
Structured Prompt Engineering for Enterprise Systems
Move beyond casual text prompts. Learn the principles of structured prompt engineering with XML boundary tags, explicit constraints, and prompt injection defense.
Technical guides and step-by-step instructions on building cloud-native applications, engineering thought leadership, and scaling Agentic AI.

Move beyond casual text prompts. Learn the principles of structured prompt engineering with XML boundary tags, explicit constraints, and prompt injection defense.

Build robust evaluation pipelines for AI systems. Implement exact-match test suites, schema validators, and the LLM-as-a-judge pattern to grade output quality and policy compliance.

Master sampling parameters in the Gemini API. Understand temperature tradeoffs between determinism and creativity, utilize stop sequences, and inspect finish reasons.

Learn how conversational memory works in Large Language Models. Master message roles, state accumulation, session helpers, and persistent system instructions using the Gemini API.

Master the foundational request-response pattern of Large Language Models using the modern Google GenAI Python SDK. Learn authentication, model selection, prompt dispatching, and response handling.

One harness does not fit every programming language, domain, or review type. Learn how to build dynamic tool registries that serve language-specific tools, a model router that assigns the right LLM to the right task complexity, and domain-tuned system prompts — then wire everything together into the complete DevPulse production system.