π 2025-04-12 β Session: Explored AI-native MVP development and orchestration
π 04:20β05:10
π·οΈ Labels: Ai Development, MVP, Prompt Engineering, Langchain, DSL
π Project: Dev
β Priority: MEDIUM
Session Goal
The session aimed to explore various aspects of AI-native MVP development, orchestration, and the transformation of developer roles in AI systems.
Key Activities
- Reviewed a lightweight MVP boilerplate for FastAPI and Next.js, including tech stack and usage instructions.
- Discussed leveraging existing workflows to maintain momentum in MVP development.
- Reflected on the transformation from MVP makers to AI system orchestrators, emphasizing skill development.
- Explored designing Domain-Specific Languages (DSLs) for AI workflows to enable complex automation.
- Considered integrating LangChainβs JSON prompt schema for standardization in AI projects.
- Envisioned an AI-native development platform for application creation through AI prompting.
- Investigated LangChainβs
ChatPromptTemplatefor modular prompt engineering in AI applications. - Outlined a framework for AI block orchestration inspired by Next.js and Vercel.
- Highlighted the innovative potential of treating prompt blocks as first-class software artifacts.
- Discussed revolutionizing developer experience with prompt blocks as atomic units in AI workflows.
- Reflected on the skills and mindset required for pioneering in AI development.
- Reviewed a starter template for MVP development with FastAPI and Next.js.
- Reflected on practical learning experiences from building MVPs beyond academic learning.
Achievements
- Gained comprehensive insights into the development and orchestration of AI-native MVPs.
- Identified key strategies for maintaining momentum and innovation in AI projects.