For years I've kept a list of apps / ideas / products I may do someday. I never made the time, with Cursor AI I have already built one, and am working on another. It's enabling me to use frameworks I barely know, like React Native, Swift, etc..
The first prompt (with o1) will get you 60% there, but then you have a different workflow. The prompts can get to a local minimum, where claude/gpt4/etc.. just can't do any better. At which point you need to climb back out and try a different approach.
I recommend git branches to keep track of this. Keep a good working copy in main, and anytime you want to add a feature, make a branch. If you get it almost there, make another branch in case it goes sideways. The biggest issue with developing like this is that you are not a coder anymore; you are a puppet master of a very smart and sometimes totally confused brain.
> For years I've kept a list of apps / ideas / products I may do someday. I never made the time, with Cursor AI I have already built one, and am working on another.
This is one fact that people seem to severely under-appreciate about LLMs.
They're significantly worse at coding in many aspects than even a moderately skilled and motivated intern, but for my hobby projects, until now I haven't had any intern that would even as much as taking a stab at some of the repetitive or just not very interesting subtasks, let alone stick with them over and over again without getting tired of it.
It also reduces the knowledge needed. I don't particularly care about learning how to setup and configure a web extension from scratch. With LLM, I can get 90% of that working in minutes, then focus on the parts that I am interested in. As somebody with ADHD, it was primarily all that supplementary, tangential knowledge which felt like an insurmountable mountain to me and made it impossible to actually try all the ideas I'd had over the years. I'm so much more productive now that I don't have to always get into the weeds for every little thing, which could easily delay progress for hours or even days. I can pick and choose the parts I feel are important to me.
I'm curious: what do you do when the LLM starts hallucinating, or gets stuck in a loop of generating non-working code that it can't get out of? What do you do when you need to troubleshoot and fix an issue it introduced, but has no idea how to fix?
In my experience of these tools, including the flagship models discussed here, this is a deal-breaking problem. If I have to waste time re-prompting to make progress, and reviewing and fixing the generated code, it would be much faster if I wrote the code from scratch myself. The tricky thing is that unless you read and understand the generated code, you really have no idea whether you're progressing or regressing. You can ask the model to generate tests for you as well, but how can you be sure they're written correctly, or covering the right scenarios?
More power to you if you feel like you're being productive, but the difficult things in software development always come in later stages of the project[1]. The devil is always in the details, and modern AI tools are just incapable of getting us across that last 10%. I'm not trying to downplay their usefulness, or imply that they will never get better. I think current models do a reasonably good job of summarizing documentation and producing small snippets of example code I can reuse, but I wouldn't trust them for anything beyond that.
If you have the budget, I have also taken a liking to perplexity.ai. I got it free from my school and it basically aggregates searches for me with sources (but be sure to check them since sometimes it reads between the links so to speak). It basically does the Google searching for me and have returned more up to date API info than Claude nor ChatGPT knew about. Then I would let Claude or ChatGPT know about it by copying doc and source code to work from.
That's literally going through the dark maze blindfolded, just bouncing off the walls randomly and hoping you are generally at least moving to your goal.
If software engineering should look like this, oh boy am I happy to be retiring in mere 17 years (fingers crossed) and not having to spend more time in such work. No way any quality complex code can come up from such approach, and people complain about quality of software now .
> The first prompt (with o1) will get you 60% there, but then you have a different workflow. The prompts can get to a local minimum, where claude/gpt4/etc.. just can't do any better. At which point you need to climb back out and try a different approach.
So you're basically bruteforcing development, a famously efficient technique for... anything.
This is such a lazy, pointless comment that doesn't add anything to the conversation. It's also way off base about what LLMs can actually do, and the fact that they're pretty handy for debugging production code too.
I mean i debug code other engineers wrote every single day... being good at that is part of the job. The biggest difference is i never have to deal with the LLM writing parts i don't want it to write.
What a feat! There's at least 3 pages of google search results for the nearly same thing. The "prompt" I used in google.com is:
site:github.com map comparison
I guess the difference, is that my way uses dramatically less time and resources, but requires directly acknowledging the original coders instead of relying on the plagiarism-ish capabilities of reguritating something through an LLM.
