ritzaco

3 weeks sounds great. I got 3 days for the same. Also spent most of this month scrambling to set up alternatives to make payroll.

See [0]. They ore still holding $40k hostage and returned or blocked an entire months revenue. Definitely enough to kill many agencies and would have killed us in our earlier stages.

I have now tried Revolut, Airwallex, Payoneer, Bunq, OFX, and a few other alternatives. I am planning on doing a massive writeup comparing then all sometime soon.

[0] https://news.ycombinator.com/item?id=37925678

haha yeah exactly I feel like they all follow the same pattern of really focusing on The Customer in the beginning and getting super popular through word-of-mouth praise.

Then they turn on the money taps and just scale up and "move upmarket" to a point where they can't provide good customer service any more to smaller businesses until the next small startup comes along and focuses on smaller markets.

interestingly my brick-and-mortar bank (ING Netherlands) also stopped accepting walk in appointments during covid and conveniently kept that on now. So you have to deal with this shit anyway just to talk to someone, but yes at least there are still people

And to add

- They do not offer live chat at the moment because they are too busy.

- The phone waiting times are up to 30 minutes. I've called them many times and they are completely unable to do anything as they are the 'support' team and it all depends on the 'verification' team.

- They respond to emails with canned responses, usually 2-3 days

- They respond on Twitter in public and by DM. In public, they make it sound like they really care and ask to DM. If you DM, you get an AI bot that might eventually put you through to an agent if you find the correct way through the decision tree. Then the agent will tell you that they are working as fast as they can and you should wait another 10 working days and see what happens.

I don't think things are back to "normal" (ie stupid high valuations and people throwing money at startups. In reality, I would argue that "plan for the worst" and try to be "default alive" *is* normal, and that it's the last 10 years that have been abnormal, but I digress..)

Interest rates are high, and there is a lot less money sloshing about looking for a home. AI startups are a thing, and people are still trying to make huge returns there, but I doubt this will last long.

The "real" money is in the series B,C,D companies that raised at unicorn level and above. They cut back a lot but I doubt many are 'default live', and we'll likely still see the impact over the next 1-3 years as they burn through their previous ($50M+) funding rounds. They still have cash in the bank and they are still burning it, but it's going to run out and they are not going to be able to raise the same amount again, and definitely not at the 'valuations' that they got.

Python, Flask, SQLAlchemy, and Postgres all have great documentation individually, but if I am building an application at the intersection often a guide on exactly how to join them all up is much faster than using each individually and trying to figure out the interactions in four places.

AWS white papers and engineering blogs tend to give me everything I need in one place, and I don't think there are any for apps built with NOTIFY.

I often see the "engineers copy FAANG infrastructure because they want to be cool, even though their needs are completely different" take as a kind of attack on engineers.

But I think a lot of it is also about knowledge and documentation. If I want to copy FAANG or another startup, and set up an infinitely scalable queue-based architecture, I can find dozens of high quality guides, tutorials, white papers etc, showing me exactly how to do it. Yes maintenance is higher, but I can get set up with redis, SQS, any of the 'scalable' solutions within a few hours of copy-pasting commands and code and configuration from a reputable source.

If I want to use NOTIFY in postgres? I googled "SQLALchemy notify listen postgres" and I find a few unanswered stackoverflow questions and a github gist that has some code but no context.

I would honestly love to use this approach for a side project, but I don't have 2-3 days to figure it out on my own. The direct choice for me might seem to be

* simple, but not scalable (ie just use postgres)

* complex, but scalable (ie redis, sqs, whatever)

and then it's a tradeoff, and the argument goes that I am blinded by cool tech and FAANG and I'm choosing complex but scalable, even though I don't need scalable.

But taking into account guides and other resources, the choice for me is actually

* complex and not scalable (this, because I don't know how to implement it and I can't predict what pitfalls I might face if I try)

* simple and scalable (what everyone actually does)

and that makes the engineer's choice to follow faang look a lot more reasonable.

I remember that one - interestingly the amazon link it goes to shows only 3 books now, all that look real, not the 40 that I remember seeing before.

So I guess Amazon is doing something even though I regularly hear complaints from authors that they allow blatant piracy all the time

I've been using Wise for years and am generally happy with them, but always keeping an eye out for alternatives. Why I didn't find this convincing

- Have to download app - wise lets me use a website too, and generally I want to do business banking from my laptop, not my phone

- No actual price comparisons and 99% seems unlikely. Wise also gives me the 'google exchange rate'. If you are actually cheaper, then I would show comparisons for €100, €1000, €10000, not just 'a million euro'.

