What we explored
Solutions Lab · Building
AI-Assisted Application Development
Hands-on work with modern AI-assisted software development to understand where it changes delivery speed, architecture choices, review needs, and build-versus-buy economics.
Why it matters
Clients increasingly need an independent view of when custom development, packaged software, or a hybrid approach makes sense. Direct experience improves the quality of those decisions.
What B2 built or tested
- AI-assisted application scaffolding and iteration
- Authentication, user-role, dashboard, and workflow patterns
- Human review of AI-generated code and architecture decisions
- Rapid prototyping before committing to a production path
Technical context
- React-based application development
- Supabase-backed data and authentication patterns
- AI-assisted coding environments
- Application logging and administrative controls
What B2 learned
- AI can compress parts of the software-development cycle substantially
- Faster code generation increases the value of architecture, review, testing, and systems judgment
- The right build-versus-buy answer depends on operating context rather than a blanket preference for custom software
Where it could apply
- Internal operating tools
- Client-facing workflow applications
- Rapid validation of process or product concepts
- Targeted alternatives to narrow SaaS use cases
Solutions Lab projects document active research and learning. They do not imply that an experimental capability is a mature client product.
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