But creating things for which there are many existing, documented examples is what LLMs do best. Without this use case it's almost like they don't provide any value at all.
I have about 6 months of coding experience. All I really knew was how to build a basic MERN app
I’ve been using Sonnet 3.5 to code and I’ve managed to build multiple full fledged apps, including paid ones
Maybe they’re not perfect, but they work and I’ve had no complaints yet. They might not scale to become the next Facebook, but not everything has to scale
I learned to drive before in-car GPS was widely available, at least where I lived.
Going to some new place meant getting a map, looking at it, making a plan, following the plan, keeping track on the map, that sort of thing.
Then I traveled somewhere new, for the first time, with GPS and a navigation sofware. It was quite impressive, and rather easier. I got to my destination the first time, without any problems. And each time after that.
But I did remark that I did not learn the route. The 10th time, the 50th time, I still needed the GPS to guide me. And without it, I would have to start the whole thing from scratch: get a map, make a plan, and so on.
Having done the "manual" navigation with maps lots of times before, it never worries me what I would do without a GPS. But if you're "born" with the GPS, I wonder what you do when it fails.
Are you not worried how you would manage your apps if for some reason the AIs were unavailable?
> The 10th time, the 50th time, I still needed the GPS to guide me.
If anyone else is frustrated by this experience, I've found that changing the setting in Google Maps to have the map always point north has helped me with actually building a mental model of directions. I found instead of just following the line, it forced me to think about whether I'm going north, south, east, or west for each directions.
Pretty sure people I remember similar conversations happening when people decided to produce content for YouTube full time, lean into Node.js as a dev stack, or build iOS apps.
Make hay while the sun shines, friends. It might not last forever, but neither will you!
I learned to code during when internet access was limited to about 1hr/week, extremely slow, and unreliable. But now without inherent I just can’t get any work done. I guess it’s same for a good chunk of people.
I never worried about what would happen if internet were to become unavailable. Given that it’s become one an essential service I just trust that powers that be will make sure to get it back up.
After 50x? I use GPS too, but I definitely learn the route after a few times with it. There are probably a class of people who don’t ever learn it, but I feel like this has to be a minority.
Wondering around a new city today I had a similar thought.
Prior to an iPhone I’d have the general lay of a city memorised within 10min of landing, using a paper tourist map, and probably never feel disoriented, let alone lost.
This morning I walked 2 blocks further than needed (of a 1 block walk) because I wasn’t at all oriented while following Google maps.
I won’t spell out the AI comparison, other than I think more “apps” will be created, and predictable “followed the GPS off a bridge” revelations.
You have to temper your ambitions. Choose languages it understands really well (typescript or python). Choose easier deployment solutions (vercel over docker). Be specific about the versions you’re using (“I’m using nextjs 14 with app router”)
We’ll see what the future holds but as an old timer, using LLMs to creat applications seems exactly the same as:
Python/JS and their ecosystem replacing OS hosted C/C++ which replaced bare metal Assembly which replaced digital logic which replaced analog circuits which replaced mechanical design as the “standard goto tool” for how to create programs.
Starting with punchcard looms and Ada Lovelace maybe.
In every case we trade resource efficiency and lower level understanding for developer velocity and raise the upper bound on system complexity, capability, and somehow performance (despite the wasted efficiency).
Every time I see claims like this, I instinctively click on the user's profile and try to verify if their story checks out.
>I played around a lot with code when I was younger. I built my first site when I was 13 and had a good handle on Javascript back when jQuery was still a pipe dream.
>Started with the Codecademy Ruby track which was pretty easy. Working through RailsTutorial right now.
>I've been freelancing since I was 17. I've dabbled in every kind of online trade imaginable, from domain names to crypto. I've built and sold multiple websites. I also built and sold a small agency.
>I can do some marketing, some coding, some design, some sales, but I'm not particularly good at any of those in isolation.
So I don't really understand where this claim of only "6 months of coding experience" is coming from, when you clearly have been coding on and off for multiple decades.
What do you do if your app has a bug that your LLM isn't able to fix? is your coding experience enough to fix it, or do you ship with bugs hoping customers won't mind?
