Assume the business logic and all edge cases work in the legacy app. The app is "done", just too old to work on or run on modern hosts. Hence the project.
Would/could you use AI to deliver the project at 10x the speed? Or at 1/10 the price? Or charge the same amount as ever?
I have a feeling the lowest-cost developers on freelance marketplaces are not very good at using the AI tools (and whatever related acumen) and need a lot of hand-holding, the same amount of effort almost as if I decided to guide AI to do it myself.
IMO, there's value you can sell in being someone that (even developers) can hand off a project to, to do end to end, if it's fully specified. Even though the buyer could do it themselves, the developer is are taking on managing it and having AI do it until it's correct, and all the little things, few as they may be.
AI should be giving contract developers superpowers. If it's not, then the limited set of contractors with the AI superpowers will be able to charge 10x as much for their time, and the actual cost of the project remains the same even if it's done 10x as fast/easily.
Curious if you see/feel this, or if there's a marketplace for "please vibe code this for me, make sure it works and is what I want".
If you search for LLM benchmarks focused on real-world tasks, you'll quickly learn this ain't the case. No point in telling business owners about that though, they need to see/learn by themselves.
The cleanup pay is mighty generous as well.
Still no Artificial Analysis benchmark yet. Or benchmark for Laguna S 2.1 or Meituan models or lots of other models.
On a sneaky one that involved parsing MIME headers and dealing with character encodings it did better than Kimi K3 at Max and for 38% lower cost.
Interestingly it seems noticeably better than the qwen3.8-max-preview model they offered just a few weeks ago.
I see people, and my self making amazing things with AI and fixing old projects and having real world impact at the fraction of the cost it would take me to hire people, or hours spent on my own coding.
I have built tools and systems with AI that have allowed me to build windows drivers, android apps, web apps, iOS apps, vm occultation, custom block drivers, custom file systems and more. To the point where entire products have been created.
Not trying to be a doomsday, but yes. It seems as though with the right infrastructure we are at the point where businesses owners can go from idea to product very fast and not need or hire much external talent.
It allows us to apply custom ACLs to AI agents and the child process spawned by AI agents. Giving us the ability to control what files an AI agent can read or write to, while still being in the calling users context. It allows us to force all ai derived processes to use a transparent MITM proxy so we can then also apply robust access rules to remote host allow or deny access to specific urls and not others. It also allows us to monitor access to windows Credential Manager with rules ti allow specific singed binaries to access some credentials but not others. It give us complete control of what AI agents on windows can see or not see or access.
Windows native sandboxing is lacking. You have some stuff in WSL that completely are broken once you call a windows native app. Or you have app containers which are too restrictive and result in applying expensive file system ACL to all files the app containers would access, which can take hours when dealing with million of files, and would be required to be applied every time you chains your app container (there are some workarounds, for them but they still have a one time cost a long with a fairly flaky maintenance process). You can get the network part done by running commands as a different user but that would result in the same file system ACL nightmare that app containers has.
Result is we get seatbelt level sandboxing in windows native, and can apply dynamic rules like preventing access to .aws folders regardless of the OS level ACLs, using glob rules like */.aws, so we don’t have to be aware of the exact path ahead of time.
It also has registry tree ACLs and, can prevent process and process trees from gaining administrative access, the list of features goes on and on.
It might please you to know that this driver was vibe coded from a linux vm based sandbox.(that was also vibe coded)
I don't know why but this made me laugh out loud. I know you're trying to help but just a funny jump
I think the volume for custom agents is probably higher than ever but so is the competition for that work.
PS. Not everyone (in fact the rare few) write as if no one is reading. For most, literally no one ever reads :D
You need to run away from any client who thinks your primary purpose is to write code. You must run away from the business if YOU think your primary purpose is to write code.
You should be able to write code and do it well, But the AIs, and I'm not even talking about the ones on the frontier, have been able to write code faster than I have for quite some time.
What you need to explain to your customers is all the things around writing code: software architecture, performance, and so on. Also make sure you have some understanding of the customers business, so you can suggest additional ways to make their lives better/make more money.
Software developers have a chance. Code monkeys? None.
guess one which is valuable ?
First, I am aware they have been able to write code for some time. I made my first LLM coding agent experiment the day after ChatGPT first blew up in November 2022.
I haven't been a "code monkey" in the last say 15 or 20 years of my programming. I would argue also that code money was never really a thing, it was just an excuse that pretentious overpaid developers used for the existence of underpaid exploited programmers. 95% of programmers have to do requirements analysis and design regardless of their pay grade. I learned a long time ago how important requirements analysis and good design is. And the jobs I am applying to largely specify architecture and requirements analysis in the description. Employers are aware of code generation tools.
But also, the premise that writing the code is not the hard part is just nonsense. Sure requirements analysis is harder than people realize, good design is hard and so is understanding things about proper and closed iteration. But that stuff is not, in the aggregate, harder than the code.
And also, frontier models can absolutely do requirements analysis and architecture. And the sheer speed of implementation means that there is a huge built-in advantage for iterating more effectively.
"Code monkey" absolutely was and still is a thing. I was hired by Big Name Co originally to be staff but a reorg had me do typical senior position duties for around a year, and it was hell. Every decision was made over our heads, feedback was unwelcome because the feature had already gone through design and gotten layers of sign-offs from different areas of the org, etc. My sole purpose was to write code and review peer code. Staying there a full year was way too much.
Second point, requirements analysis is hard because:
* Different stakeholders have conflicting goals, sometimes mutually exclusive * Some stakeholders have ideas that are actively harmful to users, and you must flex political capital to nip it in the bud * Some stakeholders think they know what they want with a far greater degree of clarity than they actually do, and lack the time to sit down and suss out the nuances, because you're a side-show in the grander scheme of their own priorities.
Writing code is a heck of a lot easier than dealing with people at the edges.
AI will help you draft the communication of that knowledge, but it won't help you actually deliver the knowledge or ensure that the knowledge was appropriately received. As you say, it is a fundamentally human problem, which is why I maintain that writing code is easier.
but then you totally jumped the shark!
My MindRoot framework had some of qm's main features awhile ago though. I do try to use it to build solutions by customizing rather than from scratch when possible. But a lot of clients or potential clients don't like that idea even though it's MIT. They want some that has clearly been invented by them as a new programming project.
I actually turned down a project last year from someone who wanted me to start over in LangGraph -- he had already decided on it before he knew about my thing.
The most recent project I have been using MindRoot and building up the voice capabilities so I can now handle voice agents end to end including SIP.
But on that website now I try not to emphasize my framework at all for most proposals. You don't have leverage on Upwork. And also with code generation it isn't a critical point necessarily.