Apache-3 Inc. · AI Literacy
What is AI? Plain English, no marketing.
Short, honest explainers for working professionals who need to understand AI well enough to make decisions about it. By the authors of Prompt to Product.
Articles
- What is AI? A plain-English answer for working professionals.
If you skip the marketing and the doom, AI is a small set of practical capabilities that you can use today. Here is the honest version.
7 min read
- Prompt engineering basics for non-developers.
You do not need a CS degree to write good prompts. You need a frame for what a prompt actually is. Here it is.
6 min read
- Working with sensitive data inside AI tools.
Most people put data into AI tools they would not put into a public email. Here is the honest version of what is safe and what is not.
5 min read
- No-code automation patterns for working professionals.
You can automate ninety percent of repetitive office work with prompts, scheduled jobs, and a couple of free tools. Here are the patterns that actually work.
6 min read
- AI in government: what works, what does not, and why most pilots fail.
The honest assessment of where AI is delivering in federal civilian agencies, and where the pilots stall before they ship.
7 min read
- AI hallucinations: what they are, why they happen, how to spot one.
The word "hallucination" sounds dramatic. The reality is more mundane and more useful to understand.
6 min read
- AI vs ML vs LLM vs GenAI: the terms, in plain English.
Marketing departments use these words interchangeably. They are not interchangeable. Here is what each one actually means.
5 min read
- AI for managers: what to do when half your team is using ChatGPT.
If you manage people, AI is now a management problem. Here is the practical guide for managers who are not engineers.
7 min read
- Claude vs ChatGPT vs Copilot vs Gemini: when to use which.
All four are useful. They are not interchangeable. Picking the right one for the task saves time and money.
6 min read
- How much does AI actually cost? A practical guide to pricing.
Most cost surprises come from one of three patterns. Once you see them, AI cost forecasting becomes straightforward.
6 min read
- AI in legal work: what is real, what is hype, what will get you sanctioned.
Lawyers have been sanctioned for AI hallucinations in real filings. Here is the honest map of where AI works in legal work and where it does not.
7 min read
- AI security threats: prompt injection, jailbreaks, and the new attack surface.
AI tools introduced new failure modes that did not exist before. Understanding them is now part of basic security literacy.
8 min read
- AI for sales and customer success teams: where it actually helps.
Sales teams have more AI tooling thrown at them than any function in 2026. Most of it does not move quota. Here is the honest map.
6 min read
- AI for HR: practical wins, legal landmines, and the bias problem.
Where AI helps HR work right now, where it creates real legal exposure, and the questions to ask before any AI tool touches employee data.
7 min read
- AI for finance teams: where it works, where SOX makes it hard.
Practical AI in finance is real. The compliance overhead is also real. Here is what works at a CFO-organization scale.
6 min read
- On-prem vs. cloud AI: which deployment model fits your work.
The hosting question shapes everything: cost, security posture, accuracy, latency. Here is the honest comparison.
7 min read
- AI procurement: the questions to ask before signing any AI contract.
Most AI tools are bought on demo enthusiasm. The contracts that ship to legal are often inadequate. Here is the procurement checklist that prevents the predictable problems.
7 min read
- AI for state and local government: where it works, where pilots stall.
State and local agencies face the same AI questions federal agencies do, with smaller budgets, less procurement infrastructure, and faster pressure to ship. Here is the honest path.
6 min read