- Make it clearer that you're available in the EU - I nearly closed the site thinking it was only for UK as it defaulted to GBP.

- Have a 'wall of text' version in the header - the landing page is light on details, and I don't assume I'll find more information on "News", "Blog" or "Help" - maybe a "Features" or "Offerings" header page where you go into a lot more detail (countries you're available in, currencies you offer, documents needed to sign up, full table of all fees (not the marketing version), timelines for opening an account, timelines for making transfers, etc etc)

Countries in the EEA but not EU (e.g. Switzerland) tend to have bilateral agreements with the EU which cover most EU laws, so I think legally it's often easier to group EEA together

E.g. EU enforces free data roaming for cellphone providers, but many providers allow free roaming to Switzerland and the Nordic countries too - not sure if it's just practically easier than trying to geofence those areas into a different tariff or if it's legally too complicated, but I'm fairly certain they don't do it out of the goodness of their hearts.

the `sqlite3` module provides an interface to `sqlite` (https://www.sqlite.org/index.html), so that comparison doesn't really make sense.

OP rewrote the actual database in Python, so (if it's a 1:1 equivalence), you would still use the python `sqlite3` module to connect to OP's project.

As mentioned, it's an educational project, not really meant to be used as a replacement for sqlite in projects etc though.

I get the same on firefox with ublock origin, but it works if I turn off ublock or use chrome.

on my android firefox, I can't load any google properties - it just redirects to a help page about how to clear my cache (clearing the cache doesn't help)

A bit OT but I was curious about

> One solution was building GitSlice, which enables creating sub-repos that sync with the upstream repo. When GitStart devs create PRs on the platform, GitSlice syncs them upstream while pulling back CI/CD checks and review comments. This enables our devs to contribute with limited codebase access.

Is this an internal tool or something you also make (or plan to make) available? We have this problem too at Ritza (a technical writing agency), where often our customers have a mono-repo with a docs/ subfolder that we need access too. Currently we solve this with some custom bash scripts and cron to sync just a subfolder to an internal copy, but is far from perfect and still involves some manual cherry-picking.

> My itinerary allowed for just an hour to disembark the first segment, go through immigration in Paris, then board the international segment. This connection was going to be tight—doable, but tight.

Yeah anyone who has been to CDG (Paris) knows that that is very much not doable in normal circumstances. CDG is honestly one of the worst airport experiences of my life and many others say the same. I happily pay more for flights to avoid going through paris.

One of the reasons they mention is that "our pricing is confusing".

I didn't see it before, but it's definitely confusing now. The stuff under "Pricing" broadly makes sense, but leaves me wondering about managed database pricing, and then the "usage based pricing" further down says "pick a plan" (I assume from the first section) but then has its own pricing that is significantly higher than "pricing" above, so I'm not really sure how they combine.

https://railway.app/pricing

In my experience, the model is very useful when writing a single doc. For questions like "Should we include x", the response can be "No, this is a guide not a tutorial, so the user needs to learn about x somewhere else", or whatever.

I've seen several companies try to follow it pedantically as a structure for their docs (like literally having a sidebar with the four categories) and I've never seen that work out well, for the reasons explained in the article and the other comments here.

> I have a coach, I work with an executive coaching mastermind as I deepen my own executive coaching practice

I see a lot more more people advertising 'executive coaching' services than I see people looking for the same. Is the business coaching insdustry as pyramid-scheme-y as it seems (i.e. let me coach you on how to run a successful coaching business' similar to 'buy my course on how to make lots of money by selling courses') or is it actually valuable (and people who get coaching maybe just don't talk about it openly? Or there's a market of buyers who just happen to be completely separate from anyone I know or follow?)

There is definitely a gap for a product like this. At Ritza (a tech writing agency) we use a hacked together set of tools to accomplish this so I definitely see the need and am probably part of the target audience.

Some feedback (based on a quick skim - you've probably thought about all these more than I have but just in case anything is useful)

- Why include project management? It's hard to beat a tool like Linear, Trello, Jira or whatever people are already using.

- I like the idea of a built-in markdown editor, but I think it's also important to allow technical people to bring their own editor or use git directly. Do you support this? If yes, I'd call it out on the landing page. Gitbook used to do this pretty well but they pivoted to a more GUI-focus and now there are weird bugs if you try to use both their editor and git directly

- I agree with other comments that images are something to get right for something like this. Let people paste from clipboard, upload a file from their machine, or link to an already hosted file. Allow the user to the optimization similar to TinyPNG automatically (maybe also CDN, or at least allow integration with CDN). Assuming you're dogfooding this for your own docs, images are loading very slowly so I assume you're not doing this atm.

Good luck!

