Guides / Tools

Practical AI references

Visual guides and tool comparisons for enterprise AI readers who want useful shortcuts, not another pile of tabs.

Quick reference

Every OpenAI Codex command, at a glance

A visual July 2026 reference for starting sessions, planning, project context, engineering, tools, files, analysis, and sharing work in Codex.

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Every OpenAI Codex Command quick reference poster, July 2026 edition.
Codex guide

How Codex instructions and context files actually work

A practical guide to Codex surfaces, `AGENTS.md`, reference Markdown files, context loading, and the instruction priority stack that shapes output quality.

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V Vanderburgh.it CODEX CONTEXT AT A GLANCE

Surface, instructions, context loading, and priority in one model.

Surface

Choose the runtime

CLI, IDE, cloud, and ChatGPT Codex each fit a different working style.

Instructions

`AGENTS.md` first

Behavior rules belong in the repo contract, not scattered across docs.

Loading

Read on demand

Codex pulls the relevant docs and files when the task moves there.

Priority

Task wins first

The current prompt and task framing outrank passive repo context.

Governance guide

AI governance and compliance, where the real gap starts

A practical guide to the difference between AI governance and compliance, the framework stack around them, and what changes once agents and runtime controls enter the picture.

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V Vanderburgh.it AI GOVERNANCE AT A GLANCE

Strategy, proof, agent controls, and human oversight in one operating model.

Governance

Roadmap

Principles, roles, escalation paths, and long-term AI operating decisions.

Compliance

Proof

Logs, evidence, registrations, and regulator-ready technical controls.

Agents

Runtime guardrails

Tiered autonomy, checkpoints, and bounded execution for live agent behavior.

Humans

Oversight

Board visibility, review quality, training, and challenge when AI output looks polished.

Framework

The modern GenAI architecture stack

A detailed systems-engineering guide to LLMs, RAG, AI agents, and MCP. Built as a visual architecture reference for moving from demos to enterprise-ready AI systems.

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V Vanderburgh.it GENAI STACK AT A GLANCE

Four systems: reasoning, grounding, execution, and secure connectivity.

LLM

Brain

Reasoning, drafting, interpretation, and language generation.

RAG

Memory

Verified retrieval from enterprise sources before the model answers.

Agents

Hands

Planning, tool use, execution loops, and corrective action in workflow.

MCP

Nervous system

Standardized connectivity between AI clients, tools, and governed data sources.

Infographic

Which AI tool do you use for what?

A practical comparison of Claude, ChatGPT, Gemini, Qwen, Grok, and Mistral. Use the card view as the quick scan, then open the matrix for strengths, limits, and best-fit work.

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Editorial AI News Board preview for the AI tools comparison guide.