I have been working on it for a few years. Unfortunately it is currently put on pause, possibly for the entire 2026, but it will launch, and it will be a really useful tool for those that need something like this. I am very hopeful
From my perspective biggest shift is that people that would never have made anything digital 10 years ago are now making their own apps and websites. It is cool to see because often they make things that currently do not exist. The downside is that we software people that have been in the trenches for a while also learn about laws, cyber security and other topics that you should know, but claude won’t tell you unless you know what to ask for. These people have never heard about any of these things, and what I have seen so far getting built ranges from slightly risky to straight up super illegal. All without no clue what they are doing, no warning from claude, and the timeline from zero to launching something illegal can now be done by the average person in an evening.
This is both good and bad. We get more new stuff, people enjoy creating these websites, but they risk themselves and others people in the process. Like a kid being allowed to drive a partly autonomous car.
The super annoying thing I have encountered are managers and other low technical people with some influence over engineers that now believe they ”know the limitations of AI” because they managed to make a CRUD demo in 30min. More than once have someone in my vicinity expected claude to one shot an algorithm that might be physically impossible to even do. I have also seen people try to ”prove” that it is possible by having claude make this algorithm on some toy example where the output looks okay at first glance, but with no verification that it is actually correct. And now the engineers ”just need to take it to production”. AI have made any professional software development 100x worse in my experience. Annoying people that previously could be convinced that certain things are not quick and easy are now extra stubborn, extra annoying, extra time consuming to deal with. Therefore, in my professional life, AI is a big net negative when it comes to efficient use of time. AI made all bad things worse, and barely brought anything good with it. I am convinced that it doesn’t have to be like this, but most organizations are dysfunctional to some level, and that just became worse. If I could go back in time, I would not have gone into software engineering. I love the field, but there is just too much BS going on.
I also see and hear about tiny teams being more effective than ever, teams that already have the skills to know what they are building, and how. They can ship more, faster, and still ensure reliability because they know what they are doing, and they are allowed to spend the time if needed to ensure things are done correctly (without AI powered ”managers” standing in their way).
I think we will see many small companies literally come out of nowhere, no funding, no big names behind them and completely crush companies 1000x their size because of AI. I also believe big slow organizations will use AI to become less efficient and ship worse products while panicking on their way down, ensuring ”all in on AI” by sending more emails faster than ever.
More easy problems will be solved than ever, every imaginable easy problem will be possible for anyone to solve. The hard novel problems will remain unsolved, remain difficult and only the smartest, most stubborn, most stupid people will attempt to solve them, and if they do, the market will reward them.
I took another look at this and it seem like the issue is a bug where firefox on linux for some reason fails to enable hardware acceleration when using WebGL. The landing page requires WebGL to function properly and will fall back to non accelerated rendering if it fails. I could not reproduce this on arch Linux with latest firefox build, plain default install. So it could be that some setting or extension in your browser triggers this issue. But thank you for letting me know about this :)
I think this is the case. In the early GPT-4 days I tested the same model side by side across the subscription and API. The API always produced a longer better answer. To me it felt like the API model was working how it was supposed to work while the subscription model tried to reduce its token usage. From a business perspective that would make sense. I then switched to API only because I felt like it was worth the extra cost.
I did a similar test with sonnet about 6 months ago and noticed no difference, except that the subscription was way cheaper than API access. This is not the case anymore, at least not for me. The subscription these days only lasts for a few requests before it hits the usage limit and goes over to ”extra usage” billing. Last week I burned through my entire subscription budget and 80$ worth of extra usage in about 1h. That is not sustainable for me and the reason I started looking at alternatives.
From a business perspective it all makes sense. Anthropic recently gave away a ton of extra usage for free. Now people have balance on their accounts that Anthropic needs to pay for with compute, suddenly they release a model that seem to burn those tokens faster than ever. Last week I felt like the model did the opposite, it was stopping mid implementation and forgetting things after only 2 turns. Based on the responses I got it seemed like they were running out of compute, lobotomized their model and made it think less, give shorter answers etc. Probably they are also doing A/B testing on every change so my experience might be wildly different from someone else.
I can't notice any difference to 4.6 from 3 weeks ago, except that this model burns way more tokens, and produces much longer plans. To me it seem like this model is just the same as 4.6 but with a bigger token budget on all effort levels. I guess this is one way how Anthropic plans to make their business profitable.
