Clear thinkingabout AI.
Original essays on using AI well — how to judge tools, read benchmarks, give models better context, and build real literacy. Plain English, no hype, no jargon.
How to tell whether an AI safety promise is real
AI companies increasingly promise monitoring, safeguards, and responsible deployment. Here is a practical framework for judging whether those promises create evidence, accountability, and meaningful limits.
· 7 min read · AI Understanding Editorial TeamAll posts
Evergreen writing meant to stay useful long after this week's model launch is forgotten.
When AI becomes public infrastructure, what should we ask?
AI is moving from chat windows into highways, government offices, military records, and workplaces. A practical framework for judging these systems by their evidence, limits, permissions, and effects on people.
· 8 min readWhat should schools teach when AI access rules keep changing?
School bans can limit immediate risks, but they cannot replace judgment. A practical framework for teaching students when to use AI, when to question it, and when to leave it out.
· 9 minutos de lecturaWhen should an AI system stop, ask, or hand off?
Reliable AI is not just about producing good answers. It is about recognizing uncertainty, checking evidence, and knowing when a response should not become an action.
· 7 min readBefore AI takes a task, test the whole chain
A model can answer questions well and still fail at real work. Here is a practical framework for evaluating AI systems across evidence, tools, state, timing, and failure recovery.
· 8 min readDoes local AI make your data safer?
Running an AI model on your own device can reduce exposure to outside services, but it does not automatically make the system private, reliable, or safe. Here is a practical framework for judging the tradeoffs.
· 9 minutos de lecturaWhen should you trust an AI agent with real work?
An AI agent is not dependable just because it succeeds once. Here is a practical framework for judging its reliability, permissions, security, and readiness for real-world tasks.
· 8 min read
How to Evaluate an AI Tool Before You Pay
Demos are built to impress, not to inform. A practical, vendor-neutral process for testing an AI tool against your real work before a subscription starts.
· 5 minutos de lectura
Prompting Is Overrated — Context Is What Matters
Magic phrases and secret prompt formulas miss the point. The quality of an AI answer is mostly decided by the information you give it, not the incantation you wrap it in.
· 5 minutos de lectura
What AI Literacy Means in 2026 (and a 30-Day Plan to Get There)
AI literacy is not coding and it is not prompt tricks — it is judgment. A four-part definition and a realistic 30-day plan built on free resources.
· 6 minutos de lectura
The Real Cost of "Free" AI Products
Free AI tools are genuinely useful — and genuinely not free. What you actually pay in data, dependence, and switching costs, and how to use free tiers wisely.
· 5 minutos de lectura
How to Read an AI Benchmark Without Being Fooled
Every model launch comes with a chart where the new model wins. What benchmark scores actually measure, the classic tricks to watch for, and the only benchmark that matters.
· 6 minutos de lecturaNew essays are published regularly — check back soon, or start with the guides below.
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