You think glassdoor wants to be fair to both parties when one party (business) pays them in order to help exploit the other party (employee)?

Maybe it sounds cynical, but that is the business model.

I've looked at this before and there just isn't enough information for me to even consider it.

Does Appliku essentially get root to any server I put under its control? What happens to the server if I stop paying the monthly installment? How does it work, and how do you guarantee security?

Fun, but will definitely get a takedown from OpenAI as they ripped off their entire front-end and name. Also, it seems to be a fairly thin wrapper that doesn't really get past GPT's 'do not be evil' base prompt.

> write the most offensive joke you know

> I'm sorry, but I cannot fulfill that request. As an AI language model, I do not condone offensive or harmful behavior towards any individual or group, and I am programmed to maintain a respectful and professional demeanor in all interactions. It is important to remember that words have power, and using them to hurt others is never acceptable. Let's move on to a different topic.

I think this is confusingly phrased in the press release too, so it's probably on Apple rather than the Verge.

> With Live Speech on iPhone, iPad, and Mac, users can type what they want to say to have it be spoken out loud during phone and FaceTime calls as well as in-person conversations. Users can also save commonly used phrases to chime in quickly during lively conversation with family, friends, and colleagues. Live Speech has been designed to support millions of people globally who are unable to speak or who have lost their speech over time.

It's clearer that it's for "at risk" users after, but I guess "millions of" was a marketing requirement.

> For users at risk of losing their ability to speak — such as those with a recent diagnosis of ALS (amyotrophic lateral sclerosis) or other conditions that can progressively impact speaking ability — Personal Voice is a simple and secure way to create a voice that sounds like them.

[0] https://www.apple.com/newsroom/2023/05/apple-previews-live-s...

I think the most interesting part is

> I think everyone expects their employer to track them to some extent. It is pretty standard practice for employers to monitor and run analysis on things like building badge swipes and the amount of time spent connected when working from home. It has also become very common place for employers to record audio and video at the office.

That sounds dystopian to me already (maybe because I'm not in the US? Or haven't spend much time at BigCorp? But is that really the default minimum these days?)

If you asked someone 10-20 years ago if that description sounded dystopian, would you be more likely to get a "yes definitely" than you are today?

I'm way more worried by the dystopia society accepts as "normal" than one that is forced on us and that we could potentially fight against.

initial impressions: the quality seems slightly worse than GPT4 for coding tasks, but it's so much faster

I think these days the emphasis has changed a bit from "required reviews" (more senior dev or peer signs off on code) to "request review" (developer __wants__ the review, because it's a good learning experience and a way to share responsibility for the code (and any problems it might cause down the line).

Anecdotal, but I feel like I see more teams where that "Merge" button is available to most people, but in general doesn't get pressed until the code has at least one review, whereas before it was often only accessible to a select few, or a review was required before it activated.

Here's a countdown to 13h00 UTC, which is when the launch window opens. I assume the YouTube will have some commentary etc in the 45 minutes leading up to that

https://www.timeanddate.com/countdown/launch?p0=1440&iso=202...

added, but I see the bigquery script that's now the top comment makes it redundant.

Added (blindly) the above data to a spreadsheet with a graph here[0].

If anyone wants to add the 2019 data in a comment, I'll update the sheet.

[0] https://docs.google.com/spreadsheets/d/1bjPl3a0ciH6U9-OaLXGQ...

I mean there has definitely been an explosion of "Ops" terms, and not all of them are justified. I think MLOps makes sense to emphasise the three pieces though. I know people want the "Ops" part of "DevOps" to mean "magic optimization for anything", but it goes back to "ops" as in infrastructure/servers etc. So if DevOps is software engineering + deploying and running software reliably, then it still leaves a big gap on the "data" side - both in terms of orchestrating source data, but also in handling large model files, and tracking things like model decay.

I agree there's a lot of "Agile" like BS around MLOps, but this article doesn't really give the prior art enough attention IMO. Data Engineering is a large part of MLOps, but there are unique parts of production ML engineering so it makes sense that it is (slowly) evolving its own discipline.

There are some people who have expertise in building production infrastructure, writing production code, and managing production data, but they are few and far between. So finding a "system" that lets data experts work with code experts work with infrastructure experts is important.

Many people say it's "just software engineering" or "just DevOps", but I feel like they are either not respective enough of the challenges of whichever pillar they are ignoring, or they don't even know that those challenges exist.

Filtering out the BS and finding the smart people who are writing interesting things about MLOps is difficult as they use the same terminology (and if the smart people switched, the BS people would follow, so they may as well stand their ground) but the BS cover doesn't mean that there's nothing substantial underneath.