During the past weeks of lobotomized opus, I tried a few different open weight models side by side with "opus 4.6" on the same issue. The open weights outperformed opus 4.6, and did it way faster and cheaper. I tried the same problem against Opus 4.7 today and it did manage to find one additional edge case that is not critical, but should be logged. So based on my experience, the open weight models managed to solve the exact problem I needed fixed, while Opus 4.7 seem to think a bit more freely at the bigger picture. However Opus 4.7 also consumed way more tokens at a higher price, so the price difference was 10-20x higher on Opus compared to the open weights models. I will use Opus for code review and minor final fixes, and let the open weights models do the heavy lifting from now on. I need a coding setup I can rely on, and clearly Anthropic is not reliable enough to rely on.
Why pay 200$ to randomly get rug-pulled with no warning, when I can pay 20$ for 90% of the intelligence with reliable and higher performance?
The goal is to make every recipe foolproof on the first try, similar to when you walk into a restaurant and just pick what you want to eat without thinking about the details. The goal is to have the same experience, just pick what you want to eat, with recipes that tells you exactly what to do with no magic involved.
Technically it is probably very different from other recipe apps. The database is a huge graph that captures the relations between ingredients and processes. Imagine 'raw potato'->'peeled potato'->'boiled potato'->'mashed potato'. It is all the same ingredients but different processing. The lines between the nodes define the process and the nodes are physical things. Recipes are defined as subsets of the graph. The graph can also wrap around into itself, which is apparently needed to properly define some European dishes in this system. The graph also has multiple layers to capture different relationships that are not process related.
Why was it designed it in this way? Because food/cooking is complex to define. This design is the only way I have found that can capture enough of these complex relationships that the computer can also 'understand' what is going on.
My favourite thing about this is that each recipe is strictly defined in the graph. If the recipe skips a step, or something is undefined, the computer knows that the recipe is incomplete. It won't ask you to do 10 things at the same time and then have something magically appear out of nowhere. It is like compile time checking but for recipes.
It also enables some other superpowers, for example:
• Exclude meat part of the graph = vegetarian. Same thing works with allergies.
• Include meat part of graph = only show me recipes that contain meat.
• Recursive search: search for 'potato' and the computer will know that french fries are made from potato. It can therefore tell you that you could make the hamburger meal, but you will need to complete the french fries recipe first, which should take 60 minutes.
• Adjustable recipe difficulty (experimental): It knows which steps can be done in parallell, and which can't based on how the nodes connect. A beginner can get a slower paced recipe with breathing room between steps, while someone more experienced can do a faster pace and do more things in parallell.
If I knew what it would take to build this, I would never have gotten started. I completely underestimated the complexity of the problem I was trying to solve. But here we are, and now it is basically done and working.
The website captures the key points from a non-technical point of view, and you can enter your email and get notified when it will launch in your country.
The goal is to make every recipe foolproof on the first try, similar to when you walk into a restaurant and just pick what you want to eat without thinking about the details. The goal is to have the same experience, just pick what you want to eat, with recipes that tells you exactly what to do with no magic involved.
Technically it is probably the most advanced recipe app ever made. The database is a huge graph that captures the relations between ingredients and processes. Imagine 'raw potato'->'peeled potato'->'boiled potato'->'mashed potato'. It is all the same ingredients but different processing. The lines between the nodes define the process and the nodes are physical things. Recipes are defined as subsets of the graph. The graph can also wrap around into itself, which is apparently needed to properly define some European dishes in this system. The graph also has multiple layers to capture different relationships that are not process related.
Why was it designed it in this way? Because food/cooking is extremely complex. This design is the only way I have found that can capture enough of these complex relationships that the computer can also 'understand' what is going on.
My favourite thing about this is that each recipe is strictly defined in the graph. If the recipe skips a step, or something is undefined, the computer knows that the recipe is incomplete. It won't ask you to do 10 things at the same time and then have something magically appear out of nowhere. It is like compile time checking but for recipes.
It also enables some other superpowers, for example:
• Exclude meat part of the graph = vegetarian. Same thing works with allergies.
• Include meat part of graph = only show me recipes that contain meat.
