No, no, and no.
They thought they were faster too.
Yes, I know, AGI is just around the corner, we just need to wait more because "agents" are improving every day.
In the mean time, LLMs are kinda useful instead of web searches, mostly because search is both full of spam and the search providers are toxic.
I hear vague suggestions like "get better at the business domain" and other things like that. I'm not discounting any of that, but what does this actually mean or look like in your day-to-day life? I'm working at a mid-sized company right now. I use Cursor and some other tools, but I can't help but wonder if I'm still falling behind or doing something wrong.
Does anybody have any thoughts or suggestions on this? The landscape and horizon just seems so foggy to me right now.
I think it's about looking at what you're building and proactively suggesting/prototyping what else could be useful for the business. This does get tricky in large corps where things are often quite siloed, but can you think "one step ahead" of the product requirements and build that as well?
I think regardless if you build it, it's a good exercise to run on any project - what would you think to build next, and what does the business actually want. If you are getting closer on those requests in your head then I think it's a positive sign you are understanding the domain.
It would be helpful, as you suggest, to start shifting away from "I code based on concrete specs" to "I discover solutions for the business."
Thanks for the reply (and for the original essay). It has given me a lot to chew on.
Answers I see are typically "be a product manager" or "start your own business" which obviously 95% of developers can't/don't want to do.
Ultimately, software is for doing something, and that something can be a whole range of things. If you become really good at just a slice of that, things get a lot easier regardless of the general state of the industry.
1. Use the tools to their fullest extend, push boundaries and figure out what works and what doesn't
2. Be more than your tools
As long as you + LLM is significantly more valuable than just an LLM, you'll be employed. I don't know how "practical" this advice is, because it's basically what you're already doing, but it's how I'm thinking about it.
Maybe becoming full stack? Maybe understanding the industry a little deeper? Maybe analyzing your company's competitors better? That would increase your value for the business (a bit of overlap with product management though). Assuming you can now deliver the expected tech part more easily, that's what I'd do.
As for me, I've moved to a permanent product management position.
AI will probably replace the bottom ~30-70%(depends who you ask) of dev jobs. Dont get caught in the dead zone when the bottom falls out.
Exactly how we'll train good devs in the future, if we don't give them a financially stable environment environment to learn in while they're bad, is an open question.
My .02$. Show you can tackle harder problems. That includes knowing which problems matter. That happens with learning a "domain", versus just learning a tool (e.g. web development) in a domain.
Change is scary, but thats because most aren't willing to change. Part of the "scare" is the fear of lost investment (e.g. pick wrong major or career). I can appreciate that, but with a little flexibility, that investment can be repurposed quicker today that in pre-2022 thanks to AI.
AI is just another tool, treat it like a partner not a replacement. That can also include learning a domain. Ask AI how a given process works, its history, regulations, etc. Go confirm what it says. Have it break it down. We now can learn faster than ever before. Trust but verify.
You are using Cursor, that shows a willingness to try new things. Now try to move faster than before, go deeper into the challenges. That is always going to be valued.
Its a big bet to put your career on and right now IMV it isn't worth it; especially when I see a lot of money right now (trillions?) betting and investing in the opposite outcome. The high risk was rewarded in the past by high pay in certain locations but that's changing as well.
Ironically the "bullshit jobs" as they call them might be safe havens in the short term since they often exist due to corporate processes, regulation, etc and already don't provide much value so in turn aren't measured by that. Its no accident that I see the people most excited by AI were the people who delivered the least value in the delivery process previously from an anecdotal POV.
No one knows the future and many are in the same boat as you. Its not great news (not even for me) but that's where things are heading I think. Its definitely the loosely stated goal of AI labs, etc to democratize coding and probably most creative/intellectual work at that.
Opus 4.5 in particular has been a profound shift. I’m not sure how software dev as a career survives this. I have nearly 0 reason to hire a developer for my company because I just write a spec and Claude does it in one shot.
It’s honestly scary, and I hope my company doesn’t fail because as a developer I’m fucked. But… statistically my business will fail.
I think in a few years there will only be a handful of software companies—the ones who already have control of distribution. Products can be cloned in a few weeks now; not long until it’s a few minutes. I used to see a new competitor once every six months. Now I see a new competitor every few hours.
They wont automate everything, but the bar for being able to produce working software will plummet.
I've seen unbelievably complex logistics logic coded in... WordPress templates and plugins to take a random example. Actually virtually impossible to figure out - but AI can actually extract all the logic pretty well now.
edit: typos
It’s often hard to ground how “good” blog writers are, but tidbits like this make it easy to disregard the author’s opinions. I’ve worked in many codebases where the test writers share the authors sentiment. They are awful and the tests are at best useless and often harmful.
Getting to this point in your career without understanding how to write effective tests is a major red flag.
Stuff like reimplementing large amounts of the code inside the tests because testing the actual code is "too hard", spending inordinate amounts of time covering every single edge case on some tiny bit of input processing unrelated to the main business logic, mocking out the code under test, changing failing tests to match obviously incorrect behavior... basically all the mistakes you expect to see totally green devs who don't understand the purpose of tests making.
