Level 4 Anticipatory Intelligence for Software Engineering
Select a wizard below and provide code or requirements to see Level 4 Anticipatory Intelligence in action.
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Wizards now work together with shared intelligence, automatic routing, and cross-wizard learning.
Just describe what you need in natural language. The router automatically dispatches to the right wizard(s).
"Fix security issues in auth.py"
→ Routes to: SecurityWizard + CodeReviewCross-wizard intelligence sharing. Findings from one wizard inform all others.
SecurityWizard finds SQLi → BugPredict
knows to watch for similar patternsWizards automatically trigger related wizards based on findings and configurable rules.
SecurityAudit (high severity) →
auto-triggers DependencyCheckfrom empathy_os.routing import SmartRouter, quick_route
# Natural language wizard dispatch
router = SmartRouter()
decision = router.route_sync("Fix security issues in auth.py")
print(f"Primary: {decision.primary_wizard}") # security-audit
print(f"Chain: {decision.suggested_chain}") # [security-audit, dependency-check]
print(f"Confidence: {decision.confidence}") # 0.92Predicts bugs before they manifest in production with trajectory-based analysis.
Identifies vulnerabilities and security risks across your entire codebase.
Predicts performance bottlenecks and optimization opportunities before deployment.
Automatically generates and maintains comprehensive code documentation.
Multi-agent system for complex development tasks with coordinated AI assistants.
Coordinates multiple AI agents for complex, multi-step development workflows.
Implements Retrieval-Augmented Generation patterns for context-aware AI responses.
Analyze, generate, and optimize prompts with token reduction and chain-of-thought scaffolding.
Orchestrates multiple AI models for optimal results across different tasks.
Empathy continuously analyzes your codebase, tracking changes, patterns, dependencies, and code quality metrics in real-time.
AI wizards identify code patterns, anti-patterns, and trajectories that indicate potential bugs, security vulnerabilities, or performance issues before they occur.
The system generates proactive recommendations with code fixes, optimizations, and best practice suggestions before issues reach production.
Long-term memory enables the system to learn from your project's history, improving predictions and adapting to your team's coding patterns over time.
"The framework transformed our development workflow. Instead of discovering issues weeks later during debugging, the wizards alerted us to emerging problems immediately. We shipped higher quality code, many times faster."
Empathy is Fair Source licensed and production-ready. Start building anticipatory AI for software development today.