In 30 seconds
- AI-assisted: same process, AI helps individuals go faster.
- AI-native: roles, flow and practices redesigned around AI.
- Most teams start assisted; few are truly native yet.
Pick AI-assisted when…
- The team is new to AI tools
- Quality and compliance processes can't change quickly
- You want gains without reorganizing
Aim for AI-native when…
- Review, testing and deployment are already highly automated
- The team can rethink roles and events
- Specs and evaluations are treated as first-class work
Side by side
| AI-assisted | AI-native | |
|---|---|---|
| Process | Unchanged | Redesigned around AI |
| AI's role | Helper for individuals | Participant in the workflow, including agents |
| Main human work | Writing code | Specifying, reviewing, deciding |
| Bottleneck | Same as before | Review and product decisions |
| Key artifact | Code | Specs and evals |
Myth vs reality
Myth · Buying AI tools makes a team AI-native.
Reality · Native means the workflow changed, not the toolset.
Myth · AI-native teams need fewer people.
Reality · They need different emphasis: more review and product judgment.
Myth · AI-assisted is a failure state.
Reality · It's a sensible starting point.
FAQ
How do we know which we are?
If you removed AI tomorrow and nothing about your process would change, you're assisted.
Should every team aim for native?
Not necessarily; it depends on risk, domain and readiness.
What's the first step toward native?
Make specs and review explicit, visible parts of the workflow.