π 2025-04-14 β Session: Developed the PromptFlow AI Workflow Protocol
π 16:40β18:00
π·οΈ Labels: Promptflow, Ai Workflows, YAML, JSON, Standardization
π Project: Dev
β Priority: MEDIUM
Session Goal
The primary goal of this session was to develop and formalize the PromptFlow protocol, a minimal interface for AI workflows, leveraging YAML for workflow declaration and JSON for execution traces.
Key Activities
- Outlined the architecture and endpoints for a FastAPI backend to serve as a bridge between frontend and AI engines.
- Connected YAML configurations to LLM runs, enhancing traceability and debugging.
- Planned the foundation of a lightweight AI product architecture using YAML and JSON.
- Articulated a new primitive for AI workflows to standardize AI logic.
- Emphasized the importance of claiming and naming the innovative PromptFlow concept.
- Developed a thesis outline for PromptFlow, highlighting its potential as a new interface for human-AI interaction.
- Strategized the adoption of PromptFlow within platforms like Vertex AI.
- Defended the integrity of the PromptFlow concept against potential bloat.
- Introduced PromptFlow as a minimal interface for AI workflows, focusing on standardization.
- Framed the developerβs journey in creating PromptFlow, emphasizing its unique features and philosophy.
- Outlined the theoretical framework of PromptFlow as a runtime protocol for declarative AI composition.
- Compared Dockerfile, Makefile, and pytest to guide PromptFlow tool development.
- Reflected on self-perception in AI development, emphasizing clarity and modularity.
Achievements
- Successfully developed a comprehensive framework for the PromptFlow protocol.
- Established a strategic approach for its adoption and standardization in AI development.
Pending Tasks
- Further refinement of the PromptFlow protocol for broader adoption.
- Continued engagement with the AI community to promote and share the PromptFlow concept.