tomwphillips

In my last company, we _did_ pay for Google Cloud support and when BigQuery jobs started to fail randomly, causing huge trouble producing critical reports, the response was essentially "we are investigating", "we have identified the issue", and "please wait for it to be fixed". Hardly what I would call support. They couldn't care less.

Thank you, and please keep it online. Apparently I am incapable of remembering HTTP status codes and I always go straight to http.cat!

The post is light on details. I'd guess the author ended up hammering the API and they decided it was abuse.

I expect more reports like this. LLM providers are already selling tokens at a loss. If everyone starts to use tmux or orchestrate multiple agents then their loss on each plan is going to get much larger.

Author here, thanks for reading. Yes, naming is tricky. By mono-environment, I mean that there is one _long-lived_ environment to which we deploy software.

>Every project has boilerplate. It gets written once.

Agree with you - I think when my colleagues have talked about boilerplate they really mean two kinds of boilerplate: code written once for project setup, like you describe, and then repetitive code. And in the context of LLMs, they talking about repetitive code.

I like this analysis.

I'm constantly surprised by developers who like LLMs because "it's great for boiler plate". Why on earth were you wasting your time writing boiler plate before? These people are supposed to be programmers. Write code to generate the boiler plate or get abstract it away.

I suppose the path of least resistance is to ignore the complexity, let the LLM deal with it, instead of stepping back and questioning why the complexity is even there.

Interesting. I don't recall this happening during my studies. You didn't have the time in my exams to cheat, leaving for the toilet was strongly discouraged and if you did leave, you would have an invigilator standing behind you at the urinal or outside the cubicle.

The article is about accountancy. Accountancy is not academia.

>In the end of the day academia in general should stop relying on exams based on memorization of random facts and start using real world examples of what kind of work student would be working with as an employee.

I have an undergraduate degree and PhD in chemistry and I don't really think "blind memorisation" had much to do with my success. It will only get you so far.

I think there is also substantial within academia about the purpose of academia. I think a lot of academics might disagree that it is about preparing people to be employees.

Our team uses IntelliJ so we use Code with Me with Slack for AV. Specifically on Slack we have channels called pairing-room-1, pairing-room-2, etc. Allows colleagues to drop in and out.

I would try Tuple but to be honest we are fine on Code with Me.

Indeed. Github is a nightmare when I'm working on an unreliable 4G connection too (e.g. on a train in the UK). Half the page will load.

Night and day compared to something like Linear.

>Pair programming is less fruitful.

I'm surprised at this statement. My team pair a lot - at least half of the time - and the majority is remote.

We find it much more comfortable to pair remotely on our own setups than crowded around a single desk and keyboard.

I wonder why our experiences are so different.

Good luck.

The major plus of having low or zero baseline caffeine consumption is that when you really need a jolt, a single cup will have the desired effect!

I had a similar experience as an undergraduate.

In my penultimate year I was struggling under a huge lecture and lab workload, working at the weekends, and partying too.

I developed stomach pain and went to the campus doctor, who sent me off to A&E (ER) with suspected appendicitis. My appendix was fine, but the doctors thought I might have a stomach ulcer. I discharged myself early to get back to the library, so never actually got a diagnosis!

I was drinking 3-4 cups of coffee and ~500mL knock-off Red Bull a day, eating a poor diet, and then drinking alcohol in the evenings. I went cold turkey and spent an entire weekend in bed with the worst headache imaginable.

I think I managed a few months before cracking and getting back on coffee. I quit cold turkey again a couple of times but in recent years I titrated off of it by gradually changing ratio of caffeinated to decaffeinated beans in my coffee at home. I drink 1 - 2 small cups a day now.

Might give quitting a go again.

Author here. Indeed - it would be just as fantastical to deny there has been no value from deep learning, transformers, etc.

Yesterday I heard Cory Doctorow talk about a bunch of pro bono lawyers using LLMs to mine paperwork and help exonerate innocent people. Also a big win.

