The Autonomous Debugging Pipeline

From Production Error to Deployed Fix

Experience the fully automated pipeline that detects, analyzes, and deploys fixes without human intervention—all within minutes.

The 6-Stage Pipeline

Each stage is optimized for speed, accuracy, and safety

01

Error Detection

Sentry MCP streams production errors in real-time. Development errors captured via VSCode extension. CI/CD failures routed through webhook integration.

Real-time error streaming from Sentry
Development error capture via VSCode
CI/CD webhook integration
Error classification and routing
02

Context Enrichment

Reads .lattice/ folder for relevant specs. Maps error to affected spec contracts. Retrieves mutation history from Lattice. Gathers git commit context.

.lattice/ folder analysis
Spec contract mapping
Mutation history retrieval
Git context correlation
03

Root Cause Analysis

AI model analyzes error + context. Compares code implementation vs. spec contract. Identifies missing/incorrect implementations. Scores confidence in root cause.

AI-powered analysis
Spec vs implementation comparison
Confidence scoring
Impact assessment
04

Safety Validation

Checks error against configured safety rules. Determines if autonomous fix is allowed. Calculates risk score (0-10). Decides approval path: auto, review, or escalate.

Safety rule validation
Risk score calculation
Approval path determination
Autonomous vs human-in-loop
05

Fix Generation

BugSage sends task to Lattice. Lattice assigns to appropriate coding agent. Agent generates code based on spec + diagnostic. Automated tests written alongside fix.

Task assignment to Lattice
Coding agent orchestration
Spec-aware code generation
Automated test creation
06

Deployment & Monitoring

VSCode extension receives commit notification. Shows diff with diagnostic context. Auto-commits (if safety rules allow). Canary deployment to production.

VSCode Git integration
Diff review with context
Automated commits
Canary deployment

Technical Stack

Built with modern technologies for performance and reliability

Error Detection
Sentry MCP Client
Production error streaming
VSCode Language Server
Development error capture
CI/CD Webhook Handler
Testing integration
AI/ML Models
Code Analysis
Fine-tuned CodeBERT
Root Cause
GPT-4 with custom prompts
Pattern Matching
Custom similarity model
Risk Scoring
Trained on historical data
Parsers & Analyzers
Multi-language
Tree-sitter
Spec parsing
Custom YAML/JSON parser
Stack trace
Enhanced error-stack-parser
Git analysis
isomorphic-git
Storage
Local
SQLite (diagnostics cache)
Cloud
PostgreSQL (historical data)
Files
Cloudflare R2 (reports, diffs)
Queue
Redis (task distribution)

Privacy & Security

Your code and data security are our top priorities

Local-First Architecture

Analysis runs on your machine by default. No code sent to cloud unless explicitly enabled.

Zero Code Storage

Only diagnostics metadata stored in cloud. Your source code never leaves your environment.

End-to-End Encryption

Cloud sync uses E2E encryption. SOC 2 Type II compliance in progress.

Self-Hosted Option

Enterprise plans include air-gapped deployment for maximum security.

Performance Metrics

Optimized for speed and efficiency

< 1 second
Error analysis
< 500ms
Spec correlation
2-5 minutes
Fix generation
< 100ms
VSCode response

See it in action

Watch a 3-minute demo of the full autonomous pipeline