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Data Careers & AI

Don’t Cut the Expertise That Makes AI Valuable Just to Please Shareholders Most read

Illustration of a person in a suit standing beside a database cylinder

How AI multiplies engineering productivity, and why cutting experience can erase the benefit Companies that understand AI will use it to multiply expertise, not eliminate it. The others will see only the dollar sign, replace experienced engineers with cheaper developers plus an LLM, celebrate the quarterly savings, and proudly call it transformation. Artificial intelligence is …

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AI Is Automating the Work That Creates Experts Widely read

Hand-drawn infographic comparing a junior engineer's learning cycle, where a mistake builds judgment, with an AI-answered task that leaves a gap in understanding

Artificial intelligence allows consulting and technology companies to complete many tasks with fewer employees. A senior consultant supported by AI can analyse requirements, generate code, prepare documentation, review test results, and create presentations much faster than before. Work that once required several junior employees can increasingly be completed by a small number of experienced people …

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The Market Does Not Pay for Tool Lists

A person facing a shelf of collected software tools, beside a signpost pointing from collect more tools toward solve real problems

Why capable data and platform engineers stay invisible, underpaid, and afraid to apply There is a quiet fear in the current technology job market. Many people who are entirely capable of doing the work do not apply for it. They read a job description, see ten tools listed, and fix their attention on the two …

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The Brain and the Muscle Popular

A blue brain on a circuit-board background beside an orange flexed arm, under the words The Brain and the Muscle

A practical guide to spec-driven development — built around one real website, so you can follow along and try it yourself. Whether a conversation persists after closing depends on the product and settings. Keep project decisions in versioned specifications so they remain reviewable independent of chat persistence. This is vibe coding, and there is nothing wrong …

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The Two Engineers

Three people with money: one downcast behind shrinking stacks, one with folded arms behind even stacks, and a cleaner throwing banknotes into the air

This is a story. The two men in it do not exist. Everything that happens to them does. Year One They had studied together, and so once a year or so they met at the same café near the old university, ordered the same coffee, and compared the shape of their careers. In the first …

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Why does your test suite lie to you when the system contains an LLM

Comparison of a calculator-like deterministic system, where the same input always gives the same output, with an LLM that can give different valid outputs

A passing test means the tested assertion held for those cases, not that the whole program is correct. This limitation applies to deterministic software as well as systems containing LLMs. Traditional software tests establish behavior for tested cases, not general correctness. Deterministic programs can silently calculate wrong values. Property-based, randomized and concurrency tests can check …

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What You Actually Need to Know About LLMs Before the Next Interview

Diagram of the five transformer phases in an LLM: input tokenized, tokens embedded, N transformer blocks, output projected to vocabulary, next token predicted

“All models are wrong, but some are useful.”George Box This practical primer is part of the series on moving from data engineering into AI systems. It focuses on LLM concepts relevant to interviews and implementation; the original relative newsletter schedule is omitted. Read the related career and job-posting articles for the broader series. Publication timing …

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