6/9/2026 at 8:56:21 PM
Reminds me of the old joke "90% of the code is 90% of the work. The last 10% of the code is the other 90% of the work."I have spent almost my entire adult life (since 1986) shipping products. One of the very first things that I learned, was that "shipping" > "designing".
There's so much work in delivering products that will carry your brand, and then must be supported.
I liken it to having children. Conceiving them is fun. Delivering them is painful. Raising them, is a lifetime of work.
In my experience, the same type of thing applies to products that we ship (and charge money for).
by ChrisMarshallNY
6/10/2026 at 9:49:47 AM
Beautifully said. Engineering is often just a cost center and I often have the feeling management is suspicious that the engineers are just wasting time and throwing up roadblocks for nothing. This in turn makes managers always on the lookout for "the shortcut" to cut out as many of those engineers as possible.There is a definite lack of appreciation for the often repetitive grit, toil and maintenance work required to just have profit generating working software running reliably in production.
by leokennis
6/9/2026 at 10:13:37 PM
> There's so much work in delivering products that will carry your brand, and then must be supported.People think otherwise with AI partly because Anthropic kept telling us that they didn't have to write code or review code any more for most of their work. Their agent swarms just comb through their github, slack and wikis to figure out what to do next, and another swarm of agents just review, test, merge, deploy, A/B test, and revert the code. Boris alone merged nearly 300 PRs in the past week (or two?). So the top research labs seem have broken the productivity seal.
And then they talk about this recursively self-improving AI that is so powerful, so autonomous that they advocate that every company should be prepared to "pause" the effort. And their Fable/Mythos has this specific restriction as mentioned in their model card[1] that they are going to reject requests to tune and train models because, well you guess it, the models are too powerful to be used by mere mortals.
[1] We’ve implemented new interventions that limit Claude’s effectiveness for requests targeting frontier LLM development (for example, on building pretraining pipelines, distributed training infrastructure, or ML accelerator design). Using Claude to develop competing models already violates our Terms of Service, but enforcing this restriction through our safeguards avoids accelerating the actors most willing to violate these terms. Unlike our interventions for cybersecurity, biology and chemistry, and distillation attempts, these safeguards will not be visible to the user. Fable 5 will not fall back to a different model. Instead, the safeguards will limit effectiveness through methods such as prompt modification, steering vectors, or parameter-efficient fine-tuning (PEFT).
by hintymad
6/10/2026 at 3:17:54 AM
I think taking Anthropic or any company in this space at face value is naive at best though. AGI has been 6 months away for years now. Surely anyone can think this through: Anthropic knows what theyre doing with their public facing repositories, they know to make things enabled by their tech seem impressive. I would consider Bun etc. examples of this.Realistically, nobody intellectually honest really knows.
by koe123
6/10/2026 at 4:37:53 AM
People think otherwise with AI partly because Anthropic kept telling us that they didn't have to write code or review code any more for most of their work.Even if that were 100% true, it only collapses the coding effort to near zero. Anyone who's built and shipped a real product should know that coding is maybe 50% of the work, and on a mature product it can be much less.
by onion2k
6/10/2026 at 4:42:57 AM
even boris says they need people with judgment to manage the agentsi dont write code by hand anymore but shipping something people want is as hard (or maybe harder?) as its ever been
by vanuatu
6/10/2026 at 4:57:27 AM
Boris also says he stops using /plan, he writes loop to write prompt, and he simply asks AI to come up with solutions. He also said many times that his agents would comb their emails, slack channels, and Github issues to come up with things to do. When we combine what he has said, it's hard not to have the impression that he was implying full autonomy of their agents. The only that the engineers need to do is to build harness and to issue approvals, rejections, or suggestions.by hintymad
6/10/2026 at 5:24:25 AM
I work on a toy project that has exactly one user (me). On its face it's fairly simple. It's a portal to my media server because I didn't like how Plex worked with regards to searching and filtering. I can look for movies or series by director, studio, publisher, etc. I can rate things, I can find highly rated things. It's great, and instead of bugging plex support to add new features, I just tell Deepseek to do it. I started it before LLms were prevalent and now that I have open code I've had Deepseek write and rewrite most of my code and implement new features.But even with this toy project, and the target market being someone I should know very well (me), I often struggle to figure out what I want the app to do. When I go through brainstorming or grilling sessions it'll often ask me a question about how the product ought to work and I'm just like ¯\_(ツ)_/¯ give me suggestions and I'll let you know.
