They mean “percentage points”.

https://www.gov.uk/late-commercial-payments-interest-debt-re...

As I understand it, from our lawyer, is that this exact wording is automatically enforceable in UK courts and easiest in the event of a dispute. It’s also generally internationally accepted.

It costs something like 80 quid to file for recovery in court and in our experience invoices are immediately paid up when a “Letter before action” is sent.

You burn the relationship, but arguably you probably don’t want it anyway.

- Payment is due X days after receipt of invoice, or immediately after the consultant has addressed any quality issues, whichever is sooner

- Late payment shall incur interest at 8% above the BoE base rate and a late fee of 100 GBP as per the UK Late Payment Legislation. Partial payments on invoices shall apply to late fees, interest, and then principal, in that order.

- In the event of a late payment the invoice for the next deliverable shall immediately fall due.

- The consultant shall be entitled to shift deadlines on deliverables in the event of a late payment as a result of any work disruption, without incurring any liability.

- Payment shall be made in X currency, or an exchange rate at X date on Oanda.com shall apply.

- The client is responsible for any bank fees incurred by their, or any intermediary bank. In the event of a SWIFT transaction it shall be made with the OUR payment code.

- The jurisdiction in the event of a conflict shall be England and Wales. Neither party shall be bound by arbitration.

- The client and consultant shall both indemnify the other up to the total value of the contract and shall not under any circumstance be liable beyond X GBP.

We also no longer share downloadable links of our deliverables until they are paid up. They get a view/comment only link for reports/data etc.

We’ve found that clients that aren’t willing to accept these terms won’t pay you either way.

We determine the net days on the invoice based on the credit rating of the client. Ironically, the good clients pay within 2-3 days normally, and the difficult ones are very “long tail”. About 1% of contracts tend to fully or partially default on their payments.

We’re in a particularly credit poor industry but our average delay due to late payment is 23 days. Those clients where we stop delivery pay on average 11 days sooner than those contracts where we don’t stop delivery.

This is based on around 2,000 invoices sent over the last 5 years.

I spent the last two days building this exact thing for our internal use.

Managed to get a full RAG pipeline integrated and running with all of our company documents in less than two days work.

Chunking, embedding and querying, connected to S3 and Google Drive, and running on our own hardware (and scaling on AWS too if needed).

AI has led us into a deep spaghetti hole in one product where it was allowed free rein. But when applied to localised contexts. Sort of a class at a time it’s really excellent and productivity explodes.

I mostly use it to type out implementations of individual methods after it has suggested interfaces that I modify by hand. Then it writes the tests for me too very quickly.

As soon as you let it do more though, it will invariably tie itself into a knot - all the while confidently ascertaining that it knows what it’s doing.

So we ended up with “auth service” instead of something like “Galactus”. The problem of course is that “auth service” isn’t searchable in our monorepo and it was a nightmare to find or discuss any info or references to the service itself. Now imagine if docker was called “container manager”. Good luck googling that and disentangling it from all the search results.

The value of a name doesn’t come from it being self-explanatory but rather from it being a pseudo-unique identifier. The small cognitive tax of remembering it serves as a shared bookmark between people that you can refer to when discussing or speaking to others about it - whether we’re talking about docker, Linux, or another person.

It’s like the Gell-Mann amnesia effect applied to AI. :)

https://en.wikipedia.org/wiki/Gell-Mann_amnesia_effect

Even leaving your laptop unlocked for seconds in the office would have someone /pwn it in slack and get flagged by security.

If there’s one thing they took extremely seriously it was data security.

Stockholm is jokingly referred to as Teslatown these days.

In the UK it’s pretty mixed between Tesla, VW, Kia, BYD, and BMW.

France like their Peugeots …

In Italy last year I saw one EV in the whole time I was there … (although it’s supposedly 5% of new car sales)

It certainly still is true today. Anybody who is sufficiently motivated to cheat can pass it. It was true prior to ChatGPT, and it still remains true today. And yet they don’t. Most people completely fail these screens

> It does for mine, because we've hired all of the good developers that get through the process you're describing and it isn't enough.

