Design Privacy-First AI Tools for Schools: Practical Guide
A practical framework for school leaders and ed‑tech builders to assess risk, choose privacy-preserving AI architectures, design consent and age-appropriate UX, and manage incidents.
Prompt Library Framework: Organize, Test, and Version Prompts
Step-by-step framework for building a prompt library: taxonomy, naming, metadata, automated tests, versioning, rollback, review flows, and tool checklist.
Multimodal Prompt Engineering: Templates & Debugging
Practical guide to multimodal prompt engineering with 10 ready templates, step-by-step workflows, before/after fixes and a checklist to debug image and video prompts.
AI Notebook Workflows for Research and Class Projects
A practical, product-agnostic guide to using AI notebooks for literature reviews, experiment logs, notes, reproducible prompts, and instructor-friendly policies.
Choose the Right AI Model for Small-Business Tasks: Decision Flow
A practical decision flow to choose AI models for common small‑business tasks—summaries, support, code, and images—plus prompts, tradeoffs, and a vendor checklist.
Audit an AI Tool’s Access to Credentials — Practical Checklist
Step-by-step checklist to audit what AI tools can access, run quick live tests, fix configurations, vet vendors, and set monitoring for secrets protection.
Prevent Code Leaks: Secure Practices for AI Coding Assistants
Practical guide to prevent code leaks with AI coding assistants. Concrete IDE, repository, token and monitoring safeguards plus detection and remediation steps.
Non-engineer’s checklist: Integrate an AI copilot into your SaaS
A concise, non-technical checklist to add an AI copilot to your SaaS—covers architecture choices, privacy-safe data flows, low-code options, UX patterns, testing, and rollback.
Vet an AI Tool’s Training Data & Privacy: A Practical Checklist
A practical, step-by-step AI training data checklist for small businesses — questions to ask vendors, contract language, simple tests for data leakage, and a scorecard.
How to Build a Secure Sandbox for LLM Automations — Practical Guide
Step-by-step guide to set up an isolated LLM automation sandbox: threat model, local vs cloud infrastructure, data rules, safe test cases, metrics and rollback plan.