by abustamam
6/10/2026 at 6:08:34 AM
Genuine creativity is something LLMs struggle with and it kind of makes sense given their design. If you have a complete plan for a feature or even just an idea what the feature should do, that is enough for an LLM. But asking it to think and come up with a new feature idea by itself will always yield mostly extereme basic things you've already thought of. That creativity of "what" to build so it serves a purpose is still very difficult imo and LLMs are not good at it.by altmanaltman
6/10/2026 at 8:01:04 AM
> People think otherwise with AI partly because Anthropic kept telling us that they didn't have to write code or review code any more for most of their work. Their agent swarms just comb through their github, slack and wikis to figure out what to do next, and another swarm of agents just review, test, merge, deploy, A/B test, and revert the code. Boris alone merged nearly 300 PRs in the past week (or two?).Apart from many other issues with this, heavily subsidized subscription plans won't last forever, and if you start burning your own money on tokens in this way, you'll soon realize it's terribly inefficient.
by benterix
6/10/2026 at 2:15:21 AM
I’ve been wondering if “you’re not google” when learning about googles software dev process applies to Anthropic. Anthropic is a company that A. Has cheap unlimited access to its models and B. Is probably largely insulated from the types of tradeoffs that the rest of industry has had to observe in the post-ZIRP era.Like did they break through the productivity seal? Or are they willing to spend that much more on it since they see their failure as a like existential threat to humanity. I doubt it our boss sees your software the same way.
by techblueberry
6/10/2026 at 3:41:04 AM
It doesn't need to be an existential threat to humanity - it's an existential threat to their business. They need agentic workflows to work for their business to become profitable. So pouring money into the "no engineers write code anymore, only agents" model is at once R&D, QA, product development, and advertising. They can spend as much of their investors' money on this as they have to because if they can't (sustainably) sell this vision to other companies, their company collapses.by skillina
6/10/2026 at 2:17:06 AM
What is post-ZIRP please :-) ?by kreelman
6/10/2026 at 2:20:20 AM
Zero interest rate policy. When interest rates are Near zero you can spend money like it’s free. A lot of what we thought of as like normal engineering culture were the result of interest rates being zero.by techblueberry
6/10/2026 at 6:16:09 AM
Tah for that.by kreelman
6/10/2026 at 12:19:28 AM
> the safeguards will limit effectiveness through methods such as prompt modification, steering vectors, or parameter-efficient fine-tuning (PEFT)Holy crap that is dark. I like learning about ML for fun, and now I have to assume that their model is intentionally misinforming me to sabotage my learning? It is absolutely bananas that somebody decided that was ok behavior.
by californical
6/10/2026 at 1:59:04 AM
time to support open source and local modelsby claysmithr
6/10/2026 at 2:59:38 AM
I don’t see how that helps, unless you actually mean open source, rather than open weights like most people do. Without everything that goes into the model, including training data, these things are opaque.by jcgl
6/10/2026 at 3:50:54 AM
Actual open source is hard without a big war chest that allows you to flagrantly steal the training data.by Spooky23
6/10/2026 at 8:56:12 AM
That may very well be the case. In fact, I'm nearly certain that you're right. But it doesn't change the fact that open weight models are altogether insufficient on a number of important dimensions regarding freedom and transparency. And so often (such as the comment I replied to, I think), even technical people seem to just ignore the difference. Open weights are just weights. No amount of open-washing changes that.by jcgl
6/10/2026 at 5:40:43 AM
The raw training data is so large that very few parties could host it for free even if there weren't copyright barriers.But I think you could have a full open source training software pipeline that's set up to work with Wikipedia, Common Crawl, Books3, Library Genesis, Anna's Archive, and whatever other useful data sets people can name. There would just be a step where you have to provide your own copy of Library Genesis (or whatever subset of it you have managed to obtain).
