Humans are accountable to each other. Humans can be shamed in a code review and reprimanded and threatened with consequences for sloppy work. Most,
humans once reprimanded , will not make the same kind of mistake twice.
> Humans can be shamed in a code review and reprimanded and threatened with consequences for sloppy work.
I had to not merely threaten to involve the Ombudsman, but actually involve the Ombudsman.
That was after I had already escalated several times and gotten as far as raising it with the Data Protection Officer of their parent company.
> Most, humans once reprimanded , will not make the same kind of mistake twice.
To quote myself:
other people in their own team had already admitted this, apologised to me, promised they'd fixed it, while actually still continuing to send letters to the same non-existent address.
I used to be a big advocate for Salesforce in my organization. And it was really great .. allowing us to deliver new functionality without the usual IT procurement bureaucracy.
Now with cloud maturity and Vibe coders who will get better and cheaper, I think it's possible to replace all the features we use on Salesforce at a fraction of the cost of our Salesforce licensing cost.
Think of the LLM as a slightly lossy compression algorithm fed by various pattern classifiers that weight and bin inputs and outputs.
The user of the LLM provides a new input, which might or might not closely match the existing smudged together inputs to produce an output that's in the same general pattern as the outputs which would be expected among the training dataset.
Ignoring your last line, which is poorly defined, this view contradicts observable reality. It can’t explain an LLM’s ability to diagnose bugs in code it hasn’t seen before, exhibit a functional understanding of code it hasn’t seen before, explain what it’s seeing and doing to a human user, etc.
Functionally, on many suitably scoped tasks in areas like coding and mathematics, LLMs are already superintelligent relative to most humans - which may be part of why you’re having difficulty recognizing that.
I get your sentiment but a lot of people on this forum forget that a lot of us are just working for the paycheck - I don't owe my company anything.
Do I know the code base like the back of my hand? Nope. Can I confidently talk to how certain functions work? Not a chance.
Can I deploy what the business wants? Yep. Can I throw error logs into LLMs and work out the cause of issues? Mostly.
I get some of you may want to go above and beyond for your company and truly create something beautiful but then guess what - That codebase is theirs. They aren't your family. Get paid and move on
Gemini's large context window is incredible. I concatenate the my entire repo and repos of supporting libraries and then ask it questions.
My last use case was like this : I had a old codebase code that was using bakbone.js for ui with jquery and a bunch of old js with little documentation to generat UI for a clojure web application.
Gemini was able to unravel this hairball of code and guiding me step by step to htmx. I am not using AI studio; I am using Gemini subscription.
Since I manually patch the code, its like pair programming with an incredibly patient and smart programmer.
For the record, I am too old for vibe coding .. I like to maintain total control over my code and all the abstractions and logic.
I had Gemini ingest our huge aws cloudformation repo . I had it describe each infrastructure component and how it related to others and creation hierarchy and IAM.
I got a nice and comprehensive infrastructure requirement document out of this.
Now I am using it to create Terraform repo , deploying it via OpenTofu and comparing it to my existing AWS cloud formation . This part is still a WIP .
However, the cost of software maintenance went up by 1000% . Lets hope you don't need to ever add a new business rule or user interface to your vibe coded software.
I am curious : could GenAI have written the paper "Attention is all you need"? We were trapped in CNN RNN architectures for a while : could genAi have arrived at a better architecture ?
No, it couldn't have unless these ideas were sandwiched between other ideas that it could interpolate between.
You have to approach genai as a high-dimensional interpolation machine. It can perform extrapolation when you, the user, provide enough information to operate on. It can interpolate between what you provide and what it knows as well.
With these constraints, it is still pretty powerful, and I am generalizing of course. But in my experience, it is terrible at truly novel implementations of anything. It makes countless mistakes, because it continually attempts to fit to patterns found in existing code.
So you can really see the weaknesses at the frontier. I would encourage experimenting there to confirm what I am saying.
BS. I grew up in Delhi. We used to have a large open space where I and neighborhood kids used to play cricket . Eventually the whole area converted to slums with people from Bangladesh. They took over the whole area. I was too young to care about ethnicity but the loss of my cricket field still bothers me. My neighbor was a bank manager and he once said that the government politicians forced him to give "loans" to Bangladeshi people , with no documents and only their thumbprint,before elections to those people to ensure victory of the ruling party.
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