Twice weekly, I share proven strategies to help data scientists get noticed, promoted, and valued. No theory — just practical steps to transform your technical expertise into business impact and the freedom to call your own shots.
The $100M Question
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Earlier this month, Anthropic launched the Claude Frontier Academy, a program designed to train engineers to change how businesses run using agentic AI. The announcement reads as a clear signal that AI models alone aren't enough to create business value and that people are still essential for this technology to succeed. I couldn't agree more. The program's target profile makes this point even clearer. Anthropic wants engineers with strong technical skills, but also "experience helping others adopt AI" and a "habit of tackling" the business problems that matter most. Technical skills alone aren't enough. It's the judgement-based skills, such as understanding the business problem and shepherding a solution through the last mile from deployment to adoption, that make all the difference and drive the greatest returns from AI. But the program also points to a gap. Participation is by nomination only, and to be nominated, you need to have already demonstrated these judgement-based skills. In other words, to get in, you need to have already been identified as being strategic. That's not a criticism, since it isn't Anthropic's job to solve this. The program takes engineers who already think strategically and develops them even further. But what about the technical professionals who haven't yet had the chance to learn? I work with data professionals making the transition from technical to strategic, and I've seen that far too few organisations give their technical staff opportunities to bridge that gap. Left to their own devices, many never learn how to think strategically. That's the skill gap that lies beneath the one Anthropic is addressing. To make AI pay off, organisations shouldn't only invest in the strategic people they've already found. They should systematically build more of them. Talk again soon, Dr Genevieve Hayes p.s. If you're looking to make the move from technical to strategic and don't want to do it alone, I can help. I work with data professionals one-on-one to do exactly that. Reply to this email if you want to know more. |
Data Science Impact Algorithm
Twice weekly, I share proven strategies to help data scientists get noticed, promoted, and valued. No theory — just practical steps to transform your technical expertise into business impact and the freedom to call your own shots.
The first course I had to take as part of my computer science Master’s was a compulsory course on algorithms. Regardless of whether you were a data scientist, like myself, specialising in machine learning, or a software engineer specialising in computer systems, everyone had to take it - and for good reason. Because algorithms are the building blocks of everything technology professionals do, much like how protein bases are the building blocks for all things biological. The AI era hasn’t...
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