Genuine question: Do you feel like you're learning the language/frameworks/techniques well? Or do you feel like you're just getting more adept at leveraging the LLM?
Do you think you could you maintain and/or debug someone else's application?
Not as much as I would have if I was writing everything from scratch. But then again, my goal isn’t to be a coder or get a job as a coder - I’m primarily a marketer and got into coding simply because I had a stack of ideas I wanted to experiment with
Most of the things I’ve built are fun things
See: GoUnfaked.com and PlaybookFM.com as examples
PlaybookFM.com is interesting because everything from the code to the podcasts to the logo are AI generated
The more important question that programmers, who are not product makers, often miss is: Are you solving real problems?
It's a slightly orthogonal way of thinking about this but if you are solving real problems, you get away with so much shit, it's unreal.
Maybe Google is not gonna let you code monkey on their monorepo, but you do not have to care. There's enough not-google in the world, and enough real problems.
There are so many frameworks, especially on the web and in Javascript, that I have absolutely zero interest in learning.
In fact, my main reason for not doing any web development is that I find the amount of layers of abstraction and needless complexity for something that should really be simple quite deterring.
I'm sure e.g. React and GraphQL allow people to think about web apps in really elegant and scalable ways, but the learning curve is just way more than I can justify for a side project or a one-off thing at work that will never have more than two or three users opening it once every few months.
I think the front end is the most interesting place right now, because it’s where people are making stuff for themselves with the help of LLMs.
The browser is a great place to build voice chat, 3d, almost any other experience. I expect a renewed interest in granting fuller capabilities to the web, especially background processing and network access.
That seems a bit too much to ask, I want the piece of mind of knowing the browser keeps isolated sandboxes, if that philosophy changes I would be very uncomfortable using the browser.
How about we go back to thick clients, with LLMs the effort required to do that for multiple operating systems will also be reduced, no?
I'm not saying you're wrong at all or in disbelief -- but I've spent lots of time with Claude 3.5 trying to prototype React apps and not even full fledged prototypes -- and I can't get it to make anything bug free somehow.
Maybe I'm "holding it wrong" -- I mean using it incorrectly.
True it renders quite interesting mockups and has React code behind it -- but then try and get this into even a demoable state for your boss or colleagues...
Even a simple "please create a docker file with everything I need in a directory to get this up and running"...doesn't work.
Docker file doesnt work (my fault maybe for not expressing I'm on Arm64), app is miss configured, files are in the wrong directories, key things are missing.
Again just my experience.
I find Claude interesting for generating ideas-- but I have a hard time seeing how a dev with six months experience could get multiple "paid" apps out with it. I have 20 years (bla, bla) experience and still find it requires outrageous hand holding for anything serious.
Again I'm not doubting you at all -- I'm just saying me personally I find it hard to be THAT productive with it.
You have to temper your ambitions. Choose languages it understands well. Deploy on vercel. Specify exactly what you’re working with (“I’m using nextjs 14 with app router”)
Agreed. LLMs can give you ideas on how to get there, but you still need foundational knowledge of the language or framework to extend the code it generates.
Claude is fantastic. I think the model itself is good enough to be able to write good software when competently directed; it's let down only by the UI/UX around it.
My only complaints are:
a) that it's really easy to hit the usage limit, especially when refactoring across a half dozen files. One thing that'd theoretically be easyish to fix would be automatically updating files in the project context (perhaps with an "accept"/"reject" prompt) so that the model knows what the latest version of your code is without having to reupload it constantly.
b) it oscillating between being lazy in really annoying ways (giving largeish code blocks with commented omissions partway through) and supplying the full file unnecessarily and using up your usage credits.
My hope is that Jetbrains give up on their own (pretty limited) LLM and partner with Anthropic to produce a super-tight IDE native integration.
I wanted to develop a simple tool to compare maps. I thought about using this opportunity to try out Claude AI for coding a project from scratch. It worked surprisingly well!
At least 95% of the code was generated by AI (I reached the limit so had to add final bits on my own).
