However, I think what a lot of people don't realize is the reason a lot of executives and business users are excited about AI and don't mind developers getting replaced is because product is already a black box.
I'm more and more convinced top execs are most likely to be advantageously replaced by LLM.
They navigate such complex decision spaces, full of compromises, tensions, political knots, that ultimately their important decisions are just made on gut feelings.
Replace the CEO with an LLM whose system prompt is carefully crafted and vetted by the board of directors, with some adequate digital twin of the company to project it's move, I'm sure it should maximize the interest of the shareholders much better.
Next up: apply the same recipe to government executive power. Couldn't be much worse than orange man.
I've been doing the same. I don't mind SaaS subscription fees, but I often run into things where I need a niche feature that doesn't exist.
Incidentally, I ran into something like this with WhisperFlow last year. Used it for a few weeks, loved it, basically hardly typed for the month and just spoke to my system/terminal etc.
But, I ran into a unique challenge. Barking orders at my computed for 8 hours a day made me realize that I was changing how I communicated with people. Being nicer was easier to solve, but speech-to-text made me less articulate. I wasn't very articulate to begin with -- which is something that I have wanted to solve for a while.
So I built my own STT app, that works in a similar way as whisperflow, with a few notable exceptions. Minor: it has dictionaries, snippets etc on a per app/website basis. Major: most notably it has rubrics on how I want to communicate in different contexts, ex: Biz Exec over email, Principle engineer in my ide/terminal. etc
And scores me on areas like conciseness, flow, logical flow/ease to follow, clarity etc. every time I say anything. 10 weeks in I'm noticeably more articulate than I've ever been.
This feels like a far better reason to code your own; when your use case is just a bit too niche to ever be prioritized but you otherwise need a similar tool.
VAT is only levied if it doesn't get exported within a certain amount of time (6 months from the scheduled delivery date).
I knew someone who tooled around Europe for a month before dropping it off to be shipped to her without having VAT incurred (though it was a couple decades ago).
I'm building an ERP to encapsulate the whole "customer" journey. I'm building it to be a business operating system of sorts with a goal of creating clear line-of-sight visibility for all activities along journey's like lead-gen to churn (but in a variety of settings).
The goal is make it easier for organizations to work with external parties that affect finances (customers, investors, vendors, etc.).
The idea was born out of personal frustration that I've faced in a variety of leadership roles in organizations, that lead to wasted effort, slower decision making, bad decisions made with equally unhygienic data.
I've solved this successfully in the past form of internal tools and a data governance layer (data warehouse with much more authority).
My preferred language to build apps is Ruby, and I'm still more likely to pickup RoR as a backend. But I can't see if winning in the AI generation.
I never recommend it with LLMs, because there is a definite context window and attention problem with a lot of languages, but Type-safety + being pre-trained on strong typing, makes any issues with context sizes moot. The latest generation of AI dev tools, are getting really good at solving problems using the type errors that it creates.
Also a lot of Rails niceties can be achieved in languages like Typescript with patterns such as decorators, which do an amazing job DRYing things up and reducing those contexts.
This is a very good start, I don't think it'll replace a lot of the custom code/comboboxes that are seen in react-land without search (unless I missed it).
I for one am very excited about where things are going.
I know we're getting fewer "traditional" junior devs, but I'm seeing more and more designers and product managers contributing, at a frequency which was much harder pre-GPT.
In my roles as a head of product/eng, I've always encouraged non-technical team members to either learn coding or data to get better results, but always had limited success, as folks were scared of it (a) being hard, (b) taking too much time to get proficient.
But that's changing now, and fast - and these junior devs are becoming proficient much faster and leading to much business and customer outcomes.
I'm seeing more realistic goals, sprints, etc. I'm seeing fewer front/backend bottleneck, and lastly I'm seeing fewer pixel moving requests going to senior engineers.
As other have mentioned juniors were often unable to code prior to LLMs, and what helped make them better was code reviews, bugs and general mentorship. Those tools to make them better are still available to us.
However, I think what a lot of people don't realize is the reason a lot of executives and business users are excited about AI and don't mind developers getting replaced is because product is already a black box.
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