• Recursive search: search for 'potato' and the computer will know that french fries are made from potato. It can therefore tell you that you could make the hamburger meal, but you will need to complete the french fries recipe first, which should take 60 minutes.
• Adjustable recipe difficulty (experimental): It knows which steps can be done in parallell, and which can't based on how the nodes connect. A beginner can get a slower paced recipe with breathing room between steps, while someone more experienced can do a faster pace and do more things in parallell.
If I knew what it would take to build this, I would never have gotten started. I completely underestimated the complexity of the problem I was trying to solve. But here we are, and now it is basically done and working.
The website is slightly outdated but captures the key points from a non-technical point of view, and you can enter your email and get notified when it will launch in your country.
I am working on Kastanj. It aims to make cooking as foolproof as it can get. Anyone should be able to cook any recipe and get it right on the first try. Clear step by step images and instructions for everything etc.
It also features a recipe manager with family/friends sync. This makes it possible to upload your grandmother’s cookbook and share them with your whole family.
A recipe app you will actually want to use. No bloat, no ads, very minimalistic but everything works well and bugs gets fixed.
Why? Because most recipe apps and websites are frankly painful to use. I am trying to create the absolute best cooking/recipe experience possible. Something that just works.
A recipe app I built primarily for me and my wife, but realized along the way that others might find it useful too. Tried to make the whole cooking experience as smooth at possible. The recipes are made for the app, and the app is made for the recipes. Tight integration which enables some really cool features. Currently working on algorithmic optimization of recipes based on how fast you work and how many things you can do in parallel. User configurable. This makes it possible to either do very beginner friendly one thing at a time, or speedrun recipes and do multiple tasks at the same time for more skilled people.
First launch will be in 2026 in Swedish. Later in 2026 English launch planned, and then based on demand other languages.
I think the future is both bright and dark. It has never been this easy to create anything yourself. Anything from software to hardware, you can buy and build the tools and make something amazing in your spare time that would only 20 years ago would take a small team with some funding.
There are 2 kinds of companies:
1. The greedy kind that always want more. They see extracting money out of their customers as their sole purpose.
2. The kind that want to build good stuff and help people.
A lot of companies start out as nr 2, but with time and growth, greedy people have a tendency to climb the ladder and turn the nr 2 companies into nr 1 unless the original team knows about this and resist such change. This also means that the founders must be okay living their whole life without owning a Bugatti. VC companies make it hard to stay as nr 2, because even if you are good, if you make a deal with a VC firm that wants to 100x their investment through you, then you have already let the greedy devil through the front door.
A nr 1 company will over time turn into a parasite. Once they extract more value than they give, it is a downward spiral of destruction on the way down. A big part of the US tech economy (as seen from Europe) have "evolved" into parasites. They say they fuel the economy. What they actually mean is that they cause a lot of money to flow around. A parasite that suck a lot of blood will also make a lot of blood flow, so it is not a good measurement of health.
The good news are that parasites die eventually. A lot of people (especially outside US) are very much aware about how toxic american companies have become. In Europe there is right now a whole sector growing rapidly that is doing "X but European" and it looks very promising. This is not only a Europe thing, the same is happening in Asia, but European laws and culture have accelerated it.
What this means is that you will see a lot of destruction and downfall as these giant parasites have to die or kill their hosts. Don't be the host. Don't rely on them. Don't do business with them. Don't work for them. Avoid them like the plague, and don't stand in their way when they fall. They will cause collateral damage, regulators should have stepped in a long time ago, but greed prevented that. These companies are already leaving big billion dollar holes in the market. They can't win those markets back, because in business trust is everything and they have lost trust from these markets. As they continue falling, they need to continue sucking out more blood of their remaining hosts which will further erode trust and create new bigger markets looking for a non toxic alternative. Be that alternative. It has never been easier. The future is bright if you want to.
Random info: "money is the root of all evil" is false. It is actually "the love of money is the root of all kinds of evil". If you dig into the original bible texts, it is clear that it is not talking about money as being evil. It is talking about a spirit (mentality) that in English would be more accurately translated as "greed". It is very clear that greed causes destruction and suffering on all levels. From companies managing to erode the middle class to Putin wanting more land. There are companies that steal (legal with greedy corrupt leaders) water only to sell it back to the local population. Why? Greed. It caused Boeing planes to fall from the sky, it caused the 2008 crash and it will cause the AI crash. No matter how much they eat, they remain hungry without limits. This is what greed does. Greed weaponizes good companies with good ideas and turn it into a money sucking machine with no limits. If you want to resist this, you have to start with yourself. Everything starts with one person. Be that person.
