🔁 The Learning Loop for AI Safety

Stop AI From Repeating Mistakes

Self-learning AI governance that captures LLM failures, learns patterns, and prevents your Claude, Gemini, or Codex from making the same mistake twice.

87%
Context Reduction
70%
Faster Responses
100%
Test Coverage
guardloop interactive
$ guardloop run claude "implement user authentication"
📋 Task: code (confidence: 0.95)
🛡️ Guardrails: ✅ Applied (static + 12 learned rules)
📈 Learned Rule #7: "Always add MFA with Azure AD"
✅ Implementation validated
💾 Created 3 file(s):
- auth/jwt_manager.py (auto-saved)
- auth/middleware.py (auto-saved)
- tests/test_auth.py (auto-saved)
$
The Problem

AI Assistants Have Amnesia

They make the same mistakes over and over, with no memory of what went wrong before.

Forgotten Tests

You reminded Claude to add tests last week. Today? No tests again.

🔓

Security Gaps

Missing MFA, weak auth, exposed secrets - the same vulnerabilities every time.

💥

Broken Code

AI rewrites entire files, breaks working logic, ignores your patterns.

📋

Compliance Chaos

GDPR, ISO, SOC 2 requirements? The AI forgets them constantly.

The Solution

A Self-Learning Feedback Loop

GuardLoop captures failures, learns patterns, and prevents repeats automatically.

1

Capture

Every AI interaction logged to SQLite

2

Analyze

Pattern detection finds recurring failures

3

Learn

Dynamic guardrails auto-generated

4

Enforce

Rules injected into next prompt

Features

Adaptive AI Governance

🛡️

Guardrail Injection

Every AI prompt includes your organization's standards automatically

🔍

Real-time Detection

Catch security issues, bad patterns, and failures before they reach code

👥

Multi-Agent System

13 specialized agents ensure comprehensive quality validation

🔐

Security-First

MFA, Azure AD, RBAC enforced by default in all implementations

📈

Compliance Ready

Built-in support for ISO 27001, GDPR, SOC 2

See It In Action

From Mistake to Guardrail

Week 1 AI Makes Mistake
# AI-generated code (missing error handling)
async def fetch_user_data(user_id):
    result = await db.query("SELECT * FROM users WHERE id = ?", user_id)
    return result
# ⚠️ Problem: No try-catch block!
Week 2 GuardLoop Learns
$ guardloop analyze --days 7

📊 Pattern Detected:
   - 5 failures: Missing try-catch in async DB calls
   - Confidence: 0.85
   - Severity: high

🧠 Generated Dynamic Guardrail:
   "Always wrap async database calls in try-catch blocks"
   Status: validated → enforced
Week 3 Never Happens Again
# AI now generates (with learned guardrail)
async def fetch_user_data(user_id):
    try:
        result = await db.query("SELECT * FROM users WHERE id = ?", user_id)
        return result
    except DatabaseError as e:
        logger.error(f"Failed to fetch user {user_id}: {e}")
        raise
# ✅ Problem solved permanently!
Compatibility

Works With Your AI Tools

One system for all your AI assistants

Claude

✅ Fully Supported

Gemini

🚧 In Development

Codex

🚧 In Development

Custom LLMs

📋 Planned
Quick Start

Get Running in 60 Seconds

1

Install GuardLoop

pip install guardloop
2

Initialize

guardloop init
3

Use Any AI Tool

guardloop run claude "your prompt here"

Note: GuardLoop v2.0 is in alpha. Core features work great, advanced features coming soon. See status →

Stop Repeating AI Mistakes Today

Join developers using GuardLoop to build safer, smarter AI workflows