To be honest, I doubt the current state of things will hold much longer. Current AI can automate virtually all of my work as a pre-AI senior and is rapidly closing in on being able to automate the types of work that have emerged post-AI too. I have a hard time imagining a world where a drop-in end-to-end replacement for a full software team is more than a year away. I'm sure I'll have a job for a year or two past that, but there'll be some small stock market bump eventually and a bloodbath will begin the second the C-suite takes a closer look at what their engineers are even doing anymore.
At which point the question will be: What are even the customers paying for? If they can get the product / service straight from their own chatbots, why pay a company for it? The companies that sell data, will probably somewhat safe - as long as they can have some moat between the users and data.<p>The death of SaaS could also be a thing in the (not so distant) future.
C-suite is as likely to be automated as engineers. It will probably be AI firing engineers on behalf of shareholders.
> C-suite is as likely to be automated as engineers.<p>Nah. C-suite has (a) money and (b) legal and fiscal obligation. You literally need a human being certain legal operations, like incorporation, salary, and lawsuits.
I think a lot of people thought that every step of the way with the progress of AI or automation in general. Unless that C-suite is all shareholders with majority or near majority control of a company, I would think the passive shareholders (in a public or private company) would want the savings in cutting all of those high salaries to zero for a likely superior outcome with AI.<p>I wouldn't count on lawyers being deemed necessary by the law for as many actions as they have been so far.
Who is C-suite going to blame for fuck ups and failures if the company is just a suit and a laptop?
You need *a* human. And that human will be delegated to clicking approve on AI decisions.
> To be honest, I doubt the current state of things will hold much longer. Current AI can automate virtually all of my work as a pre-AI senior and is rapidly closing in on being able to automate the types of work that have emerged post-AI too.<p>reading HN these days feels like constant gaslighting. this is so far from my reality that i wonder what folks who are saying this are working on
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<a href="https://nitter.cf/shaharglazner/article/2119796029256032278" rel="nofollow">https://nitter.cf/shaharglazner/article/2119796029256032278</a><p>A readable link for those of us without Twitter/X account
If you can’t make things right when your agent goes wrong, then yeah you’re not adding value. If you can’t tell the difference between the agent hallucinations and the useful stuff, then yeah you’re not adding value. If you can’t steer the agent in a useful direction instead of just standing back, then yeah…
You sound dismissive, but taking your description to its conclusion, the engineer value can be approximated as:<p><pre><code> {(P(AI mistake) * P(human spots the mistake | AI mistake) * P(human fixes mistake | given AI mistake, human spots it) - P(AI mistake)} * cost of AI mistake
</code></pre>
For many engineering jobs, P(AI mistake) is very low and decreasing, and cost of AI mistakes is also usually (consider the cost of a bug for an average engineer; unless you’re building avionics or working on MRIs or such, usually very low).<p>So even if you can “make things right” or “tell the difference” as you say, the value of any given engineer is dropping.
At first I thought tacit knowledge would be a differentiator: LLMs are trained on writing, so they can’t learn things that have never been written down. But tacit knowledge is exactly what reinforcement learning post-training is about. So (just as with humans) the limitation is in providing a rich enough environment, with good enough feedback, to train in the tacit knowledge.
I don't buy the reductio ad absurdum, which hinges on the assertion that some developers are still 10x more productive than others due to differences in their engineering potential. I think that A) however you're measuring productivity is probably not capturing the full story, and B) one of the most important reasons people have differences in productivity is because not everyone puts the same amount of effort in. It's not necessarily because they don't have the ability to stay off of reddit and work longer hours and prompt more furiously, it's because not everyone is equally motivated to do so (hence the entire field of management).<p>I also don't buy the idea that there is special human stardust that gives us permanent irreplaceable economic value. Even if the tacit knowledge that the current generation of engineers were able to build up in the years prior to ~2025 does give us value that won't be completely replaced for a long time, why would you assume that the delta between what you can do and what claude can do will still be worth $200K in 5 years?
I'm a fan of the 'sandwich' model: someone needs to say what to do, someone needs to do it, and someone needs to say if it's been done [well enough]. Even if AI can do that middle bit entirely, we still need humans at the beginning and the end. Replace the humans at the start and you have a paperclip-optimizer; replace them at the end and you have slop.<p>The problem is that software in corporations has typically been product managers at the front, software engineers in the middle, and QA at the end. Software developers who also have good product sense and do diligent QA are still needed. Programmers who treated their job as leetcode exercises are not needed anymore.
The trick is to remain intellectually stimulated and challenged.
On Being an [Software] Engineer (i.e. AI agent manager) in 2026
> Maybe one day agents will have their own experiences, too. Maybe they'll develop intuitions they can't quite explain, just like we do.<p>Machine / program / software cannot have these things in my opinion because this stuff is produced by human consciousness which we cannot even fully explain yet. Someone has "to teach" the agent to have this stuff, but we don't have that knowledge. And also "intuition" is a feeling (like love, hate, sadness, joy) so no agent can have that until they have the limbic system, prefrontal cortex and other stuff.
Yeah AI is like the final step of the hubris of software creation where we think we can actually make something as wonderful as the human person.
Not everyone knows how the brain works and many believe it to be one organ.
"We can't explain it therefore we can't create it" doesn't seem like a strong argument, emergent behavior and whatnot.<p>Hell, the fact we don't know what consciousness is means that some LLM systems (or trees! or planets!) might already have it, and we'd be none the wiser. Not that I believe this, but as these systems get larger and more sophisticated it's an increasingly concerning proposition that we have no way to validate either way.