Writing fairly standard typescript APIs and React code, Copilot is immensely helpful and almost always correct. It definitely hits a wall when I am working on something sufficiently esoteric. As does ChatGPT, etc.
It is incredible that you can replace 90% of upwork/fiverr/juniors(and many seniors for that matter) with a $20/mo tool for doing the most common work like api integrations and frontend work (both of which I find the most boring work outside the non programming like devops and, worse, fighting tools and versions because of useless updates).
> It definitely hits a wall when I am working on something sufficiently esoteric.
So do humans. Hiring humans to do that work well is hard and expensive, so it’s not strange that is harder for LLMs as well.
I am not sure that finding things LLMs are shite at makes them less productive for most things programmers are doing during the day, which is quite boring stuff. In my reality, which, before mid last year, had 100s of people (across clients I work with, not my company) doing integrations and frontend work, now fired most of these and focused more on optimising the pipeline for copilot, chatgpt and opus.
My friend who runs an outsourcing operation in India almost went out of business mid last year when he saw his EU clients cancelling all his contracts because his people could be replaced by openai; he pivoted by having his people use ai, do ai projects and becoming more (everyone already was that but it was more heavy on the coding) business analyst heavy. He fired no one and is doing better than before now, but he doesn’t hire ‘programmers’ anymore.
I’d love to know the specifics on the ppl hiring the consultants and the work output. In my experience you need someone with experience to chain together any genAI output, as well as validate that it’s even correct. It’s not like it magically does everything for you.
Correct, but that was also the point; all these ‘consultants’ are senior programmers. Nothing is magically done; they use the ai to do the work they were mostly doing before with more people/themselves without ai; now they just focus more on business side. Higher pay and harder to replace (for now).
My company does the same but in a niche; our specific tooling is easier to automate (which we did/are still doing) and we notice it is getting easier with the llms getting better. A year ago we still needed a human to evaluate even the basic scope of work, now llama3 + some tooling we built can automatically get us a locally generated report.
Ah, but those were not consultants or maybe you didn’t mean that. Most of these clients hired people to augment their in house EU teams so they don’t need to hire more programmers locally; after 6-12 months of using copilot/gpt they found out they now could do that work in house with only the in house people in the same time. So they let go of the outsourced team members. I see this happening everywhere. It’s mostly the people that do the ‘light’ work; crud, integrations, frontend, data cleaning that are getting removed; this is a massive portion work wise, but simple, repetitive and boring. Things like business logic, workflows, data science, ml, performance and devops are done in house or still outsourced.
