AI & language models
Understand the model. Shape the response.
Model behavior, prompt design, and outputs you can evaluate.
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THE DEVELOPER’S FIELD GUIDE
A clearer path through AI, LLMs, agents, REST, and the tools between them. Understand the possibilities. Ask better questions. Plan your next integration.
Independent perspectives.
Practical next steps.
CHOOSE YOUR DIRECTION
Find a useful starting point, then follow the connections that matter to your project.
AI & language models
Model behavior, prompt design, and outputs you can evaluate.
Agents & connections
Tool calls, assistant behavior, and the role of MCP.
REST & the web
HTTP methods, web integrations, WordPress, and Django.
Models & developer tools
Independent reading paths for providers, models, and IDEs.
Companies & research
Company research, structured evidence, and vendor questions.
Quality & security
Practical QA, permission checks, and scoped security work.
AI, WITH INTENTION
Learn the decisions that connect language models to useful application behavior.
Define the job, provide the right context, and set a boundary for the response.
Explore prompt design 02 / EVALUATEConnect instructions, structured output, and checks that reflect your actual task.
Explore LLM outputs 03 / CONNECTUnderstand tool calls, permission boundaries, and where the application stays in control.
Explore AI agentsBUILD ON THE BASICS
Follow the request, understand the contract, and decide what you need to verify.
Illustrative resource paths · Concepts explained in the guides
MAKE SENSE OF THE ECOSYSTEM
Explore each provider or tool through its role in a development workflow.
Independent educational guides. Provider names identify the subjects covered.
EXPLORE API LAB
Practical articles for the questions that come up when you build.
Make model-proposed actions useful by designing narrow tools, checking authority in code, and reporting exactly what execution accomplished.
Build a repeatable REST API workflow that separates retrieval, replacement, retries, and concurrent updates.
Build an AI API evaluation around real product tasks and explicit acceptance criteria, then compare quality, delivery, data handling, and operational fit with traceable evidence.
BEFORE YOU DIVE IN
Find your next step without getting lost in the terminology.
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