Having played with LLMs for a few years now I’ve had various stages of appreciation for its efficiency.
- Tell me some jokes..
- You coded a debugging nightmare.
- Hey this is kinda neat.
- Think for me. I’m too lazy to look it up.
- Spawn five of yourself and wire it up.
It happened so fast. For me, tool use has been the most eye opening. To see Claude computer use, review functionality, that it just implemented, by itself, by literally clicking around the iOS app it just built, is astounding.
I dove into an article on Sherwood News, Test time. It made me think about hiring the best people for tomorrow. Imagine you are looking at candidates. How can one justify hiring someone who has no experience with the potential of LLMs?
Instead of simply talking through strategy, some CMOs, investors, and operators are now being asked to use AI tools live — or during a tight take-home window — to create something in front of interviewers. A number of other firms do the same, while Nicole DeTommaso, a principal at Harlem Capital, says that anecdotally, she’s seen practically every potential candidate looking to join a venture capital firm being asked to show their prowess with AI coding tools.
DeTommaso wrote that one candidate was asked to build an AI agent that could produce automated research about industries within a working week that could reliably brief partners on a sector before they invested. Another needed to use the likes of Claude Code and Codex to vibe code a dashboard to show information about portfolio companies.
“You are not told which tools to use or how to go about it. You are just expected to figure it out,” she wrote. “And increasingly, what you can actually show in an interview matters more than what’s on your resume.”
At an individual contributor level it seems risky to hire someone who would be doing things “the old way”. It’s like signing a flat footed defence man in the world of Cale Makars. Speed is the game now. And at a leader level, Arguably it applies too where the best managers should excel at delegating to LLMs. It’s easier than ever to test and prototype. At a fraction of the cost before AI.