by philipkglass
6/10/2026 at 2:36:01 AM
Someone could write a cyberpunk Three Body Problem with this premise.by lostphilosopher
6/10/2026 at 4:09:02 AM
They kinda did (though it's more inspired by Trusting Trust than AI)https://corecursive.com/coding-machines-with-don-and-krystal...
by crabmusket
6/10/2026 at 2:15:51 AM
TLDR :-)This comment is not entirely on point with your comment, it circles around and above it looking for lift though.
If you're not doing work that requires your code to stay in home nation data centres, Claude for Deepseek, Deepclaude (https://github.com/aattaran/deepclaude) is a great way to get better at using Claude like tools for software development. It even does a pretty good job of putting together cover letters for job applications...
Using Deepclaude is very much cheaper than using claude... For hobby projects, I've found it useful. A recipe (for cooking) management app I've made took a couple of hours to put together and cost $US 0.5. Claude is far more expensive.
The downsides of Deepclaude for many are:-
- DeepSeek is a Chinese corporation so the Chinese Communist Party may ask for data if it wants it.
- DeepClaude isn't as fast as normal Claude, though it's still pretty fast and I think fast enough (YMMV).
- DeepClaude might not be as optimised for various code issues that Claude may be able to solve more quickly or effectively.
- The same safeguards are probably on DeepSeek, but you won't be "wasting" as much money as you might on using Claude.
Inference focused hardware (https://www.youtube.com/watch?v=nvPqHoVSenE, AI generated speech) may in the medium future cause a large enough cost/energy reduction for LLM tools like Claude to make local LLMs more attractive.
Inference focused hardware would make running Open Source models like DeepSeek on local machines far cheaper and control over safeguards would return to the end user.
Hopefully this leads to a localised LLM provision market where local businesses provide varieties of these "local" LLM services. Here, local could mean on premise through to state or nationally based LLM services. Eventually, government orgs outside of the US may demand this kind of LLM use, in the same way governments legally require data to be stored within national borders for many critical government functions.
A bloke can dream I guess...
...Could affordable inference focused hardware also cause the bottom to fall out of these stock market bending valuations for AI corps and their datacentre obsessions?... Not to mention the societal costs caused by the AI super corps building these data centres. At the moment, they're nearly making a profit... They seem almost like speculative companies... Is that a term?
by kreelman
6/10/2026 at 1:12:56 AM
Anthropic is full of shit.by elzbardico
6/10/2026 at 9:14:21 AM
[dead]by hansmayer
6/9/2026 at 9:16:01 PM
Fully agree. Shipping a complete product with a functioning user acquisition funnel is much harder. It's like; you have to build the whole product first with lots of features and then you have to try to create a highly condensed overview of all those features to expose them all on the landing page.If you can't make the visitor understand your entire complex product in 10 seconds, then you've lost them.
Your product has to be complex because that's where the software market is at. All of the low-hanging fruits have been taken by the time you identify them. Sure, someone will find a way to make money using new low-hanging fruits that arise due to technological changes but it's not going to be you. You probably don't have the business connections to make that work.
by socketcluster
6/10/2026 at 12:08:27 AM
I'm not entirely sure how that dismisses the CEO's putative argument: they go big on AI precisely because shipping end-to-end is hard, so they think they shouldn't waste resources on tasks that can be automated.The structure of a good argument would be something like: certain tasks are fundamentally human and impossible to automate (which and why?) and by pushing AI use beyond what is optimal you are actually hurting your employees ability to do those hard parts.
