πŸ“… 2025-04-14 β€” Session: Developed the PromptFlow AI Workflow Protocol

πŸ•’ 16:40–18:00
🏷️ Labels: Promptflow, Ai Workflows, YAML, JSON, Standardization
πŸ“‚ Project: Dev
⭐ 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 developer’s 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.