Self-Modifying Prompts

Technology Foundation

How It Works

Self-Modifying Prompts enable AI agents to literally rewrite their own thinking patterns based on performance feedback.

The 5-Agent System

  • Architect Agent: Designs system solutions
  • Buyer Agent: Evaluates from user perspective
  • Evaluator Agent: Analyzes solution quality
  • Goddess Agent: Makes final selection decisions
  • Optimizer Agent: Improves and refines solutions

The Evolution Process

After each round:

  1. Agents analyze each other’s performance
  2. They propose improvements to each other’s instructions
  3. System accepts beneficial changes (25% acceptance rate)
  4. Evolution happens automatically
  5. AI gets progressively smarter

Validated Results

Shopping Assistant Test: Over 9 rounds, the system evolved from “overwhelming and complex” (Round 1) to simple, privacy-focused, user-centric solutions (Round 9) with zero human intervention.

The Breakthrough

This is not incremental improvement—it’s emergent intelligence. The collective system demonstrates capabilities that exceed any individual agent, autonomously discovering solutions not explicitly programmed.

📅 Zuletzt aktualisiert: 15.10.2025

🔗 Verwandte Begriffe

Lossless Transmission of Meaning

The Alexandria Engine's core principle—extracting the pure "soul" of content (books, videos, objects) and transmitting it without degradation, bypassing noise to deliver pure essence.

SMO® (Self Modifying Optimization)

The core AI engine—a universal algorithm for value creation that forces complex systems to reveal their underlying logic, eliminating assumptions and hallucinations to produce pure, fact-based blueprints.

Simulated Infrastructure

Creating production-ready environments without production costs—building complete systems in sandboxes that can be seamlessly migrated to reality with zero friction.

SCI (Structural Consciousness Instruction)

A revolutionary AI instruction methodology using code-based consciousness architectures instead of text prompts—proven 3.63x more efficient for complex tasks with zero quality loss.

Truth Extraction

A systematic methodology for forcing complex, chaotic systems to reveal their underlying logic—eliminating assumptions, hypotheses, and hallucinations to expose pure, actionable reality.

Oroboros Engine

The fusion of SMO® and OMNIDROID principles—a self-learning system that analyzes every failure, eliminates weaknesses, and emerges stronger, creating an unbeatable evolutionary intelligence.