You're only allowed to believe LLMs are a kind of digital messiah or that they're complete hype garbage, when of course the answer is some point between.
There is obviously a lot of potential here, but there is also a lot of solution looking for a problem.
My current red flag is if an argument hinges on a trademark breathless frisson for the growth potential. Statements like "models are getting smarter every month" that hasn't been true for a year. If your excitement over AI is based not on what we can do today, but a presumed future expansion for which we have no evidence, that's silly.
But what they can do today is cool. We worked for a long time to get computers to understand natural language intent, and LLMs demonstrably solve this problem.
It's going to take much longer and more human(?) effort to apply DL/LLMs in worthy applications by adding constraints and human-injected workarounds to make them work with more useful and fewer unpleasant surprises.
This has happened before. From 2000-2004, this was the world. Companies were going out of business or cutting headcount to the bone, and the folks with 7+ years of experience were getting picked up (often at a discount). If you started your first job coding in 1999 and then got laid off half a year later, sucks for you.
2004 both Salesforce, Google, and Blackboard (they were big then!) IPO, and Facebook comes screaming onto the scene. Greenspan monetary policy had already made capital nearly free, and the 2008 financial crisis kicked us into 0% interest rate territory. It costs us nothing to invest in talent, so why not? If we invest in 100 startups, each with 100 employees at $150K salaries, and just two of those unicorn exit, we've made our money back, and it costs financiers nothing to wait.
2004 kicked off the simultaneous rise of "software as a service" and "social media," both of which were highly lucrative. But not only that - SaaS allowed traditional (think General Mills or Procter and Gamble) to have high-quality, cutting-edge software products without needing to employ a lot of engineers to run them. They could just pay a line item to Salesforce and let them concentrate the devs.
Just like in 2004, I think we will have a major industry shift that unlocks jobs for lots of these junior folks. I don't think it will be AI - just feels too obvious. I suspect it'll be something to do with climate change.
It’s a fight to the bottom until we see the gaps. Senior associates think they can replace junior associates, managers think they can replace seniors, partners think they can replace managers and so on. My expectation, however inconvenient for me, is that juniors will be safe, mid levels will suffer as their subject matter will rebalance, seniors will collect the profit. Juniors will suffer longer term on a path with more selective progression.
As a senior I'm really not feeling any FOMO here. If the tools are going to get better and better, is there any need to be an early adopter, or build expertise in using them?
And who (without equity or significant direct incentives), in their right mind, would work on, invent, or deploy an automation tool that would make themselves and/or millions of others redundant? Some may say "productivity" assistant, but then it's not much of a hop to layoffs and reduced salaries.
The format of the article is creative and I don’t like it. The use of movies seems to be trying to channel a16z with movies instead of hip hop quotes and it isn’t working.
I stopped reading midway through because I realized I was more focused on (unsuccessfully) trying to figure out how the movies connected with the sections following them than on the actual article.
That's what's great about a16z's blog and what's bad about these movies. They don't connect in a fun or thoughtful way, that I can decipher. If they did, I might like it.
For me, the sweet spot is simple but time consuming tasks where the execution is very clear, or the result is very clear but I have to first read a ton of d3.js docs before implementing it. This stuff LLMs do faster than me typing it. Anything more involved where I myself don't know the final result yet, it's faster to figure out the problem while coding instead of trying to figure it out by describing to an LLM.
LLMs can often stitch together information from blogs and stack overflow like sites. You can view it as a better way to search and find answers to your development roadblocks, instead of something that writes code for you. This is where I get value worth paying for, by saving me time of having to navigate multiple search results and piece things together. Many times it is a mix of the two and the LLM, as a starting point, gives me better leads
Readit News
Five years later: Why can’t I find any senior developers? Shocked pikachu face.
There is obviously a lot of potential here, but there is also a lot of solution looking for a problem.
My current red flag is if an argument hinges on a trademark breathless frisson for the growth potential. Statements like "models are getting smarter every month" that hasn't been true for a year. If your excitement over AI is based not on what we can do today, but a presumed future expansion for which we have no evidence, that's silly.
But what they can do today is cool. We worked for a long time to get computers to understand natural language intent, and LLMs demonstrably solve this problem.
2004 both Salesforce, Google, and Blackboard (they were big then!) IPO, and Facebook comes screaming onto the scene. Greenspan monetary policy had already made capital nearly free, and the 2008 financial crisis kicked us into 0% interest rate territory. It costs us nothing to invest in talent, so why not? If we invest in 100 startups, each with 100 employees at $150K salaries, and just two of those unicorn exit, we've made our money back, and it costs financiers nothing to wait.
2004 kicked off the simultaneous rise of "software as a service" and "social media," both of which were highly lucrative. But not only that - SaaS allowed traditional (think General Mills or Procter and Gamble) to have high-quality, cutting-edge software products without needing to employ a lot of engineers to run them. They could just pay a line item to Salesforce and let them concentrate the devs.
Just like in 2004, I think we will have a major industry shift that unlocks jobs for lots of these junior folks. I don't think it will be AI - just feels too obvious. I suspect it'll be something to do with climate change.
Deleted Comment
But of course there are newer things to build, buy that is largely affected by 0% interest rate.
I have a genuine query. Are any software engineers getting sane code out of LLM ?
I struggle to conjure good unity or kotlin code from both paid and self hosted solutions.
For me, the sweet spot is simple but time consuming tasks where the execution is very clear, or the result is very clear but I have to first read a ton of d3.js docs before implementing it. This stuff LLMs do faster than me typing it. Anything more involved where I myself don't know the final result yet, it's faster to figure out the problem while coding instead of trying to figure it out by describing to an LLM.
[0] https://wakatime.com/blog/58-chatgpt-prototyped-our-new-feat...
I could never imagine copy-pasting back and forth with an AI in a chat window. At that point I'd just Google the docs and write the code myself.