We Don't Need Coders. We Need Engineers.
AI is making coding easier. It’s making engineering more important. When writing code becomes cheap, engineering judgment becomes invaluable.
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You build products for everyone else. What are you building for yourself?
You automate the work. The company keeps the agents. Then it decides it needs fewer people. Put some of that ability into a business that belongs to you.
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17 articlesDon’t write code. Let AI do the work.
CEOs want returns on their AI investments. But a company that struggled to get things done before AI may still struggle after it.
Your job is to figure it out.
Seven years of PhD and postdoctoral research in theoretical physics taught me to stay with a difficult problem and find a way through it.
AI is not helping low-performing employees.
AI can't fix poor business understanding, low motivation, resentment toward colleagues, or missing feedback. Those problems can leave the performance gap wider despite better tools.
Everyone has their own Claude Skills. Try automating across teams.
Individual developers and teams are building overlapping Claude Skills. The duplication and inconsistent standards make reliable, reusable workflows harder to achieve.
Five data engineering workflows I would give to an agent.
Backfills, pipeline failures, support tickets, anomalies, and data quality checks all involve repeated investigation. Here is where agents could help and what each workflow should produce.
GitHub projects alone won't get you an AI/ML job.
A good portfolio still matters, but aspiring AI/ML engineers face experienced competition. Networking, analyst roles, internships, and other entry points deserve a place in your job search.
The BigQuery console is dead. Agents run the queries now.
Agents can find tables, write SQL, and run queries for me. The work is shifting toward deciding what to ask and checking whether the answer makes sense.