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AI for Managers

Managers and AI: The Most Frequent Users – But Not for Managing

14 min read

Of all the professions that most frequently open Claude, managers came in first. In Anthropic’s survey, they made up 23% of respondents – while accounting for roughly 7% of U.S. employment. Managers are overrepresented among AI users by a factor of three. Now the second number: management tasks make up just about 4% of all sessions. The people who manage are using AI for everything except managing.

Behind these two numbers lies the most precise description of how managers actually work with AI. And why the fear of “it will take my job” works differently in this profession than you might expect.

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Managers and AI: The Most Frequent Users – But Not for Managing
5 Layers of an AI Agent: What Every Manager Needs to Know
19 min

5 Layers of an AI Agent: What Every Manager Needs to Know

“Most people still think an AI agent is just ChatGPT with a good prompt.” That is the opening line of Sunil Ramlochan’s article “The AI Agent Stack Is Not a Prompt. It’s a Production System”, and the author calls this belief “a comforting myth.” The useful truth, he argues, is different: a real agent is closer to a small operating system for getting work done. It has a brain, hands, memory, rules, logs, recovery plans, and someone accountable when the agent does the wrong thing.

The article’s thesis fits in a single line: an agent is an entire stack. Reliability comes from the architecture around it, while the model itself – or a clever prompt – is just one ingredient. The picture is an engineering one, so let us approach it from the other side: what in this stack actually concerns the manager who does not write code but decides whether to put an agent to work.

Why AI Pilots Die Between the Demo and the Factory Floor
11 min

Why AI Pilots Die Between the Demo and the Factory Floor

The pilot was shown at the board meeting, everyone applauded, budget was approved for ‘scaling.’ Six months later, the computer vision system that caught 98% of defects during the demo is catching maybe half, quality inspectors have stopped trusting it, and the project has quietly migrated into the ‘deferred initiatives’ column. This is not a rare mishap or the fault of a particular integrator. According to RAND, this is how more than 80% of corporate AI projects end – and almost always for reasons that were visible before the project even started.

How to Implement AI in Manufacturing: A Step-by-Step Guide for Plant Leaders
26 min

How to Implement AI in Manufacturing: A Step-by-Step Guide for Plant Leaders

A shift supervisor at a mid-size machining plant spends 40 minutes every morning filling out the shift report. Manually copying equipment readings into a Word template, describing incidents in free text, cross-checking the safety log. This routine has existed since the 1970s and hasn’t changed by a single minute. AI can cut it to ten. The hard part isn’t the technology. The hard part is knowing where to start.

280x Cheaper in Two Years: The AI Economy Has Flipped
9 min

280x Cheaper in Two Years: The AI Economy Has Flipped

In 2023, a single query to GPT-4 cost enough that you had to count carefully. In 2025, the equivalent query became 280 times cheaper. Not 280 percent – 280 times. In two years, the cost of using AI went from a barrier to a rounding error.

Stanford AI Index – the annual report that compiles data on the AI industry from hundreds of sources – flagged this collapse in its 2025 edition. The 2026 report added context: AI investment exploded to $285.9bn, consumers are extracting $172bn of value a year, and data centres are eating electricity at the scale of New York State. The economy flipped – just not the way most people expected.

4 Prompt Engineering Techniques Tested on 7 Models: Workshop Guide
30 min

4 Prompt Engineering Techniques Tested on 7 Models: Workshop Guide

“Analyze this project and give recommendations” – one prompt, seven models, and GPT-5.4 produced 2,231 words of vague advice while Claude Sonnet delivered 11 complimentary phrases like “excellent budget structure.” Rewriting the prompt using a five-element structure brought all seven models down to 346–443 words, and the praise disappeared. Token savings: 41% to 79% depending on the model.

This isn’t theory. This is data from a “Prompt Engineering in Practice” workshop I ran at the IIBA conference. One project brief, four techniques, seven models, 28 runs – and $0.054 total. Cheaper than a vending machine coffee.

99% Quality at 1.4% of the Price: What's Wrong with the AI Model Market
8 min

99% Quality at 1.4% of the Price: What's Wrong with the AI Model Market

Most managers pick an AI model the same way: grab the most expensive one available. The logic makes sense – pricier means better. That’s how enterprise software worked for the last twenty years.

The AI model market in 2026 works differently. The cost per query ranges from $0.0001 to $0.17 – three orders of magnitude. And the actual quality difference between the top ten models? 0.24 points on a five-point scale. Meanwhile, Wharton / GBK Collective reports that a third of corporate AI projects never get past the pilot stage. And Epoch AI shows that only 5.6% of users apply AI in any genuinely deep way.

Maybe the question isn’t which model is best, but whether paying a premium delivers proportionally better results for typical management tasks.

We tested it. The answer was harsher than we expected.

How to Get the Most Out of YandexGPT: What Works and What Doesn't
13 min

How to Get the Most Out of YandexGPT: What Works and What Doesn't

Millions of people in Russia use Alice every day – not because they choose to, but because it’s free, built into Yandex Browser, and works without a VPN. YandexGPT, the model under Alice’s hood, is the best Russian model in our benchmark, but it’s still a long way behind GPT-5.4.

Can you get answers from it that come close to GPT, if you learn how to ask the right way? We tested exactly that in an experiment: ten prompting techniques, six management tasks, two independent LLM judges. The short answer: yes, you can – but not every technique works, and some make things worse.

Below are the concrete templates you can copy into the chat right now, and the anti-patterns to steer clear of.