The code is very dense. Clear, concise, elegant. But dense. An LLM doesn't generate code like that.
I think it's perfectly doable to use an LLM to write into the Django codebase, but you'll have to supervise and feedback it very carefully (which is the article's point).
Would a company paying 600k per month not also be able to employ a couple of devs to improve the situation? Sure, effort is required, but with the right people they could save a ton and have a very good ROI.
I think it's just more complicated than that. No hostage situation, just good old incentives.
As long-time (and happy) DRF user of more than 7 years I've recently switched to django-ninja [1]. It's like FastAPI, but for django. Granted, I've only used it for a couple of months now, and also not in production yet. But I think it's pretty nice and a breath of fresh air for django. The thing you get from using it is full typing and IDE support (autocomplete!). It's using pydantic instead of DRF's serializers. Can definitely recommend so far.
I'm pretty much looking for the same. AFAIK, autocomplete is provided by bing/azure, mapbox, tomtom, HERE and geocode.earth (I might also be missing a few). Also, mapfit (a pretty young participant, it seems) will have it "in a month", they say.
Re 1: Why wouldn't you recommend going with kubernetes? From someone that hasn't deployed anything with it (yet), it seems rather straight-forward if run on a managed cluster (gke). I might be wrong and am thus genuinely interested in what you did for deployments.
I'm relieved, thanks guys. I really don't see the complexity when deploying to a (managed) k8s cluster. Sure, we'll still have to configure a deployment pipeline, add some scripts to push and deploy the right images etc., but overall, k8s seems really well suited to the task.
flatfox.ch | Switzerland, on site | Full-time, all levels
flatfox is a proptech startup building a next generation SaaS for landlords. We are looking for devs with high ownership who like to move fast and have an impact with our customers. We're small, you're going to be one of the very early hires, so, lots of opportunity to make a dent.
Same here. Had a chat with the support team and they say they had to allocate a number of new IPs, since some of their existing IPs were blacklisted. Now they need to warm up the new ones first, which may take an undefined amount of time.
Support was very helpful and migrated our traffic to already warmed up IPs.
Same experience here - we were migrated without warning 3 days ago and the majority of outgoing messages were subsequently deferred for 12 hours or more. When we reported the issue we were basically told they would be delivered eventually. No offer to migrate our traffic or to compensate us in any way.
We filed a support ticket and also had our traffic moved to a new IP, but I had to write to their Twitter account for them to pay attention. I urge everybody with an Essentials plan to do this, because it seems that if you don't complain on any channel possible you'll stay on this situation until it passes which can be "a few days" as they say.
I'd assume its a process of slowly ramping up new IP addresses to send out emails. If you take an IP and instantly use it on a massive scale, I'm sure it triggers a lot of spam filters.
Well, finance takes also a large chunk of Switzerland's GDP and thus is scooping up many engineers as well. Maybe it's not as pronounced as in London, but it certainly isn't very easy to hire good engineers here because of all the banks and hedge funds.
I think google came to Zurich because of EPFL/ETH, the very high living standard and most of all the rather liberal labor law. It's very easy to fire someone in Switzerland, compared to the surrounding countries.
Finance is 12% of Swiss GDP last time I checked. This country has this image of banking powerhouse, but in reality small/medium companies and tourism contribute much more.
healthier economical setup I must say. also, if they decide to trash banks with some end-of-data-privacy law (and it will eventually come, as for US persons), it won't be such a disaster for their economy.
I think it's perfectly doable to use an LLM to write into the Django codebase, but you'll have to supervise and feedback it very carefully (which is the article's point).
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