Then your industry is atypical in the type of applicants that you are getting. So to accommodate you’ve had to increase your false positives to reduce false negatives. That’s completely fine if it’s what you need to do, but it’s not the typical experience for a tech company.

We also do a pair screen after the code test and we still reject around 80% who make it to that stage. How do you scale interviewing everyone if you don’t pre screen?

The same logic sort of applies to Tim and his performance. The bias of having an imperfect metric is probably much better than the bias of letting an army of middle managers go with their cut. Besides, it doesn’t have to be a hard filtering function at this stage, but a metric to indicate that we need to look a little closer at Tim

The blog poster could’ve asked, why does the manager want me to deliver the story points? It’s because Jake is also delivering zero story points and he’s a terrible engineer and it’s a good canary metric.

If I may latch on to your first paragraph, my point is that we are saying this first bit “this system is broken” and are happy to throw out the baby with the bath water and tear it all apart, on flimsy evidence and generalisations.

And yes, there’s definitely something to be said about the HN crowd having a temperament toward innovation, but I don’t think that’s in any way orthogonal to my point. In fact, this community is far more rational than most others, so I would sort of expect us to rationally look at company processes too, but for some reason we seem to have a blind spot when it comes to our managers and executives and the ‘horrors and hoops’ they make us jump through every day.

Giving Tim the benefit of the doubt in this story, it still holds true that for every extraordinary and invisible superstar like Tim there are 99 under-performers who are indistinguishable from him.

We need to empathise with our managers and the processes in our organisations to understand their purpose and how they came to be.

We, software engineers, keep picking out singular data points of evidence to point at a flawed and unfair world, that go against our self inflated egos.

The brew guy inverting the binary tree and Tim being great, does not invalidate the practices of whiteboards and story points as a general practice.

To your final point, the best organisations that I’ve worked with used metrics in a very effective way (mostly in start ups). The worst did too. Just because some do it poorly, does not mean that it’s bad across the board.

What is tiring, is the unfair, and low expectation of the quality of evidence demanded of the anti-establishment notions in software development, before they are taken as gospel by this community.

And, in my experience, the people who are the strongest proponents of sidestepping or dismantling these processes overlap strongly with those who also do not deliver value to their teams.

We’re told of the hero, who goes against their managers and executives and doesn’t deliver any stories as agreed in sprints.

We’re told of the engineer who isn’t hired by Google because he can’t invert a binary tree. Everyone else piles on and decree that, yes indeed, you cannot measure developer efficiency with a Leetcode or whiteboard problem. We’re too good for that. Another engineer chimes in: “I don’t test my candidates. The best people I worked with were hired over a beer and a chat at the local pub”

We’re told of the MBAs who destroy the organisation, by introducing evil metrics, and how that the work we do are immeasurable and that the PHBs don’t understand how great we are. 10x engineers aren’t a real thing, everyone is equally productive in our digital utopia.

Meanwhile in the real world, hordes of awful engineers deliver no story points, because they in fact, do nothing and only waste time and lowers morale.

Meanwhile in the real world, each job opportunity has thousands of applicants who can barely write a for loop. Leetcode and whiteboards filter these people out effectively every day.

Meanwhile in the real world, metrics on delivery, features and bugs drive company growth and success for those companies that employ them.

To me, all these heroes, and above process people, just strike me as difficult to work with narcissists who are poor at communication. We are not special, and we do not sit above every other department in our organisation.

Every time you’d start the tv it’d switch to the Samsung Baywatch 24/7 stream.

So inappropriate for the children.

I installed solar panels at home and the car is now pretty much completely free to drive during those summer months where I get enough sun to supply my house and the car. I think these panels had an ROI of around 4 years for me, which is crazy good.