📅 2025-04-14 — Session: Developed PromptFlow AI Workflow Protocol
🕒 16:40–18:00
🏷️ Labels: Promptflow, Ai Workflows, YAML, JSON, Standardization
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to conceptualize and formalize the PromptFlow protocol, a minimal interface for AI workflows that utilizes YAML for workflow declaration and JSON for execution traces.
Key Activities
- Explored backend orchestration using FastAPI to serve as a bridge between the frontend and AI engine.
- Connected YAML configurations to LLM runs for improved traceability and debugging.
- Developed a lightweight AI product architecture emphasizing modularity and development-friendliness.
- Articulated a new primitive for AI workflows using YAML and JSON to standardize AI logic.
- Emphasized the importance of claiming and naming the PromptFlow concept.
- Outlined a thesis for PromptFlow as a new paradigm in AI workflows.
- Proposed strategic adoption pathways for PromptFlow in platforms like Vertex AI.
- Discussed strategies to protect the integrity of the PromptFlow concept.
- Introduced PromptFlow as a minimal interface for AI workflows with expert insights.
- Framed the developer’s journey in creating PromptFlow, emphasizing its unique features.
- Theorized PromptFlow as a runtime protocol for declarative AI composition.
- Compared Dockerfile, Makefile, and pytest configurations to guide PromptFlow development.
- Encouraged self-reflection on contributions to AI development.
Achievements
- Successfully conceptualized the PromptFlow protocol, emphasizing its modularity, observability, and scalability.
- Established a framework for claiming ownership and sharing the PromptFlow concept with the community.
Pending Tasks
- Formalize the PromptFlow protocol into a comprehensive specification document.
- Begin outreach to major AI platforms for adoption and standardization discussions.