Each district you draw is the only thing that counts for voting.
So, "gerrymandering" the districts to make it so the least popular "party" wins is the objective of the game. What's maybe not clear about the game is that each dot represents one animal and not say another mini district.
Tests can be green and I think doing E2E is better than just unit tests. But it's also very easy to have hundreds of tests that are green - but if they are testing the wrong thing then it really doesn't matter.
Ultimately, you spec out these tests and create deterministic code around them - but that doesn't mean that the tests didn't drift from the intended spec.
I think I agree with the author in that what you were TRYING to achieve is much more important than what you actually achieved (in code or tests) and actually using the product is your best defense to see if code / spec has drifted.
But good gherkin tests encode pretty well what I’m trying to achieve, because they can be super high level - any flight level I want them to be. The only precondition is that the test env can deterministically measure the conditions.
Basically every large company has gone all in on AI, and as a result the number of bots has (likely, I have no proof) exploded. Then as a result of that, they crack down on "potential bots" by banning them. Of course, all they care about is what % of bots they cracked down on now what % of real people. Then because they've gone all in on AI, you can't get an actual human to help you... just a bot they trained to always say no.
My current experiences in these arena:
- Opened a Meta for Business account to try and buy ads. Immediate lifetime ban before taking even a single action. Most likely thing that looks like a bot? Opening a new account.
- Got bot farmed on a Google Ads campaign, delivered definitive proof of it to Google. Never got a real human, just went back and forth with a bot who was told to acknowledge everything I said without admitting fault. End result - no refund, the bot farm still operates, and I have to be super careful when buying Google Ads.
- Tried to open an account to post stuff on Reddit, every post gets instantly banned because I don't have enough karma. Try to start posting comments to get karma, same thing. IN fairness, this did eventually start to work - where I could post on certain subreddits and comment in others.
Overall the experience always has the same shape - something super opaque to the end user, no resolution options, and really you are left with no alternatives because every big tech firm is doing this.
So then the same AIs that create the problem recommend you try and get media articles published about it to draw attention to the plights of the real human caused by AI bots.
>Immediate lifetime ban before taking even a single action
This actually sounds like a fun way to manipulate these large companies...
Put together a set of stolen credentials that contain business owners and other people that are likely to make these companies money.
Then use that information and bots to get them permanently banned from the platform. You'd have to do it somewhat slowly, but eventually it would start adding up to real damages.
>Opened a Meta for Business account to try and buy ads. Immediate lifetime ban before taking even a single action.
It let me pay for ads for 2 weeks and then decided I need a temporary ban. Theres no reason posted for the ban. Temporary ban has no end date. Every time I submit a support ticket, they tell me to just chill out and maybe it will end next week. This has been going on 3 years.
I'm definitely on board with governments owning stuff - I think the traditional issue has been that government jobs don't attract the best talent (lower pay / whatever). So the types of people that go to government jobs are the ones that like stability and moving slow. That's probably fine - but it has also given them the reputation for being really inefficient.
The natural response is to assume that corporation will be more efficient, and there the consumer will get a better end result. And, again, that was probably true for some period of time. The problem is in a corporate world you need to grow your profits by 3-5% a year (minimum) in order to be considered a "viable" investment. So what happens when your customer base isn't growing at 3-5%? Well you cut costs to improve your profits or you raise prices or both.
End result is the consumer ends up worse off, they got a one-time efficiency gain by switching from government to corporate - but then pay for that over decades.
Honestly, the simplest answer is that only like 20-30% of an actual company is the idea / the product. The rest is selling it. I think in areas where selling is adjacent to the selling they are doing now - then they are going to end up doing it.
Anything software related they will end up being "in", in some form or another. Why? They are already selling to enterprises and have their trust. The selling motion for Project Management software may be slightly different than Enterprise AI - but it's close enough to rhyme.
They will probably also end up in anything consulting related. Why? Well again most consulting comes from Enterprise or Government. They are already selling to both. Probably Enterprise moves away from Accenture / Deloitte / McKinsey towards Anthropic / OpenAI faster than Government - but still the point remains.
Yeah - in my own personal experience building AI products this still holds true. And you can see it in the way they behave themselves, they don't really write prompts for themselves to use in the future (say CLAUDE.md) when they need the output to be deterministic. They write code for it, then write tests around that code, then fix the bugs in that code.
Yes it all started with "natural language", but even AI has an understanding that you need more structure than natural language when you want deterministic results.
Like what matters is:
- Does it do the thing it's supposed to do
- Does it do it with a reasonable amount of resources
- Does it do it without any obvious security flaws
Yeah, if they were nuclear codes you'd want to be really really sure and you'd probably want to check every line yourself. But if you're making a habit tracker or 95% of apps out there, it really doesn't matter.
There is definitely some skill in piloting the LLM, where you have an advantage if you understand what "good" is - but I'd argue it really isn't that necessary in most cases. McDonald's has had a lot of success selling food that most chefs would say isn't that great, but it fills that need at that moment.
Yeah I agree - if you're very clear and consistent with how you ask it score something it will do well. Not fundamentally different than giving it clear instructions when you code.
One thing that has helped me make the LLM more consistent on scoring is deduction based rubrics. Start everything at perfect and deduct points for specific things (ie style, missed facts, etc). It gives much tighter final scores under these conditions (for me) than giving rubrics + samples.
I feel like newer systems are even worse, probably in about 50% of my online experiences now I just get "banned" immediately. Opening a new account = sign of a bot = banned.
Hyper focusing on detecting bots without thinking about the humans you're blocking is making the Internet a crappier place.
This is very cool - one minor issue, when I zoomed out on a Metropolis it hung for a very long time at the several block radius and then after say ~20-30s it then was able to load the full city.
After that it still did it on various different views but it was much faster.
So, "gerrymandering" the districts to make it so the least popular "party" wins is the objective of the game. What's maybe not clear about the game is that each dot represents one animal and not say another mini district.
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