arnvald

Agreed, similarly to what they're doing with Hashicorp (though way to early to say if it works out for both sides in the end)

In some companies yes, but in other ones when comparing two similarly priced products, the decision will be made based on something else than just a budget.

Currently often the narrative is “we have it included for $0, why would we pay $100 per year per employee for a similar product?”

Companies grow - today you have 50 engineers and a few microservices, in 2 years you might have 200 engineers and tons of APIs and web applications. I think if old orgs could have bought off the shelf developer portals years ago, they would have. Now companies that grow have this option.

It might not be a massive market, but there are a few interesting companies building this kind of tools and they sell it

By default it offers you a few tools to better understand and manage your software landscape:

- you have all your micro services catalogues in one place, with a fairly decent data model (services are grouped into systems, they are owned by teams, they have declared dependencies on each other)

- you have documentation for each service that you can easily find

- you have a template catalogue that allows you to easily create new services. You need a full-stack app? Here, recommend option is Java + React, use this template. You need a new ML system? Here’s what you should use, click “create” and we’ll bootstrap it for you

- plus a few more, like customizable home page

If you are looking for a way to start cataloguing and standardizing services across your org, the developer portal (whether Backstage or other solution) is a good thing to have

I’ve introduced it at a company with ~3,000 engineers and it’s been quite successful, though we do not yet leverage all of its power and we do have a dedicated team to run it and build on top of it

We have a lot of in-house tooling and Backstage allows us to move big chunk of UIs into one place - it helps us keep UIs consistent, and makes it easier for everyone to find the tools we have. However with a lot of older, more mature in-house tooling it’s been a struggle to migrate to their data model, introduce their software templates etc.

For an org with ~50 engineers I’d recommend something more off-the-shelf like Cortex, Port, or OpsLevel

Not sure about review sites, but there are companies specializing in ransomware negotiations on behalf of the victims and they can advise not to pay a group that is known to release the data anyway

Is there any comparably complete framework that does not need any significant adjustments even when it's used by 1000s of developers building the same app?

This is a first of its kind, I'm sure over time they'll become more efficient.

But yes, probably not using carbon would be better, so maybe if we have proper capabilities and laws in place, companies might be forced to remove all the carbon they release - that will either make them pay for such service or push towards reducing carbon as much as possible

I’m quite surprised it’s dropped “only” by 55%.

Musk made the offer just before a big drop in valuation of tech companies. Even if Twitter revenue remained stable it probably wouldn’t be worth $44B Musk paid.

With a drop in usage, drop in ads, controversy around the bots, misinformation, failure of Twitter Blue, I would expect that the actual value is quite below the said $19B.

Maybe the cost saving measures partially offset the drop in revenue? They crippled functionality for guest users quite a lot (I’m not logged in on my work laptop and I can’t see quote tweets nor replies), their workforce is 5x smaller, it seems their costs are way lower than before.

The benefit is that you still profit from actions that break the law.

If it's possible to stop breaking the law in a way that the revenue drop is smaller than $30M a year, they'll possibly do it at some point. However, it's possible that the drop would be bigger, in which case the $30M/y fine is just cost of doing business.

The initial response had 2 problems - not counting Sally and counting sisters separately for each brother. Your hint pointed out the 1st problem, but then LLM should still provide wrong solution. This makes me think that maybe it would try another answer and explanation no matter what you said. If your reply was just "no, think again" it could also provide the right answer

At this points it looks like Germany is almost allergic to innovation.

Their government introduces more bureaucracy for companies, discouraging investments there. Berlin had a chance to take #1 spot as the tech capital of Europe post-Brexit, instead we rarely see any new unicorns coming from there.

Auto industry is another example - Volkswagen and Volvo groups are #4 and #5 when it comes to battery-only electric cars, and they're behind Tesla, BYD and SAIC (both Chinese). They're not innovators, they're still behind and I don't know if they'll catch up.

As an EU citizen I feel more and more negative about the economic future here, with UK having left and the biggest countries (Germany, France, Italy, Spain) struggling to stay relevant, especially in tech industry where AI can soon turn cause a major power shift.

I've never seen this before. What an incredibly powerful act, this might have taken so much courage. Thank you for sharing!

It reminds me of Segway back in late 90s. Hailed as "the next big thing" by millionaires who invested in it, it was a mysterious device that nobody even knew what it would do. We all know how it ended

> And every two weeks during my 1:1 discussions with each engineer, I would also pull up that individual’s personal velocity chart (...) And if their chart is on a downward trend or significantly lagging behind their teammates, I would ask them what I can do to unblock them and help them achieve their full potential

> In fact, when discussing velocity metrics in 1:1 conversations, you should explicitly avoid comparing them against one another

These sentences are in 2 subsequent paragraphs. Compare people against each other, but you should explicitly avoid comparing them against one another. Sure thing.

> Ultimately, using lines of code, commit counts, or pull requests, to quantify engineering performance is a fool’s errand. All it does is create a culture where dishonest people write bad code to get ahead, and those with integrity are penalized and eventually quit in frustration.

But somehow velocity, which is an abstract, imprecise, and very error-prone measurement should be used as a primary metric for both team- and individual-based performance?

