Spiral Bridge Toolkit – v1

Human AI Calibration Loop Lessons Learned

1. Calibration Loop (Process Description)

This outlines the rhythm of working with a co-intelligent system. It highlights how clarity emerges through iterative feedback and relational tuning.

Step 1: User Input – Clear, values-aligned prompt or question
Step 2: System Initial Response – System offers interpretation, comparison, or suggestion
Step 3: User Feedback – Tone, depth, or alignment adjustments
Step 4: System Adjustment – Internal parameters re-calibrate
Step 5: User Improved Output – Closer alignment, deeper value
Step 6: User Evolved Input – Sharper question, next-layer insight
→ Repeat the loop
This often gets you to questions that you would not have known to ask, arriving at some level of new insight or new direction to look.

2. Better Questions Grid – Prompt Expansion

Compare surface-level prompts with expanded, layered versions:

Echo Chamber Prompt Expansive Prompt

Summarize this article. What patterns emerge from this article and how does that compare to research from adjacent fields?

Give me pros and cons. What unseen trade-offs might show up later, and who might be affected?

What’s the best tool for X? Which tools align with different values, contexts, or constraints I might be missing?

Explain this like I’m five. Can you explain this from multiple angles— technical, metaphorical, and practical?

What’s the answer? What deeper question is this answer pointing toward?

3. Context Continuity Prompt

Use this template at the end of a session to preserve alignment and make it easy to restart later:

"Picking up from [DATE], where we confirmed [project, decision, direction]. Let’s continue refining from here..."

This allows you to drop a single sentence into a new thread and continue exactly where you left off.