POCs and demos are easy to build by anyone these days. The last 10% is what separates student projects from real products.
any engineer who has spent time in the trenches understands that fixing corner cases in code produced by inexperienced engineers consumes a lot of time.
in fact, poor overall design and lack of diligence tanks entire projects.
Interestingly, I’m pretty sure they mean they hit the limit with tokens on Claude.
There’s a daily 2.5 million token limit that you can use up fairly quickly with 100K context
So they may very well have completed the whole program with Claude. It’s just the machine literally stopped and the human had to do the final grunt work.
I asked Claude AI to make me an app and it refused and called it dangerous. I asked what kind of apps they could build and they suggested social media or health. So I asked it to make one but it refused too dangerous. I asked it to make anything.. anything app and it refused. I told it it sucked and it said it didn't. Then I deleted my account.
There have been rumors of the system prompt changing for some services if the user had strikes on their account from earlier conversations. I wonder if you were impacted by this because what you described has not been my experience nor have I seen it discussed previously.
I think we're going to see a similar backlash to AI apps as we did with AI art.
Not necessarily because users can identify AI apps, but more because due to the lower barrier of entry - the space is going to get hyper-competitive and it'll be VERY difficult to distinguish your app from the hundreds of nearly identical other ones.
Another thing that worries me (because software devs in particular seem to take a very loose moral approach to plagiarism and basic human decency) is that it'll be significantly easier for a less scrupulous dev to find an app that they like, and use an LLM to instantly spin up a copy of it.
I'm trying not to be all gloom and doom about GenAI, because it can be really nifty to see it generate a bunch of boilerplate (YAML configs, dev opsy stuff, etc.) but sometimes it's hard....
I hope not. I commend that software devs in particular seem to be adaptable to new technologies instead of trying to stop progress.
Take this very post for example. Imagine an artist forum having daily front-page articles on AI, and most of the comments are curious and non-negative. That's basically what HackerNews is doing, but with developers instead. The huge culture difference is curious, and makes me happy with the posters on this site.
You attribute it to the difficulty of using AI coding tools. But such tools to cut out the programmer and make it available to the layman has always existed: libraries, game engines, website builders, and now web app builders. You also attribute it to the flooding of the markets. But the website and mobile markets are famously saturated, and yet there we continue making stuff, because we want to (and because quality things make more money).
I instead attribute it to our culture of free sharing (what one might call "plagiarism"... of ideas?!), adaptability, and curiosity. And that makes me hopeful.
No doubt about it, things will get very competitive in the software space and while anyone will be able to use generative AI tools, I think more will be expected for less.
> I am looking forward to this type of real time app creation being added into our OSs, browsers, phones and glasses.
What do you see that being used for?
Surely, polished apps written for others are going to be best built in professional tools that live independently of whatever the OS might offer.
So I assume you're talking about quick little scratch apps for personal use? Like an AI-enriched version of Apple's Automator or Shortcuts, or of shell scripts, where you spend a while coahcing an AI to write the little one-off program you need instead of visually building a worrkflow or writing a simple script? Is that something you believe there's a high unmet need for?
This is an earnest question. I'm sincerely curious what you're envisioning and how it might supercede the rich variety of existing tools that seem to only see niche use today.
When I was in college (10+ years ago) there was a system that allowed you to select your classes. During the selection period, certain people had priority (people a year above you got to select first).
Once a class was full, you could still get in if someone who was selected for the classes changed their mind, which (at an unpredictable time) would result in a seat becoming available in that class until another student noticed the availability and signed up.
So I wrote a simple PHP script that loaded the page every 60 seconds checking, and the script would send me a text message if any of the classes I wanted suddenly had an opening. I would then run to a computer and try to sign up.
These are the kind of bespoke, single-purpose things that I presume AI coding could help the average person with.
“Send me a push notification when the text on this webpage says the class isn’t full, and check every 60 seconds”
There's no shortage of applications, both desktop and mobile, that never really stray outside of the default toolkits. Line of business apps, for instance, don't need the polish that apps targeting consumers need. They just need to effectively manipulate data.
Yeah I was talking about small apps/services for personal use rather than professional applications built to serve a business need.
