Describing what they want in plain, human language is impossible for stakeholders.
'I want you to make me a Facebook-killer app with agentive AI and blockchains. Why is that so hard for you code monkeys to understand?'
Even writing an RFC for a mildly complicated feature to mostly describe it takes so many words and communication with stakeholders that it can be a full time job. Imagine an entire app.
You want the answer to the ultimate question of life, the universe, and everything? Ok np
Doesn’t matter if they can replace coders. If CEOs think it can, it will.
And now, it’s good enough to look like it works so the CEO can just push the problem down the road and get an instant stock inflation
And then it'll all go to shit and proper programmers will be able to charge bank to sort it out.
I hope it works like that.
I hope all those companies go bankrupt, people hiring those CEOs lose everything, and the CEOs never manage to find another job in their lives...
But that's a not bad second option.
They’ll end up being exploited
Well, have you seen what game engines have done to us?
When tools become more accessible, it mostly results in more garbage.
I'm guessing 4 out of 5 of your favorite games have been made with either unity or unreal. What an absolutely shit take.
LLMs often fail at the simplest tasks. Just this week I had it fail multiple times where the solution ended up being incredibly simple and yet it couldn’t figure it out. LLMs also seem to „think“ any problem can be solved with more code, thereby making the project much harder to maintain.
LLMs won’t replace programmers anytime soon but I can see sketchy companies taking programming projects by scamming their clients through selling them work generated by LLMs. I‘ve heard multiple accounts of this already happening and similar things happened with no code solutions before.
Your anecdote is not helpful without seeing the inputs, prompts and outputs. What you're describing sounds like not using the correct model, providing good context or tools with a reasoning model that can intelligently populate context for you.
My own anecdotes:
In two years we have gone from copy/pasting 50-100 line patches out of ChatGPT, to having agent enabled IDEs help me greenfield full stack projects, or maintain existing ones.
Our product delivery has been accelerated while delivering the same quality standards verified by our internal best practices we've our codified with determistic checks in CI pipelines.
The power come from planning correctly. We're in the realm of context engineering now, and learning to leverage the right models with the right tools in the right workflow.
Most novice users have the misconception that you can tell it to "bake a cake" and get the cake ypu had in your mind. The reality is that baking a cake can be broken down into a recipe with steps that can be validated. You as the human-in-the-loop can guide it to bake your vision, or design your agent in such a way that it can infer more information about the cake you desire.
I don't place a power drill on the table and say "build a shelf," expecting it to happen, but marketing of AI has people believing they can.
Instead, you give an intern a power drill with a step-by-step plan with all the components and on-the-job training available on demand.
If you're already good at the SDLC, you are rewarded. Some programmers aren't good a project management, and will find this transition difficult.
You won't lose your job to AI, but you will lose your job to the human using AI correctly. This isn't speculation either, we're also seeing workforce reduction supplemented by Senior Developers leveraging AI.
Early 80s: High level structured languages (Hello COBOL!)
Late 80s: 4th generation languages
At least before that people just assumed everybody that interacted with a computer was a programmer, so managers didn't have a compulsion when hearing the name and decided to fire all programmers.
I barely use AI for work but I gotta say that it's the first time I can get some very specific tasks done faster.
I currently make it write code generators, I fix the up and after that I have something better at making boilerplate than these LLMs. Today I had to throw up a bunch of CRUD for a small webapp and it saved me around 1-2 hours.
That's a great methodology for a new adopter.
Curious if you read about it, or did it out of mistrust for the AI?
help me. I am stuck working in SDET and my job makes me do a cert every 6 months that's "no code" and I need to transition to writing code.
I've been SDET since 2013, in c# and java. I am so fucking sick of selenium and getting manual testing dumped on my lap. I led a test team for a fortune 500 company as a contractor for a project. I can also program in the useless salesforce stack (apex, LWC).
I am the sole breadwinner for my household. I have no fucking idea what to do.
If you're not already messing with mcp tools that do browser orchestration, you might want to investigate that.
I don't want to make any assumptions about additional tooling, but this is a great one in this space https://www.agentql.com/
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