Samsung did something similar 10 years ago with their phones that had a pulsoximeter sensor. It could show on some scale between 0-100 how stressed you was and compare that to previous days. Probably more useful for most people than raw values for many kinds of data.
I think it is insane how much time people collectively spend on feeding themselves. It should be much simpler. Currently your options are something like this:
Option 1: Buy a cooking machine that can do some kinds of food quite well. Will be expensive, can't cook all types of food but works okay according to my colleagues that use them.
Option 2: Learn how to cook 5 recipes well. You will gain speed over time, but you will eat the same 5 things over and over for the rest of your life. This was my personal solution to this problem. This worked great until I met my wife. I am someone that can eat the exact same meal, everyday for months (yes I have done that) and not get tired of it. My wife is not this kind of person. Therefore option 2 stopped being an option after getting married.
Option 3: Learn how to cook for real. This will take a lot of time, failed meals, frustrations etc. But over time you can save good money because you learn how things work from the ground up. You will also gain speed over time, however you constantly need to learn new things, otherwise you will be back at option 2 but with the 20 meals you memorized. Consider this a lifestyle to do well.
Option 4: Only eating pre-made meals. Very expensive. Not good for long term health.
Option 5: Kastanj. An app that helps you cook good food without having to learn everything. If you just know how to hold a knife and what a pan is, then you have sufficient knowledge. The app will guide you through everything step-by-step with pictures. It is as fool-proof as cooking can get. Beta launch is planned in 2026.
The core ideas behind the app:
- Instructions need to be idiot proof so younger me could understand them.
- All instructions needs pictures, because "cut the carrot into (fancy word)" meant nothing to me.
- I am the "robot". The app tells me what to do. I should not have to think and understand. Just following along needs to be enough to succeed.
- Better to have 100 recipes that work 100% of the time, than 1000 recipes that work 50% of the time.
We take recipe quality very seriously. Every recipe is developed and photographed in house. Every recipe is tested at least 3 times with some variation to account for user errors. The app and all content is constantly improving to maximize success. For example, an alpha user recently managed to fail (consistency was a bit off) with one recipe despite following the instructions. The recipe was soft-banned and we set up a test where we cooked that recipe 9 times over until we managed to pinpoint what went wrong and updated the recipe accordingly. We do not accept bad recipes. This means we can't brag about having the biggest recipe collection, because developing recipes like this is slow. However the benefit is that, our users can simply scroll the app like a restaurant menu and feel confident that anything they see, they can make.
It is a recipe app but better, and way more technically capable than anything out there. The goal is to make the best recipe app ever made. With bulletproof easy to follow recipes and smart features to make cooking simple. Everyone deserves good food at home, but good food is complicated and time consuming. An experienced cook can make good food quickly, cheaply and make it look easy. The idea is that Kastanj will have the knowledge you don’t so you can cook like a pro without having to spend years learning everything.
Backstory:
I have a note where I write down practical problems I experience in life. I noticed over time that the amount of notes related to food and cooking was growing faster than anything else. I then began searching for a solution. I tried over 50 recipe apps, always the premium version if possible. There are some good apps out there but even the best ones only solved something like 50% of my issues. After enough frustration and search I just decided to start working on my own app. That was 4 years ago...
It turns out that solving some of these problems where technically complicated to do, so now I understand why no other app could solve my problems. None the less, after 4 years of work, starting over from scratch 5 times, I have now landed on a solution that technically solves all my problems.
Going forward:
Now I am working on filling the app with data and make it easy to use for normal humans. I am on purpose limiting myself to only perfecting the core functionality of what a recipe should be. I intend to launch sometime in 2026. The UI will be small and limited at first, but it is perfect for my needs. Therefore I hope it will also be perfect for someone else. Over time I will enable more advanced functionality and build it out based on user feedback. I know the backend can support 100% of my needs, but I don’t want to make it bloated. Therefore the UI is on purpose focused on only the most important things and then we will build it out with time, together with the recipe creators and end users.