Leo J. Li

Editorial focus

Each guide separates sourced facts, first-party observations, author frameworks, and limitations. Technical articles lead with a direct answer, expose their diagnostic method, and link to reusable artifacts when a template adds more value than prose.

• AI agent security and authority boundaries
• AI agent observability and evaluation
• SRE investigation and operational evidence
• Context, memory, and durable workflow state
• MCP services, agent skills, and production agent platforms
• AI cost engineering
• Technical SEO and generative-engine visibility

Books by Leo J. Li

• AI Agent Platform EngineeringFrom Prototype to Production: Orchestration, State, Queues, Retries, Identity, Deployment, and Operations
• AI Agents for SREBuilding LLM Root Cause Analysis on OpenTelemetry Traces, Logs, and Metrics
• AI Cost EngineeringToken Economics, Model Routing, Caching, Capacity, and Cost per Outcome
• AIOps in ProductionFrom Intelligent Thresholds to Graph Reasoning and Reliable Automation
• Build Your First App with AIA Step-by-Step Guide for People Who Have Never Written Code
• ClickHouse Observability at ScaleBuild a Unified OpenTelemetry Platform for Logs, Metrics, and a Million Spans per Second
• Context Engineering in ProductionDesigning Memory, Retrieval, State, Provenance, and Long-Running Agent Workflows
• Engineering Judgment in the Age of AIFrom Writing Code to Making Tradeoffs: A Practical Guide to Questions, Verification, and Failure Drills for Early-Career Developers
• Evaluating AI AgentsFrom Golden Datasets and Trace Grading to Simulation, Red Teaming, and Production Quality Gates
• EvoOntology in PracticeBuilding and Evaluating Self-Evolving Semantic Layers for Data Agents
• From the Field to the ProductHow Forward Deployed Engineering Turns Real-World Problems into Scalable Products
• Generative Engine OptimizationFrom Search Rankings to Accurate Discovery, Understanding, and Citation by AI
• LLM-as-a-Judge in PracticeA Complete Guide to Expert-Led Evaluation
• MCP in ProductionSecurity, Observability, Versioning, and Governance for Agent Tooling
• Observability for AI AgentsTracing Models, Tools, Memory, and Multi-Agent Workflows with OpenTelemetry
• Ontology-Driven Forward Deployed EngineeringAn Enterprise Architecture for Turning Domain Meaning into Governed Operational Systems
• Securing AI AgentsPrompt Injection, Tool Permissions, Identity, Sandboxing, Memory Poisoning, and Audit Trails
• Skills in ProductionDesigning Governed, Secure, and Self-Evolving Agent Capabilities
• Understanding the Magic Quadrant for Observability PlatformsA Practical Guide to Platform Architecture, AIOps, and Enterprise Adoption
• Why Systems FailFrom Ontology Modeling, Observability, and CMDB to AI-Agent Root Cause Investigation

Publication identity

Author

Leo J. Li

Publisher

Signal Studio

Language

English (United States)

Verified external profile

Leo J. Li on Medium

Method and corrections

Read the evidence-first editorial method, including what automated checks do and do not verify. Confirmed corrections are recorded on the errata page.