cleaning and profiling scripts in Python you can audit
- Executive summaries that turn a chart into a decision
- Data dictionaries and query docs drafted from the SQL itself
- Vague stakeholder requests turned into a scoped analysis plan
- The right chart for the message, not just the data
🗺️ Product Managers
- Turning raw interview notes into themes you can act on
- First-draft PRDs that keep your assumptions honest
- Stakeholder and executive updates without the spin
- Structuring a prioritization call you still make yourself
- Competitive teardowns and battlecards grounded in real sources
- Product analytics queries you can read and trust
💻 Software Developers
- Explain unfamiliar code before you change it
- A first-pass review of your own diff before humans see it
- Generate unit tests you then verify against the spec
- Rubber-duck debugging a problem you cannot crack
- Turn a decision into an ADR or the docs you skipped
- Draft commit messages and PR descriptions from your diff
🎛️ UX Designers
- Turning interview transcripts into research themes
- Microcopy and error messages that match your voice
- Usability test plans and non-leading discussion guides
- Explaining design decisions to skeptical stakeholders
- Turning a flow into a clickable coded prototype
- Breaking design fixation with divergent concepts