brendamn

Great advice. One point I’d add is to just let yourself be nervous. Once I accept that my voice will wobble and my hands will shake then nervousness starts to feel a little more like excitement.

I enjoy soldering. I enjoy using solder paste, being a human pick and place machine, and then putting boards in the oven. I enjoy building physical devices.

But then I had a hardware startup and learnt something about myself.

I enjoy building one or two of something. I absolutely hate building anything more than that.

Hiding the scrollbar is the real crime here.

If you’re going to write a post about why self-hosting is better than cloud*, then it’s probably a good idea to make sure your site loads in under a minute.

* at least I assume what this post is; I’m still waiting for it to load.

I think this varies wildly depending on where you live. Where I live (Melbourne), just the cost of suitable housing (a/ near a school, b/ close to most jobs, and c/ with space for 1+ children) is so high that it makes it difficult for a lot of couples to even consider children.

https://www.abc.net.au/news/2024-06-04/why-australians-arent...

> If she gets the most joy from Rust, that's what she should use!

In the past I’d try to justify why I’d done something a certain way when another way would’ve been faster / better / cheaper, but I now realise that (at least for personal pursuits) an acceptable answer to “why?” is simply “because I wanted to”.

> He says he is “not bad” at maths – by which he means he came top in the state of New South Wales in his year 12 maths exams

As an Australian that has worked with American companies for a while, this is a behaviour I’ve had to overcome. If you tell an Australian you’re “not bad” at something then they’ll take that to mean that you’re actually quite good, whereas many Americans will understand it to mean that you’re not good.

Offshoring has been around for decades, and if it produced the desired results at the desired price then employers would replace every expensive employee with a cheaper one (where possible). As it stands, offshoring is commonly used by large body shops, and a non-zero amount of work is done offshore, yet the cost for tech talent has increased (at least on average, the last year or two has seen somewhat of a correction).

There are definitely highly talented individuals in low cost areas, but they quickly realise they can earn a Big Tech wage, and are willing to relocate (often relocation is a bonus; as much as we complain sometimes, quality of life in a HCOL area is comparably quite nice compared to many LCOL areas).

The threat of hiring a bunch of cheap offshore labour is a bogeyman; companies would already have done this if it were feasible.

I have a theory that someone found a bunch of cheap generic toys (vehicles, dogs, etc) and realised they could sell a lot of them if they slapped a logo on the side and made a cheap, below average cartoon that showed them to kids.

I’m almost certain that there are other examples of this too.

From W3Tech;

> PHP is used by 77% of all the websites whose server-side programming language we know.

I had a quick look at the methodology section, but it’s not clear to me how accurate this data is. Determining whether a site uses PHP can be relatively straightforward (especially with default extensions / if Wordpress is used / etc), but if a site (potentially using a different language) is behind a reverse proxy/uses an API/etc then it is less clear. Does anyone know whether PHP is over-represented in the results because it’s easy to identify?

No doubt PHP is still huge, but 77% seems almost too huge. There is also a very good chance that PHP is actually that big and I’m just in a different crowd.

It’s been a few years since my last US visit, but my experience has been that Uber (and Lyft) are much better in the States than Uber in Australia.

Frequent cancellations, or a driver just not moving until you cancel the ride, is a major issue in Melbourne. Airport pickup is now basically no different than getting a taxi from the taxi rank. UberEats drivers will often just leave food at a different house on our street, or not at all, even though there is no issue with how our house is marked on maps. There is no quality control with Uber Comfort; 90% of the time it’ll be the same thrashed Camry being used for UberX. I could go on.

We’ve stopped using UberEats as a bunch of restaurants we like have alternative options, but I’m surprised the taxi industry here haven’t gotten their game together. At least among my social group, which are moderate Uber users, the sentiment towards Uber (and the available clones, ie Didi) is negative and if there was any decent competition then we’d all switch in a heartbeat.

How many people who have seen that data are acting as a service to share it, at scale?

> already replacing many people who write for a living

Is this actually the case? Are there examples of professional writers/academics/etc who have lost their jobs to LLMs?

Is there a hardware platform better suited for these types of use cases?

Not that long ago it seemed the tradeoff was either use a cheap but unreliable hobby platform (RPi or Arduino), or a stable but expensive (and usually somewhat custom) platform that involves picking the right components, board design, etc. Espressif sounds like they might be filling this gap, but it’s been a long time since I’ve looked seriously at any of this.

> How many people died in car accidents the last few days?

Car accidents (not involving anyone of note) sadly aren’t novel or newsworthy anymore. A submarine, with people potentially trapped onboard, with limited oxygen, as rescue teams race to the dive site, unfolding in real-time, isn’t exactly something that happens that often.

> I'd say with GPT4 they probably reached the limit of how big the dataset can be

I’m curious about this too; not just on the dataset size, but also the model size. My hunch is that the rapid improvements of the underlying model by making it bigger/giving it more data will slow, and there’ll be more focus on shrinking the models/other optimisations.

Using WhatsApp as an example of a lean engineering org should almost be banned at this point. WhatsApp had a high performing engineering team that used basically the perfect set of tools to build their application (which also had a narrow feature scope; plaintext messaging). Even with hindsight there is very little you could do to improve on how they executed.

Just because WhatsApp scaled to almost half a billion users with a small engineering team doesn't mean that's the standard, or even achievable, for almost all teams.

Outsource to where? Outsourcing isn't exactly new and many large orgs already outsource as many activities/projects/roles as possible. Even with outsourcing there is still a skilled tech labor shortage.

I’d be careful making assumptions about a group of people like you’ve done here. I’m not quite old enough to be in the “dad professional class”, but I’ve been around long enough to have worked with plenty of people who are. In my experience, the people who dress “like shit in ill-fitting [overly professional button downs and slacks]” have been dressing like that for at least the last 20 years, and that it was common (at least in IT/development) to dress like that.

Tech workers dressing casually at the office is only a (relevantly) recent phenomenon. Working from home, for a lot of people, is even more recent.

You’ve made a lot of assumptions, and I would consider that this group of people are just defaulting back to what they’re used to, rather than “avoid their wife and collect a salary”.

I don’t know where you work, what industry, or the demographics of who works there, but if “people [who work there] don’t always take them seriously”, and it’s based on older people dressing like older people, then there is a culture problem.

They use their own phone to order.

I’ve found myself in a similar position. I’ve often wondered whether the cause is one specific thing (eg my ideas seem small / less impactful than other projects I’ve worked on), or the culmination of several things.

I suspect in my case it’s a combination, but with a big dose of “been there, done that”. There’s only so many times you can get excited about a new tool or optimization.

The answer is, of course, to dive into something that isn’t tech. There’ll be a host of problems that seem/are fresh and interesting.

Using WhatsApp as an example of a lean engineering org should almost be banned at this point. WhatsApp had a high performing engineering team that used basically the perfect set of tools to build their application (which also had a narrow feature scope; plaintext messaging). Even with hindsight there is very little you could do to improve on how they executed.

Just because WhatsApp scaled to almost half a billion users with a small engineering team doesn't mean that's the standard, or even achievable, for almost all teams.