It saves a shitload of time setting up all the scaffolding and whatnot, but unless they very carefully reviewed and either manually edited or iterated a lot with the LLM I would be almost certain the tests were garbage given my experiences.
(This is with fairly current models too btw - mostly sonnet 4 and 4.5, also in fairness to the LLM a shocking proportion of tests written by real people that I've read are also unhelpful garbage, I can't imagine the training data is of great quality)
Far better off for who? People constantly dismiss spreadsheets, but in many cases, they are more powerful, more easily used by the people who have the domain knowledge required to properly implement calculations or workflow, and are more or less universally accessible.
As simple to build and deploy as Excel, but with the right data types, the right UI, the right access and version control, the right programming language that LLMs understand, the right SW ecosystem and packages, etc.
Especially for collaboration, access controls, etc. Not to mention they could do with unit testing.
That’s also the reason that so-called “Shadow IT” exists. Teams will do whatever they need to do to get their jobs done, whether or not IT is going to be helpful in that effort.
You have to remember that an SaaS, just like shrink-wrap software, reflects someone else's model of of a process or workflow and the model and implementation evolve per the timeline/agenda of its publisher.
For certain parts of certain workflows, where there's a highly normative and robust industry standard, like invoicing or accounting or inventory tracking, that compromise is worthwhile and we've had both shrink-wrap and SaaS products servicing those needs for a very very long time. We see churn in which application is most popular and what it's interface and pricing look like, but the domains being served have mostly been constant (mostly only growing as new business lines/fashions emerge and mature).
Most of the stuff that remains in a "core sheet" could benefit from the attention of a practiced engineer who could make it more reliable and robust, but almost always reflects that the represented business process is somehow peculiar to the organization. As Access and FoxPro and VBA and Zapier and so many tools have done before, LLM coding assistants and software building tools offer some promise in shaking some of these up by letting orgs convert their "core sheets" to "internal applications".
But that's not an opportunity for SaaS entrepreneurs. It's an opportunity for LLM experts to try to come in and pitch private, bespoke software solutions for a better deal than whatever the Access guy had promised 20 years ago. Because of the long-term maintenance challenges that still plague code that's too LLM-colored, I wouldn't want to be that expert pitching that work, but it's an opportunity for some ambitious folks for sure.
But it's very hard to have a large conventional cell-formula spreadsheet that is correct. The programming model / UI are closely coupled, so it's hard to see what's going on once your sheet is above some fairly low complexity. And many workplaces have monstrous sheets that run important things, curated lovingly (?) for many years. I bet many or most of them have significant errors.
Assuming the SaaS is implemented competently, of course. Otherwise there's not much advantage.
If you are a chairmaker and everyone gains access to a machine that can spit out all the chair components but sometimes only spits out 3 legs or makes a mistake on the backs, you might find it pointless. Maybe it can't do all the nice artisan styles you can do. But you can be confident others will take advantage of this chair machine, work around the issues and drive the price down from $20 per chair to $2 per chair. In 24 months, you won't be able to sell enough of your chairs any more.
But that's exactly not the case. Everyone is wondering what tf this is supposed to be for. People are vehemently against this tech, and yet it gets shoved down our throats although it's prohibitively expensive.
Coding should be among the easiest problems to tackle, yet none of the big models can write basic "real" code. They break when things get more complex than pong. And they can't even write a single proper function with modern c++ templating stuff for example.
From where I sit, right now, this does not seem to be the case.
This is as if writing down the code is not the biggest problem, or the biggest time sink, of building software.
Often these SaaS tools are expensive, aren't actually that complicated (or if they are complicated, the bit they need isn't) and have limitations.
For example, a company I know recently got told their v1 API they relied on on some back office SaaS tool was being deprecated. V2 of the API didn't have the same features.
Result = dev spends a week or two rebuilding that tool. It's shipped and in production now. It would have taken similar amount of time to work around the API deprecation.
How many samples do you have?
Which industries are they from?
Which SaaS products were they using, exactly and which features?
> For example, a company I know recently got told their v1 API they relied on on some back office SaaS tool was being deprecated. V2 of the API didn't have the same features.
Was that SaaS the equivalent of the left-pad Node.js module?
NODS HEAD VIGOROUSLY
Last 12 months: Docusign down 37%, Adobe down 38%, Atlassian down 41%, Asana down 41%, Monday.com down 44%, Hubspot down 49%. Eventbrite being bought for pennies.
They are being replaced by newer, smaller, cheaper, sometimes internal solutions.
Like I prefer Opus 4.5 and Gemini 3 to the open weights models, but if Anthropic or Google upped the pricing 10x then everyone would switch to the open weights models.
Arguably you could say that the Chinese labs may stop releasing them, true, but even if all model development stopped today then they'd still be extremely useful and a decent competitor.
What’s the cost to run this stuff locally, what type of hardware is required. When you say virtually nothing, do you mean that’s because you already have a 2k laptop or gpu?
Again I am only asking because I don’t know. Would these local models run OK on my 2016 Mac Pro intel or do I need to upgrade to the latest M4 chip with 32GB memory for it to work correctly?
Was there an explosion of useful features in any software product you use? A jump in quality? Anything tangible an end user can see?..
mwkaufma•1h ago