Two ideas: "For every picture of food I take, create a recipe to recreate it so I can make it at home in the future" or "Create an app where I can log my food for today and automatically calculate the calories based on the food I put in".
Why multi-pass? So multiple semantic errors can be reported at once to the user!
The most important factor here is that I've written lexers and parsers beforehand. I was very detailed in my instructions and put it together piece-by-piece. It took probably 100 or so different chats.
Try it out with the GUI you see in the gif in the README:
git clone git@github.com:williamcotton/search-input-query.git
cd search-input-query/search-input-query-demo
npm install
npm run dev
Readit News
The first prompt (with o1) will get you 60% there, but then you have a different workflow. The prompts can get to a local minimum, where claude/gpt4/etc.. just can't do any better. At which point you need to climb back out and try a different approach.
I recommend git branches to keep track of this. Keep a good working copy in main, and anytime you want to add a feature, make a branch. If you get it almost there, make another branch in case it goes sideways. The biggest issue with developing like this is that you are not a coder anymore; you are a puppet master of a very smart and sometimes totally confused brain.
This is one fact that people seem to severely under-appreciate about LLMs.
They're significantly worse at coding in many aspects than even a moderately skilled and motivated intern, but for my hobby projects, until now I haven't had any intern that would even as much as taking a stab at some of the repetitive or just not very interesting subtasks, let alone stick with them over and over again without getting tired of it.
In my experience of these tools, including the flagship models discussed here, this is a deal-breaking problem. If I have to waste time re-prompting to make progress, and reviewing and fixing the generated code, it would be much faster if I wrote the code from scratch myself. The tricky thing is that unless you read and understand the generated code, you really have no idea whether you're progressing or regressing. You can ask the model to generate tests for you as well, but how can you be sure they're written correctly, or covering the right scenarios?
More power to you if you feel like you're being productive, but the difficult things in software development always come in later stages of the project[1]. The devil is always in the details, and modern AI tools are just incapable of getting us across that last 10%. I'm not trying to downplay their usefulness, or imply that they will never get better. I think current models do a reasonably good job of summarizing documentation and producing small snippets of example code I can reuse, but I wouldn't trust them for anything beyond that.
[1]: https://en.wikipedia.org/wiki/Ninety%E2%80%93ninety_rule
If software engineering should look like this, oh boy am I happy to be retiring in mere 17 years (fingers crossed) and not having to spend more time in such work. No way any quality complex code can come up from such approach, and people complain about quality of software now .
So you're basically bruteforcing development, a famously efficient technique for... anything.
site:github.com map comparison
I guess the difference, is that my way uses dramatically less time and resources, but requires directly acknowledging the original coders instead of relying on the plagiarism-ish capabilities of reguritating something through an LLM.
Or
Can you come up easily with many things that LLMs have no clue of and hence will fail?
I’ve been using Sonnet 3.5 to code and I’ve managed to build multiple full fledged apps, including paid ones
Maybe they’re not perfect, but they work and I’ve had no complaints yet. They might not scale to become the next Facebook, but not everything has to scale
Going to some new place meant getting a map, looking at it, making a plan, following the plan, keeping track on the map, that sort of thing.
Then I traveled somewhere new, for the first time, with GPS and a navigation sofware. It was quite impressive, and rather easier. I got to my destination the first time, without any problems. And each time after that.
But I did remark that I did not learn the route. The 10th time, the 50th time, I still needed the GPS to guide me. And without it, I would have to start the whole thing from scratch: get a map, make a plan, and so on.
Having done the "manual" navigation with maps lots of times before, it never worries me what I would do without a GPS. But if you're "born" with the GPS, I wonder what you do when it fails.
Are you not worried how you would manage your apps if for some reason the AIs were unavailable?
If anyone else is frustrated by this experience, I've found that changing the setting in Google Maps to have the map always point north has helped me with actually building a mental model of directions. I found instead of just following the line, it forced me to think about whether I'm going north, south, east, or west for each directions.
Make hay while the sun shines, friends. It might not last forever, but neither will you!
I never worried about what would happen if internet were to become unavailable. Given that it’s become one an essential service I just trust that powers that be will make sure to get it back up.
