[swatcoder]

> Software developers in the US are seriously expensive, using them for data labeling would be a waste of resources.

The frontier work is on labeling and training expert content, by experts. It's unglamorous work and almost certainly doesn't warrant FAANG pay, but neither did most of the work that most FAANG engineers were already doing. But it does require competent talent from the expert domain.

Like their peer companies, Meta is still sitting on a huge pool of vetted-as-competant workers from the hiring boom and expert AI training is the most ripe business opportunity in a fragile economy where pretty much every comparable opportunity has evaporated.

[bredren]

Yes, this is not labeling what is an apple and what is a pear. "Annotation" does not do this work justice.

For a coding agent, for example, there is *very detailed* analysis of the turns and ranking of different portions of the conversation.

Adherence or deviation from specific rules matters. Writing quality matters. Expertise in the topic under discussion matters. Having intuition for the tone and beat of a good conversation matters.

Scoring a 15-20 turn conversation can easily take two and a half hours.

Clicking submit does not mean the author is done. Many annotations will be turned back to them by a reviewer to touch up in some way.

This work can be far more mentally taxing than programming, is measured much more by completions more of a timed exercise than SWE.

FWIW, Meta employees would probably make great coding agent conversation annotators. But it is absolutely not SWE and they won't enjoy it (for long).

[danny_codes]

It's a bold move cotton.

I doubt it'll pay off. Let's face it, the average FB engineer is no better than the average Polish engineer, and the Polish guy is 20x cheaper. If you wanted cost-effective labeling you'd send it to Poland. Or better, Chile.