Amanda Phillips

Something I learned the hard way running outbound for my dev agency:

Everyone obsesses over the first message: the opener, the hook, the personalization. I did too.

Something I keep running into building in the hiring space: the moment interviews went remote and AI got good, the format quietly broke. Candidates can pull up the right answer, or paste a polished one, in real time. So a lot of interviews now measure who prepped with ChatGPT, not who can actually do the work.

The usual fixes don t really hold either. Fixed question banks get shared and gamed. Harder questions just raise the bar on who copies best. Going back to in-person doesn t scale.

Curious what people here think. Is the structured Q&A interview finished, or is there a version of it that survives AI? And for anyone hiring right now, how are you actually telling a real answer from a generated one?

With the recent launch of the AISA Score - The AI Fluency Assessment marking 9 months since our first launch, we now work with many enterprises and have over 3,300 individual assessments completed. One thing is very clear to me now.
AI fluency is really the new currency both to find and keep a job, but also to solo-build or optimise the personal life. We are passed the point of discussion AI IS GOOD / AI IS BAD. It just is a new technology.
Now it's up to individuals to use it in good taste, bad taste, with skill or bluntly. Bad AI judgement leads to AI slop, good judgement and skillful usage, with high fluency of the AI ecosystem leads to sci-fi like results.
This is especially becomming apparent in the enterprises we work with. There are whole teams where the score range is 14-92. Imagine that, in one meeting room there are two people who have each an AISA Score of 14 and 92 out of a 100, and they are trying to make decisions together.
The other clear theme that's emerging to me is that if 2026 was the year of AI training become "a thing", 2027 onwards will be a period marked by generic AI training not being enough and each team and function needing training tailored to their gap areas (this is what we are positioning to serve).
What are your thoughts?