There's good stuff - engineering - that can be done with the underlying tech without the hyperscaling.

Hey Simon, author here (and reader of your blog!).

I used to share your view, but what changed my mind was reading Hao's book. I don't have it to hand, but if my memory serves, she writes about a community in Chile opposing Google building a data centre in their city. The city already suffers from drought, and the data centre, acccording to Google's own assessment, would abstract ~169 litres of water a second from local supplies - about the same as the entire city's consumption.

If I also remember correctly, Hao also reported on another town where salt water was being added to municipal drinking water because the drought, exacerbated by local data centres, was so severe.

It is indeed hard to imagine these quantities of water but for me, anything on the order of a town or city's consumption is a lot. Coupled with droughts, it's a problem, in my view.

I really recommend the book.

Not that surprising. How many millions has been piled into dbt Labs?

dbt Cloud is an uncompelling product. Fivetran is convenient but absurdly expensive. Now dbt core development is just another marketing cost for Fivetran.

I'd really love to see everyone move on from the "modern data stack". dbt is a sticking plaster to a problem caused by orgs aggressively adopting SaaS products and choosing distributed software architectures without any thought about how to deal with the problem that your data models don't fit together and data is stored in 30 different places.

This kind of science/tech investment is and has been catnip for UK government, regardless of political party, for years. They're out of ideas to stimulate growth, and AI is their hail Mary. No one involved seems to be able to explain why it will work.

Did you watch the video?

Considering how many developers still don't write tests, pair program, or do CI and CD (shipping multiple times a day) – all things Dave argues for – I don't think it is fair to dismiss him as the establishment or incumbent.

Indeed, to expand on my remark: I wrote Python in academia for ~6 years and then professionally for nearly a decade in data science, data engineering and backend web apps. Virtualenv was fine. Pipenv had a nicer CLI and easier to use dependency pinning. But fundamentally all this stuff worked fine.

>Modern

I'll pass. I'd rather have the battle-tested old thing, thanks.

Indeed. I have been using it for 5-6 months in a new job and I didn't notice it being faster than the typical web app.

If anything it is slow because it is a pain to navigate. I have browser bookmarks for my most frequented pages.

I think it might actually be because they're selling services at a loss.

I'm surprised IDE integration is written off. I've been pleased with Junie's agent mode in IntelliJ. Works well.

>You give Mozilla all rights necessary to operate Firefox, including processing data as we describe in the Firefox Privacy Notice, as well as acting on your behalf to help you navigate the internet. When you upload or input information through Firefox, you hereby grant us a nonexclusive, royalty-free, worldwide license to use that information to help you navigate, experience, and interact with online content as you indicate with your use of Firefox.

Emphasis added.

The article reports that it will be disabled for existing users at a later date.

> The way I see it, most companies already use modern ATS to stack rank every application based on their resume using AI and then just go down the list.

I have never worked anywhere that has done this. Humans have always reviewed every application.

I wouldn’t. It demonstrates that they haven’t thought enough to realise it worsens a systemic problem.

Hmm, I’m not sure about this. I’m in my 30s. Use lots of Slack huddles at work, with colleagues of all ages, and I caught up with a couple of friends this week on regular phone calls.

> Type hints are were the whole Python ecosystem is going

I see what you’re saying, but a lot of Python users, especially those who have been using it pre-3, would say that this is unfortunate.

> I also think Django should just adopt these components and we would not have the discussion in the first place.

Oof, such a monoculture sounds terrible to me!

I agree.

Unfortunately every team I’ve worked in hasn’t seen the light and prefers FastAPI/SQLAlchemy/Pydantic (before FastAPI it was Flask).

My theory is that the initial learning curves are different: with FastAPI it’s quick and easy. You barely have to read anything. Django has a steeper learning curve. There’s a lot of reading involved. Type hints aren’t a big thing in Django, but they are in FastAPI, and the average full stack dev seems to like them.

Later on it’s totally different of course. With FastAPI you’re building it all from scratch, and it’ll be much worse than the Django solution.