How I Built a Self-Improving AI Agent That Evolves Its Own Mind

Aakash Khadikar — Tue, 08 Jul 2025 10:43:42 +0000

"A walkthrough of designing an AI agent that rewrites its own strategies using recursive optimization, inspired by meta-learning and AGI research."

What if an AI could improve itself without external supervision? That question became the seed for this project.

🧠 The Goal

Build a recursive self-improving agent — a system that:

Writes its own prompts
Evaluates and critiques its past runs
Updates internal strategies autonomously
Learns over time via feedback loops

Inspired by meta-learning, recursive self-reflection, and AGI architecture principles.

🛠️ Tech Stack

Component	Tools/Approach
LLM Engine	Ollama (local inference)
Evaluation Logic	Chain-of-Thought + Self-Critique
Memory	JSON logs + vector database
Planning	Dynamic Prompt Rewriter
Tuning	Self-generated hyperparameter sweep

🔁 Self-Improvement Loop

The core of the agent is a recursive reasoning loop:

Draft an initial plan (prompt)
Execute it using the local LLM
Evaluate outcome quality
Rewrite plan if performance is subpar
Retry and compare outcomes

This loop continues until a threshold of self-satisfaction is reached.

[Plan] → [Run] → [Critique] → [Update Plan] → [Repeat]

🧪 Key Capabilities
🧩 Self-rewriting prompts: Agent modifies its own logic mid-task.
🎯 Performance-aware optimization: Adjusts strategies based on reward or error signals.
🗃️ Memory persistence: Learns over sessions by storing and referencing past runs.
💡 Emergent reasoning patterns: Shows signs of internal deliberation and experimentation.

🌱 Why This Matters
Most AI agents are static. But real intelligence — human or artificial — is dynamic, reflective, and adaptive. This project is a step toward AGI systems that can:
Grow over time
Adapt to new challenges
Optimize themselves without hardcoded updates

📚 What's Next
Multi-agent dialogue: Let multiple internal agents debate and vote
Goal generalization: From task-specific to goal-agnostic optimization
Ethics layer: Align improvements with human feedback

📂 Open Source
I’ll be open-sourcing the full codebase + research notes soon.
Follow me or drop a comment if you’re interested in contributing or testing the system.

Thanks for reading — and if you're building something similar, I’d love to connect 🚀

Forem: Aakash Khadikar

How I Built a Self-Improving AI Agent That Evolves Its Own Mind

🧠 The Goal

🛠️ Tech Stack

🔁 Self-Improvement Loop