Prior to an iPhone I’d have the general lay of a city memorised within 10min of landing, using a paper tourist map, and probably never feel disoriented, let alone lost.
This morning I walked 2 blocks further than needed (of a 1 block walk) because I wasn’t at all oriented while following Google maps.
I won’t spell out the AI comparison, other than I think more “apps” will be created, and predictable “followed the GPS off a bridge” revelations.
Python/JS and their ecosystem replacing OS hosted C/C++ which replaced bare metal Assembly which replaced digital logic which replaced analog circuits which replaced mechanical design as the “standard goto tool” for how to create programs.
Starting with punchcard looms and Ada Lovelace maybe.
In every case we trade resource efficiency and lower level understanding for developer velocity and raise the upper bound on system complexity, capability, and somehow performance (despite the wasted efficiency).
>I played around a lot with code when I was younger. I built my first site when I was 13 and had a good handle on Javascript back when jQuery was still a pipe dream.
>Started with the Codecademy Ruby track which was pretty easy. Working through RailsTutorial right now.
posted on April 15, 2015, https://news.ycombinator.com/item?id=9382537
>I've been freelancing since I was 17. I've dabbled in every kind of online trade imaginable, from domain names to crypto. I've built and sold multiple websites. I also built and sold a small agency.
>I can do some marketing, some coding, some design, some sales, but I'm not particularly good at any of those in isolation.
posted on Jan 20, 2023, https://news.ycombinator.com/item?id=34459482
So I don't really understand where this claim of only "6 months of coding experience" is coming from, when you clearly have been coding on and off for multiple decades.
Find a way to work around it.
Everybody ships nasty bugs in production that he himself might find impossible to debug, everybody.
Thus he will do the very same thing me, you or anybody else on this planet do, find a second pair of eyes, virtually or not, paying or not.
Do you think you could you maintain and/or debug someone else's application?
Most of the things I’ve built are fun things
See: GoUnfaked.com and PlaybookFM.com as examples
PlaybookFM.com is interesting because everything from the code to the podcasts to the logo are AI generated
It's a slightly orthogonal way of thinking about this but if you are solving real problems, you get away with so much shit, it's unreal.
Maybe Google is not gonna let you code monkey on their monorepo, but you do not have to care. There's enough not-google in the world, and enough real problems.
In fact, my main reason for not doing any web development is that I find the amount of layers of abstraction and needless complexity for something that should really be simple quite deterring.
I'm sure e.g. React and GraphQL allow people to think about web apps in really elegant and scalable ways, but the learning curve is just way more than I can justify for a side project or a one-off thing at work that will never have more than two or three users opening it once every few months.
The browser is a great place to build voice chat, 3d, almost any other experience. I expect a renewed interest in granting fuller capabilities to the web, especially background processing and network access.
How about we go back to thick clients, with LLMs the effort required to do that for multiple operating systems will also be reduced, no?
MetHacker.io (has a lot of features I had to remove because of X API’s new pricing - see /projects on it)
GoUnfaked.com
PlaybookFM.com
TokenAI.dev (working with blowfish to remove the warning flag)
Maybe I'm "holding it wrong" -- I mean using it incorrectly.
True it renders quite interesting mockups and has React code behind it -- but then try and get this into even a demoable state for your boss or colleagues...
Even a simple "please create a docker file with everything I need in a directory to get this up and running"...doesn't work.
Docker file doesnt work (my fault maybe for not expressing I'm on Arm64), app is miss configured, files are in the wrong directories, key things are missing.
Again just my experience.
I find Claude interesting for generating ideas-- but I have a hard time seeing how a dev with six months experience could get multiple "paid" apps out with it. I have 20 years (bla, bla) experience and still find it requires outrageous hand holding for anything serious.
Again I'm not doubting you at all -- I'm just saying me personally I find it hard to be THAT productive with it.
My only complaints are:
a) that it's really easy to hit the usage limit, especially when refactoring across a half dozen files. One thing that'd theoretically be easyish to fix would be automatically updating files in the project context (perhaps with an "accept"/"reject" prompt) so that the model knows what the latest version of your code is without having to reupload it constantly.
b) it oscillating between being lazy in really annoying ways (giving largeish code blocks with commented omissions partway through) and supplying the full file unnecessarily and using up your usage credits.