A weaker but still useful argument is that most everything can probably be automated, but frontier models aren't there yet.
by cornholio
6/10/2026 at 12:39:26 AM
I wouldn't say it "dismisses" their argument, but I think AI marketing encourages them to take an over-simplified view of what it takes to ship product. Most folks like a good, simple story, as opposed to the unvarnished truth.> "There's always an easy solution to every human problem; Neat, plausible and wrong."
-- H. L. Mencken
It's like the classic scenario, where you lash-up a barely functional UI demo, and the manager cuts your development schedule by 90%, because you "already have it working." That taught me to never do a lash-up demo. If I show something to someone, it is ship-quality (but often incomplete). It's a technique that I've used for years, and is a great way to involve nontechnical stakeholders, without risking stuff like "it's already working."
All that said, I think that AI definitely could automate a lot of the repetitive stuff involved in shipping. It's just that the CEO would fire the folks that could teach it, before it can learn, because they think that what they do, is "unimportant."
by ChrisMarshallNY
6/9/2026 at 10:54:48 PM
I hate to use a throwaway, but this bit:> with a functioning user acquisition funnel
How do you actually get this. I've got a product, the site is hand crafted, shows the complex product really well (and had good feedback on it) but how do I acquire the users?
It seems as the cost of creating software has plummeted, it's the actual sales side of it that's going to matter even more. I'm stuck at this point.
by tauserfunnel
6/10/2026 at 12:07:31 AM
"How do I acquire users" is the entire function of sales and marketing. A single HN comment explaining how to do sales and marketing, which is highly dependent on your product and market (and much more difficult than technical people tend to believe), is a bit unrealistic. And a great opportunity to use Claude/ChatGPT for something other than code. There's no silver bullet but as a springboard you can think about:Who is your ideal customer profile (look up buyer personas) -- if you're B2B figure out both the profile of the company who would buy, as well as the person who would actually buy, and the person who would actually use the software: remember that buyer != user in B2B scenarios, and you'll have to figure out if the buyer, user or both is the best path to getting a sale. If you're B2C figure out your buyer personas so you know where to advertise.
Why would people want your product; sounds like you may already have this down but be ready to explain your value proposition concisely.
How will these people hear about your product -- a SaaS that falls in the woods doesn't make a sound, you need people to learn your product exists before they can pay for it. This is the point of figuring out buyer personas, you need to meet your customers where they are, and you can't know where they are unless you know who they are. This is highly dependent on your product/personas, and could range from running LinkedIn ads to SEO to having a Bluesky brand account to going to local meetup groups or conferences and trying to get your first handful of users in-person.
by mjr00
6/10/2026 at 8:02:09 AM
[dead]by tauserfunnel
6/9/2026 at 11:50:03 PM
Get a dozen users word of mouth? They will tell friends? Won’t scale forever but it gets you going.by brianwawok
6/10/2026 at 1:38:58 AM
Sorry to burst your bubble but the cost of creating software has not, bloatware definitely has.by newsicanuse
6/10/2026 at 8:06:12 AM
[dead]by tauserfunnel
6/9/2026 at 9:02:09 PM
I like this analogy; raising children well like delivering products well pays dividends. They’re less likely to cause problems and if they do, they tend to be smaller in scope.by pknomad
6/9/2026 at 10:40:42 PM
> 90% of the code is 90% of the work. The last 10% of the code is the other 90% of the work.Don't think I've heard that one but certainly rings true to my experience.
