ASEN
Autonomous Software Engineering Network
A multi-agent AI system that transforms high-level requirements into production-ready software through specialized agents coordinated by a central orchestrator.
How ASEN Works
The Autonomous Software Engineering Network distributes the software development lifecycle across seven specialized agents, each with defined roles, inputs, outputs, and decision logic.
End-to-End Automation
From requirements to deployment, every SDLC phase is handled by specialized AI agents working in concert.
Built-in Quality Gates
A dedicated Reviewer Agent validates every output against standards before it advances to the next phase.
Continuous Improvement
Feedback loops and self-correction mechanisms ensure the system learns and improves with each iteration.
Real-time Monitoring
The Orchestrator maintains full visibility into system state, agent health, and pipeline progress.
Meet the Agents
Each agent is a specialized unit with defined responsibilities, inputs, outputs, and decision logic. Together they form a complete software engineering team.
ORCH
Central CoordinatorCoordinates all agents, manages system state, and handles phase transitions across the entire SDLC pipeline. Acts as the mission control brain.
PM
Requirements AnalystAnalyzes stakeholder requirements, creates user stories, defines project scope, and maintains the product backlog with prioritized features.
ARCH
System DesignerDesigns system architecture, selects technology stack, defines API contracts, and creates data models based on the approved requirements.
DEV
Code GeneratorWrites source code, implements business logic, creates unit tests, and refactors existing code based on design specifications.
QA
Quality ValidatorPerforms comprehensive testing including unit, integration, and system tests. Identifies bugs, validates requirements coverage, and generates test reports.
OPS
Deployment EngineerManages CI/CD pipelines, generates infrastructure-as-code, handles containerization, and orchestrates deployment strategies.
REV
Quality GatekeeperCross-checks every agent's output against project standards, coding guidelines, and original requirements. Acts as the validation checkpoint.
Interactive Pipeline
Click on any agent node to inspect its role, inputs, outputs, and decision logic. Connection lines show data flow between agents.
Continuous Refinement
Three distinct feedback loops ensure quality at every stage, routing work back for correction before it advances.
Internal Bug Fix Loop
When QA discovers bugs, code is routed back to the Developer Agent with detailed bug reports. The Developer fixes issues and resubmits for testing.
Architectural Clarification Loop
When implementation reveals design ambiguities, the Developer escalates to the Architect for clarification before proceeding.
User Feedback Loop
The Orchestrator surfaces requirement gaps or ambiguities to the user for clarification, ensuring the system builds what was intended.
Robust Safeguards
Multiple layers of protection ensure the system handles errors gracefully and maintains operational integrity.
Self-Correction
Each agent performs a self-review of its output using reflection prompts before submission, catching errors early.
Retry Mechanism
Failed tasks are automatically retried up to 3 times with adjusted parameters before escalation.
Human-in-the-Loop
After 3 consecutive failures, the Orchestrator escalates to a human expert for intervention and guidance.
State Persistence
Every interaction is logged to a persistent store. On system crash, the Orchestrator resumes from the last successful state.
Built for Production
Designed to scale horizontally and handle real-world workloads with fault tolerance and optimization.
| Feature | Type |
|---|---|
| Parallel Development | N agents |
| Load Balancing | Queue-based |
| State Persistence | Crash-safe |
| Timeout Management | Per-agent |
| Prompt Versioning | Optimized |
| Token Efficiency | JSON schemas |