My hope is that Jetbrains give up on their own (pretty limited) LLM and partner with Anthropic to produce a super-tight IDE native integration.
At least 95% of the code was generated by AI (I reached the limit so had to add final bits on my own).
POCs and demos are easy to build by anyone these days. The last 10% is what separates student projects from real products.
any engineer who has spent time in the trenches understands that fixing corner cases in code produced by inexperienced engineers consumes a lot of time.
in fact, poor overall design and lack of diligence tanks entire projects.
There’s a daily 2.5 million token limit that you can use up fairly quickly with 100K context
So they may very well have completed the whole program with Claude. It’s just the machine literally stopped and the human had to do the final grunt work.
What stops you from using AI to explain the code base?
Deleted Comment
I can't think of a worse llm than Claude.
Not necessarily because users can identify AI apps, but more because due to the lower barrier of entry - the space is going to get hyper-competitive and it'll be VERY difficult to distinguish your app from the hundreds of nearly identical other ones.
Another thing that worries me (because software devs in particular seem to take a very loose moral approach to plagiarism and basic human decency) is that it'll be significantly easier for a less scrupulous dev to find an app that they like, and use an LLM to instantly spin up a copy of it.
I'm trying not to be all gloom and doom about GenAI, because it can be really nifty to see it generate a bunch of boilerplate (YAML configs, dev opsy stuff, etc.) but sometimes it's hard....
Take this very post for example. Imagine an artist forum having daily front-page articles on AI, and most of the comments are curious and non-negative. That's basically what HackerNews is doing, but with developers instead. The huge culture difference is curious, and makes me happy with the posters on this site.
You attribute it to the difficulty of using AI coding tools. But such tools to cut out the programmer and make it available to the layman has always existed: libraries, game engines, website builders, and now web app builders. You also attribute it to the flooding of the markets. But the website and mobile markets are famously saturated, and yet there we continue making stuff, because we want to (and because quality things make more money).
I instead attribute it to our culture of free sharing (what one might call "plagiarism"... of ideas?!), adaptability, and curiosity. And that makes me hopeful.
People don't seem to realize that the same thing is going to happen to regular app development once AI tooling gets even easier.
I am looking forward to this type of real time app creation being added into our OSs, browsers, phones and glasses.
What do you see that being used for?
Surely, polished apps written for others are going to be best built in professional tools that live independently of whatever the OS might offer.
So I assume you're talking about quick little scratch apps for personal use? Like an AI-enriched version of Apple's Automator or Shortcuts, or of shell scripts, where you spend a while coahcing an AI to write the little one-off program you need instead of visually building a worrkflow or writing a simple script? Is that something you believe there's a high unmet need for?
This is an earnest question. I'm sincerely curious what you're envisioning and how it might supercede the rich variety of existing tools that seem to only see niche use today.
Once a class was full, you could still get in if someone who was selected for the classes changed their mind, which (at an unpredictable time) would result in a seat becoming available in that class until another student noticed the availability and signed up.
So I wrote a simple PHP script that loaded the page every 60 seconds checking, and the script would send me a text message if any of the classes I wanted suddenly had an opening. I would then run to a computer and try to sign up.
These are the kind of bespoke, single-purpose things that I presume AI coding could help the average person with.
“Send me a push notification when the text on this webpage says the class isn’t full, and check every 60 seconds”
Ask a bird what flying is good for and their answer will be encumbered by reality.
Kind of the opposite of “everything looks like a nail”.
Two ideas: "For every picture of food I take, create a recipe to recreate it so I can make it at home in the future" or "Create an app where I can log my food for today and automatically calculate the calories based on the food I put in".
https://github.com/williamcotton/search-input-query
Why multi-pass? So multiple semantic errors can be reported at once to the user!
The most important factor here is that I've written lexers and parsers beforehand. I was very detailed in my instructions and put it together piece-by-piece. It took probably 100 or so different chats.
Try it out with the GUI you see in the gif in the README: