v3.12.0 - Progress Tracker + CI/CD Agent Framework

Supercharge Your AI Agents with
Intelligent Reasoning

J4C Enhanced Agent Framework provides 22 mental models, GNN-powered recommendations, reasoning orchestration with cause-effect mapping, real-time progress tracking, CI/CD agent automation, and heuristic learning to make your AI agents smarter.

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22
Mental Models
7
Categories
GNN
Recommendations
IAM2
Auth Integration

Powerful Features

Everything you need to enhance your AI agents with structured reasoning and intelligent recommendations

22 Mental Models

Comprehensive collection of thinking frameworks across 7 categories including analytical, creative, decision-making, risk assessment, systems, human factors, and strategic models.

First Principles Systems Thinking Inversion

Reasoning Orchestration

Chain of thought reasoning with step-by-step tracking, model synergies, and comprehensive cause-effect mapping for transparent AI decision-making.

Chain of Thought Cause-Effect Synergies

GNN Recommendations

Graph Neural Network powered model recommendations with 3 message-passing layers and 4 attention heads for intelligent model combination suggestions.

Graph Neural Network Attention Mechanism

IAM2 Integration

Enterprise-grade authentication with Aurigraph IAM2 (Keycloak). OAuth2/OIDC support, token validation, and role-based access control.

OAuth2 OIDC RBAC

SPARC Project Management

Built-in SPARC methodology support with GitHub API integration for seamless project tracking, sprint planning, and velocity monitoring.

SPARC GitHub Sync Sprints

Team Learning

Share insights across agent teams, track experience, and leverage collective learning for improved problem-solving over time.

Experience Sharing Team Insights

Progress Tracker

Real-time PRD/JIRA/GitHub correlation with sprint velocity tracking, burndown charts, gap analysis, and automated progress reporting.

PRD Correlation Velocity Gap Analysis

CI/CD Agent Framework

Automated deployment with @J4CDeploymentAgent, @QAQCAgent integration, 3-tier escalation strategy, and self-hosted runner support.

Auto Deploy QA/QC 3-Tier Escalation

Heuristic Learning

8 Chain of Thought reasoning strategies, 22 trading mental models, and adaptive learning from deployment patterns and errors.

CoT Engine Adaptive Learning Pattern Recognition

22 Mental Models

Structured thinking frameworks organized into 7 categories for comprehensive problem-solving

First Principles
Analytical
Systems Thinking
Analytical
Inversion
Analytical
Analogical
Creative
Lateral Thinking
Creative
SCAMPER
Creative
Cost-Benefit
Decision
Decision Matrix
Decision
Pre-Mortem
Risk
Second-Order
Risk
Feedback Loops
Systems
Empathy Mapping
Human

Cause-Effect Reasoning

Every mental model includes structured cause-effect mapping for transparent decision-making

Example: First Principles Thinking

Trigger

Complex problem with unclear solution path

Cause

Apply first principles decomposition

Effect

Reveals fundamental components and assumptions

Outcome

Novel solutions emerge from basic truths

Enterprise Integrations

Seamlessly connect with your existing infrastructure and tools

Aurigraph IAM2

Full OAuth2/OIDC integration with Keycloak-based IAM2. Support for user authentication, token validation, and service-to-service communication with automatic token caching.

GitHub API

Sync your SPARC projects with GitHub repositories. Automatic issue creation, milestone tracking, and commit history integration for seamless project management.

JIRA

Connect your sprints and backlogs with JIRA for enterprise project tracking. Bi-directional sync keeps your teams aligned across tools.

Key Benefits

Why teams choose J4C Framework for their AI agent development

1

Structured Reasoning

Replace ad-hoc thinking with proven mental models that guide agents through complex decisions systematically.

2

Transparent Decisions

Cause-effect mapping provides full visibility into why your agents make specific recommendations.

3

Intelligent Recommendations

GNN-powered suggestions help agents choose the right combination of mental models for each problem.

4

Enterprise Security

IAM2 integration ensures your AI agents operate within proper authentication and authorization boundaries.

5

Continuous Learning

Track agent performance, share experiences across teams, and improve reasoning over time.

6

Developer Friendly

RESTful API with comprehensive documentation makes integration straightforward for any platform.

Simple API

Get started with just a few API calls

// Get enhanced mental models with cause-effect mapping const response = await fetch('https://j4c.aurigraph.io/api/v3/models/enhanced'); const models = await response.json(); // Start a reasoning chain const chain = await fetch('https://j4c.aurigraph.io/api/v3/reasoning/chain', { method: 'POST', body: JSON.stringify({ problem: 'How to optimize our deployment pipeline?', context: { domain: 'devops', complexity: 'high' } }) }); // Add reasoning steps with cause-effect tracking await fetch(`https://j4c.aurigraph.io/api/v3/reasoning/chain/${chainId}/step`, { method: 'POST', body: JSON.stringify({ modelId: 'first_principles', input: 'Current pipeline has 15 minute build time', output: 'Identified 3 unnecessary steps that can be parallelized', causeEffect: { trigger: 'Slow build time impacting developer productivity', cause: 'Decomposed pipeline into fundamental steps', effect: 'Found sequential steps that could run in parallel', outcome: 'Potential 60% reduction in build time' } }) });

Ready to Enhance Your AI Agents?

Start using structured reasoning and intelligent recommendations today

Launch Dashboard API Documentation