[gk1]

> AI tools make great team members even better

This is the predominant (public) talking point. And it’s true.

But along with that: when you have effective people becoming even more effective with AI, it becomes glaringly obvious who the INeffective people are. At which point it becomes hard to justify keeping those people around.

(That often includes people who are otherwise effective but aren’t utilizing agents and are therefore losing their edge.)

[jurgenburgen]

Before AI, it was impossible to measure productivity. Some tried with misguided metrics like lines of code added but that just incentivized writing obtuse code.

What has changed?

[MITSardine]

Stuff just gets done, I guess? Projects move faster, people onboard faster with less intervention, etc. The speedup seems noticeable enough that it doesn’t need precise measuring.

[jurgenburgen]

If the speed up is noticeable enough then coming up with a metric should be easy?

I haven’t noticed a speed up in my own org though the feeling of engineers rushing to implementation has become more pronounced. Team members no longer understand what others are doing and siloing has become intense even within my team.

[matharmin]

Now you can ask "Is it easier to ask an AI agent to do X than asking my employee?"

Good metrics is difficult, but sometimes a simple comparison like that is enough.

[htrp]

vibes maybe?

If effective AI enhanced SWEs can ship features in a week, the guys who ship 1 feature a quarter stand out more?

[bartread]

Quality matters as well as speed though: reworking comes at a cost, so you really need to be tracking more than one metric. A lot of problems are caused by optimising for one metric above all else.

[hackable_sand]

If it takes 1 quarter to develop a feature and a developer ships a feature in 1 quarter then that makes sense.

If it takes 2 weeks to ship a feature and a developer ships in 1 then yeah, I'm highly suspicious of that.

[dboreham]

Impossible to measure in absolute terms but I think it's clear productivity increases relatively when LLMs are used. At least that's my strong experience.

[the_af]

I know you're arguing a more general point, but it's worth pointing out in their layoff announcement, CloudFlare is claiming:

- This is NOT performance related.

- This is NOT a cost cutting exercise.

They say both things explicitly. What they don't say very clearly is what the layoffs ARE about.

[toast0]

> This is NOT performance related.

It's important to say a large layoff isn't performance related, because it helps those who got laid off find new work. Even if it was all performance related, you want someone else to hire your former employees.

And, in a large layoff, it's likely to be at least partially true. Large layoffs work better when they're done quickly, when there's signs of layoffs but no information, many people will head for the exits themselves... which helps your headcount numbers, but ideally you want to keep people who are good at figuring stuff out and taking appropriate action and instead they've left. So... lay off people who are 'known performance issues', but also lay off some whole teams that have a mix of performance, and then do some random assignment and catch a mix of performance, because getting direct managers involved to pick who goes means having too many people know about the lay offs.

> This is NOT a cost cutting exercise.

Yeah, this one isn't credible. If it was about something other than costs, like pivoting to a new market, you would offer first choice of jobs for the new market. Even if it's look at our productivity, 20% of our employees have nothing to do, it takes a lot of spin to say not paying them to twiddle their thumbs is something other than cost cutting.

[ThrowawayR2]

Didn't a few large tech companies fail even that low bar of decency? I seem to recall news of layoffs in the not too distant past where the employer openly let it be known those chosen were chosen for performance reasons, e.g. https://www.cnbc.com/2025/01/14/meta-targeting-lowest-perfor...

[acdha]

That to me is a pretty clear reason to question the accuracy of those two claims. Insiders are saying that even people who were performing well in very profitable groups are being cut, which is hard to square with the stated motivations.

[the_af]

Agreed. One of the two things must be false. But that's what they are saying (not saying I buy it).

[apple4ever]

They are lying about it not being a cost cutting exercise

[aaa_aaa]

Losing what edge?

[zarzavat]

It's weird to fire people instead of giving them training.

[alphabeta3r56]

Training can be socialized by asking people to take govt loans on further education and then letting the people default on them. Why should company spend their profits on it? /s