Reminds me of "ninety percent of the game is half mental"
by dieselgate
6/9/2026 at 11:19:08 PM
I've heard it as "once you think you're 90% done, you're really halfway done."Tangential: it's always made me wonder about teams that believe "80% effort" is optimal.
by radley
6/10/2026 at 1:37:47 AM
Great analogy all the way through. Also the last 10% takes thre most effort/iteration to get the work done such that you don't spend a lot of time maintaining it later.by newsicanuse
6/9/2026 at 10:10:13 PM
I skimmed the article, guilty, but I think what I got from it is that CEOs will CEO? No disrespect meant, I’ve seen your name here often and thoroughly enjoy the folklore that you share, but I don’t understand what context you reacted to. Cheers.by stasomatic
6/9/2026 at 10:16:59 PM
The context that they think that shipping is simple. Shipping (what you need all those annoying peons for) is really terribly difficult, and has a lot of moving parts that designers often fail to take into account, until the deployment people lock them into a restroom stall, and refuse to let them out, unless they listen.That's common with newer engineers (and now, non-engineers). I believe that Mr. Dunning, and Mr. Kruger had something to say about it.
I also spent most of my career at hardware-oriented companies, and shipping hardware is orders of magnitude more difficult than shipping software.
by ChrisMarshallNY
6/9/2026 at 11:48:22 PM
Thank you. You spent some time at Apple, no? There is that “real artists ship” or “great artists steal”, but I wonder what he’d say now. Just fun to think about.by stasomatic
6/10/2026 at 12:30:24 AM
Not as an employee, but I've been an Apple developer since '86. Had fairly intimate relationships with them, at various points in my career.by ChrisMarshallNY
6/9/2026 at 9:21:55 PM
> Conceiving them is fun. Delivering them is painful. Raising them, is a lifetime of work.Then there's the technical debt!
Shipping is frankly the easy part. It's the operating overhead that often breaks you.
I liken it to free puppies.
by mullingitover
6/9/2026 at 9:56:36 PM
This is true.I have always prided myself on writing concise, high-Quality code, because it tends to be quite debt-free.
So far, LLMs seem to deliver code with "Louie Da Loan Shark"-levels of tech debt.
by ChrisMarshallNY
6/9/2026 at 11:01:50 PM
The problem is that the lines of code are riding on a stack of other dependencies that all need care and feeding. Things reach EOL. Frameworks have major breaking changes. CVEs are discovered.by mullingitover
6/9/2026 at 10:10:32 PM
You can actually get high-quality code out of them -- at least with Claude; not had a great experience with Gemini -- but for complex tasks requires riding them very, very hard and really understanding where things can go wrong and poking at them repeatedly. Iterate, iterate, iterate.by KerrAvon
6/9/2026 at 10:19:10 PM
> Iterate, iterate, iterate.That describes my last week. What made it most annoying, was the need to release through TestFlight, because the memory issues would not appear, when tethered. Also, I was checking in constantly, because I had to revert and reset the context, several times.
by ChrisMarshallNY
6/10/2026 at 12:33:25 AM
You mentioned in another part of this thread that you worked in hardware mostly?It seems like the cost of changing hardware code is high enough to still insist on building it high quality, is that accurate?
by bluefirebrand
6/10/2026 at 12:57:05 AM
Yes. It's also why working as a software (host) developer at a hardware company is difficult.Hardware people insist on treating software the same as firmware.
Bad firmware can cause real-world, physical damage, and be impossible to fix without a hardware recall. A firmware bug can wipe out a hardware company. A software bug can be embarassing, but can also be corrected a lot more easily (as long as it is being treated differently from firmware).
by ChrisMarshallNY
6/10/2026 at 5:33:28 AM
> So far, LLMs seem to deliver code with "Louie Da Loan Shark"-levels of tech debt.Maybe a couple of years ago, but these days, Opus 4.8 is frankly writing better software than what I've seen over the previous decades in non-tech enterprise. These previous two months, we've replaced so much technical debt we've been dragging along for the previous 5 years as our team went from 25 to 3 people.