This article is such a mixed bag. There are great points like "don't estimate time", but then the author throws things like the quotes above. It feels like one of these "you're so close to getting it right" situations.

Also, as another commenter here mentioned – this can be gamified, because 5-point complex new feature is surely more time consuming and difficult than 5x1-point cosmetic changes. Hence, everyone should aim to take as many small tasks as possible in order to have higher individual velocity than other team members.

They're not mutually exclusive. Ideally OpenAI wants regulation that will put them ahead of others, which means:

* set the bar high enough that competition needs to put more effort (or maybe is entirely prevented from entering the market)

* set the bar low enough that OpenAI's business model is not affected (e.g. does not require them to spend significant amount of time and resources on complying with the regulation)

So in US they can lobby for more rules while in EU for fewer restrictions.

When who got acquired? Twillio? They're a public company, aren't they?

I think there's a difference in how visible these skills are.

As an engineer it's easy to practice many new skills and also to see improvement. I might be interested in orchestration, I pick up Kubernetes course. I want to build iOS app, I start learning Swift. After a month or two I can see a difference in my skills. Others can see it too - I contributed to iOS app at work which I haven't done before, it's a new skill I learned.

As a manager, I need to be better at negotiating with stakeholders, or recognizing underperformance, or interviewing candidates. I can read books, take courses, but I can only see my improvement over longer period of time. What's more, most of people around me won't see that I'm a better interviewer now, or that I'm better at helping to improve individual performance. It doesn't mean I stopped growing, it doesn't mean I don't cultivate new skills. They're just different skills.

This. The state of leadership training in our industry is abysmal. Most managers I've met get little to no training when they transition to leadership roles. It's slightly better in larger companies, but as you say - a stark contract with military

> Not even in salary in many places

What needs to die is this trope. Few places cut salaries when people move to EM role. This might be true for some big tech companies, but even then it's only in the beginning. If you look at companies that have unified levels for SDEs and EMs (Google, Amazon), you can see that on the same level EMs have slightly higher TC.

Not to mention that there's a whole world outside of big tech where moving to management is considered a promotion (and often the only way to grow, because dual career ladder is not implemented everywhere). The cases where EMs make more than SDEs are really way more common than the reverse situation.

I see €5.49 as the lowest price (monthly subscription), with €99.99 being a "lifetime" price

Which is fine, isn't it?

The way I see it, there are 2 options: either you buy software "as is" and can use it forever, but you don't get free access to updates (or get them up to certain point of time), or you pay for a subscription. People who bought old versions of Pixelmator or Photoshop or 1Password can still use them (I have 1Password 4 on one of my devices), as long as the system updates won't render it useless.

What’s your ratio of staff engineers to all engineers?

I always think of staff as engineers working across multiple teams, so there should be ratio of 1:15 to maybe 1:30 (or in another terms, staff engineers should represent 3-7% of all engineers). If the ratio is smaller, like 1:5 or 1:8 then staff engineers are really just senior engineers

Oh, my mistake, I thought it was an additional accessory. Thanks for correcting me!

I think there are still some potential obstacles like diagnostic devices (how to diagnose phone that doesn't boot without a cable?) and pricing - adding magsafe by default would probably raise costs

I know this is not what you meant, but it's a really sad answer.

Not because of Spain, which is a great place where I hope to live again one day, but because the answer to a question "how can I live a comfortable life and save money" is "move 1000km away from your family to a place where you don't know anyone, and don't even speak the language".

It shows that something's really, really wrong with the system if people making significantly above average salary struggle to have a sustainable (in financial sense) and comfortable life in their own country.

My male colleagues enjoy a few months of paternity leave without fear of losing their job. It's not a matter of sex, but culture, law, and policies.

The most intuitive and simple explanation that worked for me is:

* if on the 1st try you choose the correct box (33% chance), then the one you can switch to will be wrong

* if on the 1st try you choose the wrong box (66% chance), then the one you can switch to will be correct one

therefore your goal is to pick the wrong box on the 1st try and then switch, and you have 66% chance to do it

I'm a bit surprised to see this article on GitHub blog, it feels more like something from dev.to - looking at the surface, with little actual insights.

Most of the provided reasons behind Python's popularity are true also for other languages - portable, open source, productive, big community. This can be also said about PHP, Ruby, or Perl back in 2000s. Why isn't Perl as popular as Python?

I don't think it's all about readability or productivity, but about tools that were built over the last 30 years that have been used in academia and now with the boom in ML/AI/Data Science, they made Python an obvious choice to use for the new generation of tools and applications.

Imagine that the boom in ML/AI didn't happen - would Python be #1 language right now?

I mostly agree with you and I think it highly depends on the organizational complexity.

In a smaller company (100 people) I was able to manage 10 people and still had time to write some non-critical code. That's because there was little overhead - just 2 PMs to work with, not many meetings.

Then in a large org (5,000+) it became much harder. Even though I had only 5 reports, I had to attend plenty of cross-dept meetings, had multiple stakeholders, and in order to get anything done I had to talk to 5 different people.

In order to "flatten" the organization, first this complexity must be tackled. If there's s lot of overhead to get things done, removing managers won't help, because now ICs will have to do the job that previously was done by managers