> This Rust rewrite would've taken a team of engineers with full-context on the codebase a year of work. With 1 engineer using Fable & closely monitoring Claude Code, we went from start to 100% of the test suite passing on all platforms in 11 days.

This is impressive from a technological standpoint, but it does gloss over the fact that it would have cost $165k in tokens were Bun not part of Anthropic.

The comparison here isn’t completely fair - it would take a small team a year to port it if they spent $0 extra on it.

I’d be interested to see a comparison between spending $165k in 11 days on Claude vs splitting that between 50 people over 11 days for a line-by-line rewrite of the Zig code. I suspect Claude might be faster and therefore cheaper, but maybe not by a lot.

They napkin math is fairly easy to do. One human works around 250 days per year, and if we assume Bay Area salaries we could assume ~300k/y conservatively for a fully loaded cost.

$1200 per day.

Your estimation is 50*11 days so $660,000. That’s 4x what Claude cost.

That’s assuming that you actually get those 50 people to work without blockers, stepping on each other, or other coordination issues. The coordination complexity alone is astounding.

I don’t like it necessarily, but Claude wins here, easily. It’s not close.

I think it'd take you at least eleven days to meaningfully coordinate 50 people!

I feel like a core difference is that the AI implementor can get cheaper/faster (and indeed _uniformly_ better), whereas it would be very difficult for the same humans to do so.

Even if this is not the right answer today, it can at the very least serve as a herald of a possible future, no?

Your example of using 50 people for this reminded me of the classic “Nine women can’t make a baby in one month.”

HINT: those 50 people must be coordinated...

> I suspect Claude might be faster and therefore cheaper, but maybe not by a lot.

While Jarred used Mythos-class model, some open weights, if they were as capable (certainly, GLM 5.2 looks the part), would have been way, way cheaper than professionals.

Approx costs:

  DeepSeek v4 Pro & Mimo v2.5 Pro   $3,426  ($2,567 / $600 / $259)
  Tencent HY3                       $3,892  ($1,180 / $552 / $2,160)
  GLM 5.2                          $30,016  ($8,260 / $3,036 / $18,720)
  Qwen 3.7 Max                     $37,925  ($14,750 / $5,175 / $18,000)
  Claude Opus 4.8 & GPT 5.5 xhigh  $82,750  ($29,500 / $17,250 / $36,000)

  5.9 billion uncached input tokens, 690 million output tokens, 72 billion cached input token reads.

$165k won't get you far on salaried engineers. There's every chance that 1 engineer, assuming Anthropic employs them, is on $500k or more. Assuming average of $336k in that pool of 50 engineers, then for 11 days for 50 engineers you've spent $710k[0].

Salary info: https://www.levels.fyi/companies/anthropic/salaries/software...

[0]The maths I used (posting because I'm tired and prone to mistakes):

    $336,000 / 260 (working days of the year) = ~$1,292.
    $1,292 * 11 * 50 = ~$710,769