This is in non-tech enterprise in Denmark and AI had absolutely no impact on us going from 25 to 3. That was all Putin and bad business decisions on the c-levels. Like keeping flexible loans to fund projects on the books when the interests rates were 0.01% because they might go to 0.001%. Anyway, I'm getting to the point where the AI does 100% of the work, but only if it's piloted by people who know what security, resource consumption and compliance is. The code itself is excellent though.
by Quothling
6/10/2026 at 6:37:40 AM
> Maybe a couple of years ago, but these days, Opus 4.8...No. Opus 4.8 still writes bad code, just like every other time AI boosters have claimed "but the newest models are really good".
by bigstrat2003
6/9/2026 at 9:41:53 PM
Every line of code is a liabilityby lokar
6/9/2026 at 9:50:31 PM
Yup. In another post, I was grumping about having to accept a truly obese bunch of code from an LLM. This particular issue is the only one I could imagine even considering accepting that much pasta, but I sort of have to, because the LLM was able to quickly solve a problem that would have taken me a couple more weeks to address.I remember a .sig that went something along the lines of:
I hate code, and want as little as possible in my software.
by ChrisMarshallNY
6/10/2026 at 6:18:55 AM
Amen. Or I should say RIP.by ilteris
6/10/2026 at 12:55:41 AM
> I liken it to having children. Conceiving them is fun. Delivering them is painful. Raising them, is a lifetime of work.I am not a children person. But I love this analogy.
To deliver something nice, we also must accept some suffering.
by Yokohiii
6/10/2026 at 2:15:32 AM
In various different projects I've been involved in where we've been implementing (not developing) software solutions I've noticed that, at management level, there is little regard given to the level of maintenance required of running the software; that people are still needed; that, yes, processes are automated, but there's a helluva lot of ongoing work required to ensure that new data won't pop the automation off the rails.It's as if the installation part is the hard bit, and after that it'll take care of itself for ... far enough into the future that it won't be <current manager>'s problem. It is solved.
... and that's just using the system, not fixing bugs and adding features.
by BLKNSLVR
6/10/2026 at 12:21:00 AM
%80 of CEOs are Meh. %10 of the CEOs add value to the company. %10 of the CEOs are actually detrimental. The %80 will always try and do what they think the top %10 CEOs do because of FOMO. The bottom %10 will do it because they know their days are numbered and hope that it might put them in the %80 keeping their jobs. A good LLM could probably replace most and not do any worse.Good CEOs don't see their employees as an expense.
by strangattractor
6/10/2026 at 2:00:17 AM
Those percent estimates look about right :0Good CEO's make such good money on their employees that everybody gets raises and bonuses, the company grows responsibly, and the stock is a good investment.
Too bad it's out of reach for so many executives.
If that's too challenging, I understand, but if they had real confidence as a business operator I don't see why so many would be kicking out anybody over AI when they could at least continue to make the same money off the same people going forward. OTOH in cases where AI is almost ideally helpful it should be no surprise if hiring is slowed, and doing the accounting it could very well add up about the same either way. But one way clearly indicates the limited vision of a lesser leader, why settle for that?
Two of the most macro giveaway characteristics are emotionalism and superstition.
Not just for CEO's and other executives, but anyone in a leadership position or with decision-making tasks to perform.
One of the legendary combinations is when superstition is used in place of technology, and emotional reactions completely prevail instead of genuine business acumen.
It's a pretty good estimate that almost every CEO who thinks it would be good if AI replaced their employees, that these CEO's fit squarely in the superstitious camp.
I would say that's just one growing subset of a much larger smorgasbord of superstitions to choose from, and some big-shots are bound to indulge a whole lot more than others :\
by fuzzfactor
6/10/2026 at 4:22:47 AM
Honestly I am burned out on public discussion of AI. There are so many hot, low info takes on both sides. All the dumb stuff revolves around this imbecilic notion that AI will take your job.In that sense Altman and Dario et. al. were extremely successful in their cringeworthy campaign to establish themselves as priests of a new machine god religion. Even the people who don't want it believed them.
The good news is at least this year companies are starting to get a little more thoughtful about why they're paying for AI and what specific business function it serves.
