Learning. Experimenting. Sharing reliable stories.
A coordinated system of specialized agents working together to ensure reliability
Continuous monitoring of service health and business SLIs. Scout filters irrelevant metrics to identify true signals of degradation across the fleet.
Analogy // The Fire Lookout Identifies the first plume of smoke amidst thousands of signals before the forest burns.
Cache-Augmented Generation. Checks the tactical knowledge cache for known failure patterns. If a match is found, bypasses heavy reasoning for sub-second recovery.
Analogy // Muscle Memory Pulling your hand away from a hot stove before your brain even processes the heat.
The reasoning layer powered by LangGraph. It correlates Jaeger traces and OpenTelemetry signals to perform multi-step cognitive evaluation before requesting any high-impact fix.
Analogy // The Detective Examines fingerprints (Otel traces) and checks the alibi (logs) to identify the true culprit.
Enforces safety policies and architectural constraints. Guardrail evaluates every proposed action against the blast-radius policy to prevent cascading failures.
Analogy // The Brake System Ensuring the car doesn't go off the cliff, no matter how hard the driver hits the gas.
Executes remediation only after multi-step decision loops. Uses GitOps via GitHub MCP to ensure all actions are auditable, version-controlled, and reversible.
Analogy // Controlled Demolition Precise, approved, zero collateral damage.
The Improved Memory Agent. Manages the RAG knowledge base by evaluating, indexing, and merging triage logs into ChromaDB for future retrieval.
Analogy // The Librarian Archiving every troubleshooting journey so the system never repeats the same mistake.
Google Jules operates as the final architectural authority, triggered only for chronic or systemic failures. Jules performs deep code refactoring—introducing circuit breakers, safety patterns, and structural fixes rather than just symptoms.
System Sync
Whenever an anomaly is detected by Scout, it is first routed to CAG for an instant troubleshooting match. If the cache misses, the Brain (LangGraph) initiates a multi-step triage cycle, correlating traces with historical data. Every decision is then passed through the Guardrail for safety validation before Fixer implements the change. Finally, Curator indexes the entire lifecycle to improve future triage.
Production systems and experiments in autonomous reliability engineering
Built an AI-assisted system using LangChain to automate root cause analysis through trace correlation. The system uses multi-step evaluation to ensure safe action selection before resolution.
Operational Reality
Substantial reduction in manual intervention and engineer toil.
Integrated Confluence runbooks into a RAG retrieval layer, orchestrated via LangChain. This provides agents with verified operational context, ensuring reasoned triage flows.
Operational Outcome
Safe issue resolution by grounding decisions in approved enterprise knowledge.
Built an AI-assisted proof-of-concept to detect synthetic, manipulated, or inauthentic images in enterprise submissions—addressing a real operational challenge in insurance.
Focus Area
Building trust, integrity, and scale through explainable validation systems.
Real-world experiences and lessons learned from building reliable systems
How caching tactical issue signatures reduced resolution time from minutes to 2 seconds for known recurring anomalies.
When the Brain Agent proposed a cascading restart of the production ingress. How Guardrail stepped in and blocked the request.
Solving a "ghost error" in the payment gateway by linking current traces to a similar event from a 2024 deployment archive.
Regional failure analysis: Why high-availability is not a substitute for architectural discipline during cloud degradations.
Validating structural resilience through controlled fault injection. Identifying dormant failure modes before they trigger customer-facing issues.
Bridging real-time observability and long-term memory to reduce triage errors during critical system events.
Why agents must never have full sovereignty. Balancing self-healing with strictly defined blast-radius control.
Managing the risks of high-velocity automation. Why intent-based reasoning must precede triage actions to prevent failure loops.
Deconstructing the operational loop from signal detection to reasoned resolution. Aligning technical observability with user health.
An integrity verification POC addressing the real-world risk of inauthentic submissions. Protecting automated triage logic through trust validation.
Shifting from infrastructure metrics to CUJ health. Why your CPU graph is lying about user satisfaction.