Founding Architecture: Complete Setup Guide for Custom Workout Prompts
AI Fitness Architecture: Core Framework Guide
Welcome to the AI Fitness Architecture Toolkit member forum! This foundational guide gives you direct, battle-tested prompt engineering frameworks to generate tailored, progression-ready workout programs using any modern LLM (Claude, ChatGPT, or Gemini).
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How to Deploy These Prompts
Copy the system prompt and fill in your bracketed parameters (
[AGE],[SCHEDULE],[EQUIPMENT],[TARGET RPE]).Paste into your LLM of choice as the initial framing message.
Use the progression rules prompt weekly to recalibrate volume and load.
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Master Prompt Template
Act as an elite strength and hypertrophy biomechanist and AI fitness architect.
Design a periodized workout protocol adhering strictly to these specifications:
- Split & Frequency: [Insert days / schedule, e.g., 3-day Push/Pull/Legs or Minimalist Full Body]
- Available Equipment: [e.g., Hotel Dumbbells up to 50 lbs + Pull-up Bar]
- Primary Adaptation Goal: Hypertrophy with joint longevity
- Target Intensity & Volume: 2–3 working sets per exercise at RPE 7-9 (1-3 reps in reserve)
Rules & Progression Constraints:
1. Group exercises by movement pattern (Horizontal Press, Vertical Pull, Knee-dominant, Hip Hinge, etc.).
2. For each movement, list exact Rep Ranges, Rest Intervals, Tempo (e.g., 3-0-1-0), and RPE target.
3. Provide double progression criteria: add reps until top of range is hit across all working sets, then advance load or density.
4. Format output as a markdown table with warm-up protocols and substitute movements.---
Calibration & Progression Rules
RIR / RPE Precision: Maintain 1–2 RIR on compound movements; take isolation work to 0–1 RIR.
Progression Check: If target reps are hit with zero degradation in form across all sets, increase load by 2.5–5% in next session.
Drop your outputs, modifications, or questions below for prompt optimization feedback!