Tutorials, real-world applications, and plain-English explanations — for people who use AI at work but don't want to read a research paper to understand it.
Three ways in, depending on what you're trying to do. Each one gathers the relevant posts and puts them in a sensible order.
How do I use AI safely and usefully at work?
How do I roll AI out to my team?
How do I use AI for X?
Models score around 43% on simple character-counting tasks. Everyone blames tokenization. A larger benchmark found it barely predicts counting errors at all, and what does predict them is worse news for real work.
In a randomized trial, students using an AI tutor scored 127% better on practice problems and no better on the exam. The ones using plain ChatGPT scored 17% worse. Here is what to do differently.
Microsoft measured 29 factors against reported AI impact across 19,854 people. Culture, manager support and talent practices explained 67% of it. Individual mindset explained 32%.
Every assistant now has a thinking mode. Research found three levels of difficulty, and on the easiest one the ordinary model beats the reasoning one. A plain-English guide to which tasks want it.
77% of workers scrutinize a colleague's work more closely when they know AI was involved. The load-bearing words are 'when they know.' A review method that doesn't depend on being told.
Berkeley researchers spent eight months inside a company using AI. In the moment people felt momentum. Stepping back, they felt busier. Both were true.
Hallucination isn't a glitch or a lie. It is what you get from scoring a model like an exam that gives no credit for saying "I don't know".
The most-quoted stat about failed AI projects lists data quality, cost and unclear value. It does not list people. Research on why that omission matters.
I gave my team AI training, tools and encouragement. Someone still built the useful thing on their own time, because I never said it counted as work.
Anthropic sampled a million conversations and found experienced users delegate less, not more. What they do instead, and how it fits the long-chat research.