Post funny things about programming here! (Or just rant about your favourite programming language.)
Ha, you fools still pay for doors and locks? My house is now 100% done with fake locks and doors, they are so much lighter and easier to install.
Wait! why am I always getting robbed lately, it can not be my fake locks and doors! It has to be weirdos online following what I do.
Hilarious and true.
last week some new up and coming coder was showing me their tons and tons of sites made with the help of chatGPT. They all look great on the front end. So I tried to use one. Error. Tried to use another. Error. Mentioned the errors and they brushed it off. I am 99% sure they do not have the coding experience to fix the errors. I politely disconnected from them at that point.
What's worse is when a noncoder asks me, a coder, to look over and fix their ai generated code. My response is "no, but if you set aside an hour I will teach you how HTML works so you can fix it yourself." Never has one of these kids asking ai to code things accepted which, to me, means they aren't worth my time. Don't let them use you like that. You aren't another tool they can combine with ai to generate things correctly without having to learn things themselves.
100% this. I've gotten to where when people try and rope me into their new million dollar app idea I tell them that there are fantastic resources online to teach yourself to do everything they need. I offer to help them find those resources and even help when they get stuck. I've probably done this dozens of times by now. No bites yet. All those millions wasted...
This is satire / trolling for sure.
LLMs aren't really at the point where they can spit out an entire program, including handling deployment, environments, etc. without human intervention.
If this person is 'not technical' they wouldn't have been able to successfully deploy and interconnect all of the pieces needed.
The AI may have been able to spit out snippets, and those snippets may be very useful, but where it stands, it's just not going to be able to, with no human supervision/overrides, write the software, stand up the DB, and deploy all of the services needed. With human guidance sure, but with out someone holding the AIs hand it just won't happen (remember this person is 'not technical')
It's further than you think. I spoke to someone today about and he told me it produced a basic SaaS app for him. He said that it looked surprisingly okay and the basic functionalities actually worked too. He did note that it kept using deprecated code, consistently made a few basic mistakes despite being told how to avoid it, and failed to produce nontrivial functionalies.
He did say that it used very common libraries and we hypothesized that it functioned well because a lot of relevant code could be found on GitHub and that it might function significantly worse when encountering less popular frameworks.
Still it's quite impressive, although not surprising considering it was a matter of time before people would start to feed the feedback of an IDE back into it.
We just built and deployed a fully functional AWS app for our team entirely written in AI. From the terraform, to the backing API, to the frontend Angular. All AI. I think AI is further along here than you suspect.
idk ive seen some crazy complicated stuff woven together by people who cant code. I've got a friend who has no job and is trying to make a living off coding while, for 15+ years being totally unable to learn coding. Some of the things they make are surprisingly complex. Tho also, and the person mentioned here may do similarly, they don't ONLY use ai. They use Github alot too. They make nearly nothing themself, but go thru github and basically combine large chunks of code others have made with ai generated code. Somehow they do it well enough to have done things with servers, cryptocurrency, etc... all the while not knowing any coding language.
Might be satire, but I think some "products based on LLMs" (not LLMs alone) would be able to. There's pretty impressive demos out there, but honestly haven't tried them myself.
An otherwise meh article concluded with "It is in everyone’s interest to gradually adjust to the notion that technology can now perform tasks once thought to require years of specialized education and experience."
Much as we want to point and laugh - this is not some loon's fantasy. This is happening. Some dingus told spicy autocomplete 'make me a database!' and it did. It's surely as exploit-hardened as a wet paper towel, but it functions. Largely as a demonstration of Kernighan's law.
This tech is borderline miraculous, even if it's primarily celebrated by the dumbest motherfuckers alive. The generation and the debugging will inevitably improve to where the machine is only as bad at this as we are. We will be left with the hard problem of deciding what the software is supposed to do.
This industry also spends most of it's money either changing things that don't need to change (we optimized the right click menu to remove this item, mostly to fuck your muscle memory) or to avoid changing things (rather than implementing 2fa, banks have implemented 58372658 distinct algorithms for detecting things that might be fraud).
If you're just talking about enabling small scale innovation you're probably right, but if you're talking about the industry as a whole I think you need to look at what people in industry are actually spending their time on.
it's not code.
Yeah, I've been using it heavily. While someone without technical knowledge will surely allow AI to build a highly insecure app, people with more technological knowledge are going to propel things to a level where the less tech savvy will have fewer and fewer pitfalls to fall into.
For the past two months, I've been leveraging AI to build a CUE system that takes a user desire (e.g. "i want to deploy a system with an app that uses a database and a message queue" expressed as a short json) and converts a simple configuration file that unpacks into all the kubernetes manifests required to deploy the system they want to deploy.
