Defining AI-Native¶
A shared definition your team can use to align delivery decisions, controls, and accountability.
Why this chapter matters¶
A practical definition keeps teams aligned. AI-native delivery treats AI systems as accountable participants, not as hidden automation behind developer tools.
Key points for your team¶
Definitions matter because they influence architecture, risk posture, and team expectations. Here, AI-native means AI participates in the workflow in ways that can be reviewed and governed, not merely assisted by autocomplete.
For conference attendees, this is a useful standard to carry home: if contribution cannot be traced and reviewed, it should not be treated as production-ready regardless of how fast it was produced.
What to review with your team¶
For team discussion, use this chapter to connect AI is a participant, not a tool, Designed for, not bolted on, Every action leaves a trail, and Three words: designing, participating, accountable with your current delivery loop.
In the session context, Here is the definition Attendees can leave with. AI-native software development means designing your delivery loop so AI isn't just helping developers, it's participating alongside them. Use that framing to align engineering, platform, and governance stakeholders on concrete next steps.
Put this into practice¶
Add explicit ownership and auditability requirements to your team definition of done for any AI-assisted or agent-generated change.