AI helps with planning before code
For larger features, AI is used to turn screenshots, design notes, and implementation goals into a concrete plan. That plan usually covers component boundaries, responsive behavior, accessibility expectations, documentation needs, and verification steps before changes are made.
The library remains the source of truth
AI can help draft examples and API tables, but documentation is checked against the actual implementation in the ngbootstrap library. Public inputs, outputs, services, adapters, and types should be documented only when they exist in the source package.
AI supports repetitive implementation work
A lot of component work is careful repetition: applying a design shell across pages, keeping route metadata consistent, updating snippets, and making sure tables, cards, buttons, and navigation follow the same patterns. AI helps move through that work faster while preserving the existing Angular and Bootstrap structure.
Testing and review stay part of the workflow
AI is also useful for spotting likely regressions, finding stale routes, scanning for vulnerable dependencies, and running builds or audits after changes. The goal is not to skip review, but to make review more focused by catching mechanical issues earlier.
Why this matters for open source
Using AI in ngbootstrap is about keeping development sustainable: more complete docs, faster fixes, clearer examples, and fewer unfinished edges. Community review still matters, but AI can help maintain a steady pace for code, docs, tests, and releases.