I'm trying to be fully shift-left about it. So, even if the user's configuration is as simple as my example, it should still use CUE templating to construct the files needed for a full DevSecOps stack - Ingress Controller, KEDA, some kind of logging such as ELK stack, vulnerability scanners, policy agents, etc. The idea is the every stack should at all times be created in a secure state. And extra CUE transformations ensure that you can split the deployment destinations in any type of way, local/onprem, any cloud provider, or any combination thereof.
The idea is that if I need to swap out a component, I just change one override in the config and the incoming component already knows how to connect to everything and do what the previous component was doing because I've already abstracted the component's expected manifest fields using CUE. So, I'd be able to do something like changing my deployment from one cloud to another with a click of a button. Or build up a whole new fully secure stack for a custom purpose within a few minutes.
The idea is I could use this system to launch my own social media app, since I've been planning the ideal UX for many years. But whether or not that pans out, I can take my CUE system and put a web interface over it to turn it into a mostly automated PaaS. I figure I could undercut most PaaS companies and charge just a few percentage points above cost (using OpenCost to track the expenses). If we get to the point where we have a ton of novices creating apps with AI, I might be in a lucrative position if I have a PaaS that can quickly scale and provide automated secure back ends.
Of course, I intend on open sourcing the CUE once it's developed enough to get things off the ground. I'd really love to make money from my creative ideas on a socialized media app that I create, am less excited about gatekeeping this kind of advancement.
Interested to know if anyone has done this type of project in the past. Definitely wouldn't have been able to move at nearly this speed without AI.
so, MASD(or MDE) then ?
I've never heard of this before, but you're right that it sounds very much like what I'm doing. Thank you! Definitely going to research this topic thoroughly now to make sure I'm not reinventing the wheel.
Based on the sections in that link, I wondered if the MASD project was more geared toward the software dev side or devops. I asked Google and got this AI response:
"MAD" (Modern Application Development) services, often used in the context of software development, encompass a broader approach that includes DevOps principles and tools, focusing on rapid innovation and cloud-native architectures, rather than solely on systems development.
So (if accurate), it sounds like all the modernized automation of CI/CD, IaC, and GitOps that I know and love are already engaging in MAD philosophy. And what I'm doing is really just providing the last puzzle piece to fully automate stack architecting. I'm guessing the reason it doesn't already exist is because a lot of the open source tools I'm relying on to do the heavy lifting inside kubernetes are themselves relatively new. So, hopefully this all means I'm not wasting my time lol
AFAICT MASD is an iteration on MDE which incorporates parts of MAD but not in a direct fashion.
Lots of acronyms there.
These types of systems do exist, they just aren't mainstream because there hasn't been a version of them that could be easily used for general development outside of the specific mid-level niches they are built in.
I think it's the goal, but I've not seen anything come close yet.
Admittedly I'm not an authority so it may just be me missing the important things.
Thanks for the info. When I searched MASD, it told me instead about MAD, so it's good to know how they're differentiated.
This whole idea comes from working in a shop where most of their DevSecOps practices were fantastic, but we were maintaining fleets of Helm charts (picture the same Helm override sent to lots of different places with slightly different configuration). The unique values for each deployment were buried "somewhere" in all of these very lengthy values.yaml override files. Basically had to did into thousands of lines of code whenever you didn't know off-hand how a deployment was configured.
I think when you're in the thick of a job, people tend to just do what gets the job done, even if it means you're going to have to do it again in two weeks. We want to automate, but it becomes a battle between custom-fitting and generalization. With the tradeoff being that generalization takes a lot of time and effort to do correctly.
So, I think plenty of places are "kind of" at this level where they might use CUE to generalize but tend to modify the CUE for each use case individually. But many DevOps teams I suspect aren't even using CUE, they're still modifying raw yaml. I think of yaml like plumbing. It's very important, but best not exposed for manual modification unless necessary. Mostly I just see CUE used to construct and deliver Helm/kubernetes on the cluster, in tools like KubeVela and Radius. This is great for overriding complex Helm manifests with a simple Application .yaml, but the missing niche I'm trying to fill is a tool that provides the connections between different tools and constrains the overall structure of a DevSecOps stack.
I'd imagine any company with a team who has solved this problem is keeping it proprietary since it represents a pretty big advantage at the moment. But I think it's just as likely that a project like this requires such a heavy lift before seeing any gain that most businesses simply aren't focusing on it.
He should be promoted to management! Specifically head of cyber security! They also love security by obscurity and knowing nothing about what they are doing!
CIO, Peregrine Took.
ELI5?
Guy who doesn't know how to write software uses GenAI to make software that he then puts up for sale, and brags about not knowing how to write software.
People buy his software and, intentionally or not, start poking holes in it by using it in ways neither he nor the GenAI anticipated. Guy panics because he has no clue how to fix it.
Man uses AI to make software. Man learns hard way that AI doesn't care about stuff like security.
Managers hoping genAI will cause the skill requirements (and paycheck demand) of developers to plummet:
Also managers when their workforce are filled with buffoons:
