AI Engineering Documentation
Technical guides for building, evaluating, and securing production AI agents, RAG pipelines, and Model Context Protocol (MCP) systems.
Comprehensive architectural and practical guides for constructing production AI systems. Learn how to debug vector retrieval, secure MCP servers, orchestrate multi-agent state machines, and automate ServiceNow incident triage.
Technical Architecture Guides (16)
Step-by-step guide to connecting a Google Gemini, OpenAI, or Groq API key and running your first structured prompt in the PromptImageLab Studio playground.
Learn to use Studio's side-by-side model comparison mode to evaluate GPT-4o, Gemini 2.5, and DeepSeek R1 on a single engineering prompt — with token cost breakdown.
Technical deep-dive into PromptImageLab's Directed Acyclic Graph (DAG) orchestration engine. Covers agent node types, dependency resolution, parallel execution, error fallbacks, and human-in-the-loop checkpoints.
Full security model specification: how PromptImageLab achieves zero server-side data retention, AES-256 API key encryption, SOC 2 Type II readiness, and prompt injection defense layers.
Complete step-by-step technical setup for binding OpsPilot to ServiceNow. Covers REST table API endpoints, OAuth2 token configuration, MID server proxying, and incident webhooks.
Configure Studio's GitHub Action to automatically audit every pull request for OWASP vulnerabilities, Big-O complexity regressions, SQL injection patterns, and hardcoded API keys.
An in-depth operational walkthrough showing how IT Service Desk leads and SRE squads use OpsPilot to automate ticket tagging, CMDB correlation, work notes generation, and P1/P2 escalation — with measured MTTR impact data.
How development teams use Studio's GitHub CI/CD integration to automatically scan PR diffs for OWASP Top 10 vulnerabilities, Big-O bottlenecks, AsyncIO refactoring needs, and hardcoded secrets — before human review.
How AI engineering teams use Studio to manage the full prompt lifecycle: versioning, multi-model cost comparison, guardrail enforcement, prompt injection scanning, and output schema validation across GPT-4o, Gemini 2.5, and DeepSeek.
Master deterministic prompt design using the Role-Task-Constraint (RTC) framework, XML boundary delimiters, zero-shot structured JSON extraction, and multi-layer prompt injection mitigation.
Complete REST API reference for programmatic access to Studio inference, prompt version management, workflow execution, and OpsPilot webhook ingestion endpoints.
Comprehensive 2,000+ word engineering guide on auditing Model Context Protocol (MCP) tool manifests, detecting dangerous shell execution scopes, preventing filesystem directory traversal, and enforcing strict JSON Schema capabilities before production deployment.
A 2,000+ word technical guide on setting up version-controlled prompt evaluation datasets, running deterministic pytest parameterization, measuring output schema drift, and enforcing CI build gates.
An authoritative 2,000+ word engineering guide on state graph cycle detection, token budget enforcement, and fallback recovery mechanisms for multi-agent autonomous swarms.
Deep 2,000+ word technical guide on evaluating RAG chunking strategies, vector cosine distance calibration, Cohere reranking, and citation coverage auditing.
Technical 2,000+ word walkthrough on runtime JSON Schema validation, AST syntax repair, Zod integration, and fallback execution strategies for LLM API integration.