I’m at 90%+ code AI generated by stats. I work in embedded systems. It still goes off the rails all of the time and needs a heavy hand to guide it. It does not currently feel like it will ever be truly able to operate independently. It’s a very useful tool, but it’s just not there yet in my day-to-day.
Obviously, YMMV.
Maybe your point is just what the difference is to me. It’s competence. On hard problems Fable can just iterate by itself like nothing before. You give it a task, it can plan it, formulate and falsify hypotheses, and do more complex reasoning than anything before it. The main difference is simply that it gets more right and can go deeper on everything. Yes, you do still need to course correct it, but it’s just on the next level.
It’s like what everyone experienced when Opus 4.5 came out last year, and the penny finally dropped that AI coding had arrived. If these sorts of jumps happen even one or two more times then it’s all over. It might even be over now and it’s just too expensive to run, but that will change over time.
If you can, you should try it and see for yourself.
Honestly, the biggest improvement AI have brought me is the complete end of my imposter syndrome. People say comparison is the thief of joy,but in my case, previously invisible devs getting more visibility, suddenly pushing new code every week at the same pace as me but clearly without any understanding any of the underlying issues did wonder to my self esteem. I still consider myself among the worst of my group, but my group evolved from 'all devs I know' to 'the competents', which is very nice.
To the direct point: I've used AI for a lot of things. It's good, you can definitely build some things faster. It's far from perfect.
Also, if we were sooooo close to AGI, why would Anthropic and OpenAI continue hiring SDEs like mad, which they are? Why would Claude & co have embarassing bugs years after release (the glitchy scrolling bug, their websites being fully synchronous in 2026!!)? Etc.
The steam engine was invented in 1765 (+/-) but employment crashed in the textile industry starting in 1815, 50 years later.
LLMs were practically invented in 2017, 9 years ago.
Of course, software is software and we live in a faster age, but guess what, human needs and desires are infinite so requirements keep going up.
At this point I have 0 trust in purely agentic coding (i.e. the 0 supervision approach). YouTube randomly stops displaying subtitles, Gemini CLI (before its shutdown) and Claude Code suffer from constant refresh glitches, the Gemini and Claude mobile websites are synchronous, like we're living in the 60s (if I minimize Firefox both Claude and Gemini stop answering and Gemini until about 1 month ago would also lose my prompt - this is the kind of thing people were fired for in the past, etc). If this level of buginess is the best agentic coding can produce with unlimited state of the art mega corp tokens, software itself will collapse faster than the job market.
Claiming that there will be no more SDEs of any kind, worldwide, in max 2 years, is an extreme position.
I'm not even an SDE. If they're turkeys, AI boosters are pheasants :-p
And I know why the legitimate AI boosters do it. They were genuinely impressed by what they saw in agents, especially since many hated programming anyway. They extended the line into the future and assumed complexity was linear. These people looked at LLMs and agents and didn't see what was there, but what could be (frequently from a position of major SciFi consumers through their entire lives, as all techies are).
Optimism is a positive, extreme optimism is a great flaw.
Nobody said that. The claim is that within 24 months the models will have the capability required to replace all of us. I stand by that. How quickly that moves to everyone actually getting replaced is a social and economic question. There may very well be well be a long tail, I’m sure today you can find traditional weavers and barrel makers somewhere, they just happen to be economic novelties.
For the record, I’ll say that by 10 years out the profession is hollowed out enough for it to count as destroyed, and the process has already begun.
LLMs/turtles all the way down?
Also Fable 5 isn't "that impressive" as a lot of people have that kind of intelligence since 6 months+ by using combo of models and loops (I scored better on HLE than gpt-5.5 xhigh last January with some good tooling and 6x the cost), but for a lambda Claude Code user, I can see why it looks that good.
End result - 2 hours later it produced a convincing theory with lots of references, and burned a bunch of tokens too of course. just for fun we tried its suggestions and deployed them to prod. Guess what? Didn’t fix the issue. Alas, a human was needed after all.
either everyone’s working on toy problems, or they’re working on very cookie-cutter code. I’m really not sure. I DO remain impressed with Fable 5 but the idea that we’ll all be unemployed in 2 years is hilarious delusion. we’re already at the point where many organizations are scaling back some of their AI spend.
And while we’re talking about hilarious delusions, perhaps you should look at the current capability curve of AI and weigh it against the constant stream of arguments for why it couldn’t have continued at every point and yet has.
Yes, the solution is to just burn more tokens.
In this case i had no empirics in the loop. The scenario was only reproducible under high api load. I could load test, but management isn’t eager to spend prod-like costs in staging (requires scaling opensearch a lot in stage). What can i say.
On the bright side, maybe that means the end of new javascript frameworks every 6 months :)
However, the ability to reason generally on novel problems is AGI and we aren't there yet. Eventually in the absence of AGI, we will have to train models on them, and that will require data.
In my experience with all agents, including Fable, is that they work great when there is automated validation. But as soon as it needs to design something, it just keeps adding so much slop.
"Models can code well now but they cant do high level architecture" is just a logical fallacy. Its literally only true in this particular moment in time. But if they can code well, whose to say they wont architect well? And at that point, what do SWEs do? If anything, SWEs are in the critical path of automation for these AI labs anyway, so theres a very strong incentive to automate us out vs other professions, and it'll happen soon. All these random 1-off datapoints of "Fable 5 can't do X very idiosyncratic thing" are completely missing the point. 6 months ago, even attempting that problem with any "tool" would be totally intractable, and now it _just_ writes a slightly subpar solution. You can do some basic extrapolation here, its not that complicated.
Your best bet is to just chose a different career, or, if you still want to be in the software industry, be more enterprising.