The key point for me was not the rewrite in Go or even the use of AI, it was that they started with this architecture:
> The reference implementation is JavaScript, whereas our pipeline is in Go. So for years we’ve been running a fleet of jsonata-js pods on Kubernetes - Node.js processes that our Go services call over RPC. That meant that for every event (and expression) we had to serialize, send over the network, evaluate, serialize the result, and finally send it back.
> This was costing us ~$300K/year in compute, and the number kept growing as more customers and detection rules were added.
For something so core to the business, I'm baffled that they let it get to the point where it was costing $300K per year.
The fact that this only took $400 of Claude tokens to completely rewrite makes it even more baffling. I can make $400 of Claude tokens disappear quickly in a large codebase. If they rewrote the entire thing with $400 of Claude tokens it couldn't have been that big. Within the range of something that engineers could have easily migrated by hand in a reasonable time. Those same engineers will have to review and understand all of the AI-generated code now and then improve it, which will take time too.
I don't know what to think. These blog articles are supposed to be a showcase of engineering expertise, but bragging about having AI vibecode a replacement for a critical part of your system that was questionably designed and costing as much as a fully-loaded FTE per year raises a lot of other questions.
Yeah, it's like those posts "we made it 5,000x faster by actually thinking about what the code is doing."
> If they rewrote the entire thing with $400 of Claude tokens it couldn't have been that big.
The original is ~10k lines of JS + a few hundred for a test harness. You can probably oneshot this with a $20/month Codex subscription and not even use up your daily allowance.
You aren’t accounting for managerial politics. A product manager won’t gamble on a large project to lower operating cost, when their bonus is based on customer acquisition metrics.
Think this is pure piggyback marketing on what cloudflare did with next.js. In my experience a company that raised $30MM a month ago is extremely unlikely to be investing energy in cost rationalization/optimization.
edit: saw the total raise not the incremental 30MM
I mostly agree, but it's more appropriate to weigh contributions against an FTE's output rather than their input. If I have a $10m/yr feature I'm fleshing out now and a few more lined up afterward, it's often not worth the time to properly handle any minor $300k/yr boondoggle. It's only worth comparing to an FTE's fully loaded cost when you're actually able to hire to fix it, and that's trickier since it takes time away from the core team producing those actually valuable features and tends to result in slower progress from large-team overhead even after onboarding. Plus, even if you could hire to fix it, wouldn't you want them to work on those more valuable features first?