Realities:
1. AI is a tool. You don't replace a job with a tool, just like you don't replace an apple with a sock. It was always an error of classification to think this way.
2. AI is a useful tool. For every CEO who thinks it justifies mass layoffs, there are dozens of people who don't want to admit that it does have a lot of utility. Anyone who isn't figuring out where this tool can make them more productive will have a hard time down the line imho.
3. We can infer from the priors that jobs will continue to be a thing, just like they still were after the inventions of printing presses, cars, power looms, etc. but there will be some pretty massive churn, some roles maybe disappearing entirely, new ones getting created, same goes for skill sets.
4. Businesses will use this churn to the best of their ability to either reduce costs or increase output. That second part is the key the AI haters don't seem to recognize. Thanks to competition, not every business wants to just fire everyone. Yeah, America's financialized and monopolized and less competitive than it used to be, but still, plenty of businesses will repurpose their budgets to produce more and expand.
So in terms of real specific and concrete things I've seen so far.
If you're in customer support that's a pretty rough spot, a well designed RAG system can turn 20 minutes of research into 20 seconds. Customer support budgets flow downstream from actual usage/customer base so if they can do more with less people will get laid off, they don't expand scope, they automate and cut the budget.
If you're a developer, your position's a lot more secure than that, coding agents are pretty incredible but they are simply not at a point where they can think through architectural decisions, and they occasionally go off the rails and trash everything. These things need to be operated and steered. Yes that's 100% the future of the profession and I'm sorry if someone doesn't like that, being a blacksmith who forges metal things by hand is also very niche these days, kind of sad if you loved blacksmithing but it happens. Devs also have to be aware that a PM/product owner can likely do some of their job now and I think any dev whose preference was to avoid thinking about customer or business requirements is going to find his utility is shrinking. A mass shrinking of the profession is unlikely but things will change and the only rational paths forward honestly are to retire or to figure out now how you fit in, it's a career opportunity if you get ahead of the curve even.
Lastly there is a whole other domain now which for lack of a good term I'll refer to as "prompt engineering," it requires some level of systems design thinking, but basically no programming expertise. The best candidate for this work is a person who possesses business process knowledge as well as systems oriented thinking. Maybe these jobs will end up finding a home in the IT department or something. As an economy we're barely recognizing them yet but I see that in engineering we can increasingly implement places for a prompt input, and then hand some workflow/business domain decisions off to someone who understands them better and they just tweak their prompts over time to get a great system. Pretty sure new jobs will be created and formalized around this over time.
by safety1st
6/10/2026 at 8:24:21 AM
I think this is the most level-headed take I've read in a while, sums up perfectly the HN discourse on "AI taking our jobs", thanks!by cpt_sobel
6/10/2026 at 9:08:44 AM
Agreed.It is a fairly good summary of my PoV.
by ChrisMarshallNY
6/10/2026 at 9:37:06 AM
Thanks guys!It's happening! We can see it! The future is somewhat legible and in it we don't all die! (Well we do, but mostly for the usual reasons)
We just gotta keep getting out of bed and making a smart choice or two between now and then!
by safety1st
6/9/2026 at 9:01:47 PM
[flagged]by aplomb1026
6/10/2026 at 12:17:59 AM
[dead]by ofModel35ba3b
6/9/2026 at 9:37:04 PM
now it's closer to 95% of work can be done by AI and requires 5% mental effort, but 5% of the work requires 95% of the mental effort to finish because of all the unoptimial decisions AI has taken. I find that AI works best in small micro-service type architecture where each component has a clear goal and doesn't have interconnected parts within the same application that can break. But you do run into an issue where changes in microservice a need changes in microservice b and updating it is not ideal since it usually cascades thru the entire system or requires stacks of legacy support.by himata4113
6/9/2026 at 9:41:31 PM
IME it’s possible to have good clear APIs, limited scopes/goals, etc in a normal (macro?) service. But it requires a level of discipline and process many teams are unwilling to engage in.by lokar