6 ms·

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 lif

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).

aplomb1026 5mo ago
[flagged]
pknomad 5mo ago
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.
socketcluster 5mo ago
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.
- tauserfunnel 5mo ago
  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.
  - brianwawok 5mo ago
    Get a dozen users word of mouth? They will tell friends? Won’t scale forever but it gets you going.
  - mjr00 5mo ago
    "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.
    - tauserfunnel 5mo ago
      I really appreciate you writing this down. Thank you. This has helped a lot more than you probably think.
  - newsicanuse 5mo ago
    Sorry to burst your bubble but the cost of creating software has not, bloatware definitely has.
- cornholio 5mo ago
  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.
  - ChrisMarshallNY 5mo ago
    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."
mullingitover 5mo ago
> 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.
- lokar 5mo ago
  Every line of code is a liability
  - ChrisMarshallNY 5mo ago
    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.
- ChrisMarshallNY 5mo ago
  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.
  - KerrAvon 5mo ago
    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.
    - ChrisMarshallNY 5mo ago
      > 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.
himata4113 5mo ago
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.
- lokar 5mo ago
  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.
stasomatic 5mo ago
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.
- ChrisMarshallNY 5mo ago
  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.
  - stasomatic 5mo ago
    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.
    - ChrisMarshallNY 5mo ago
      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.
hintymad 5mo ago
> 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).
- californical 5mo ago
  > 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.
  - claysmithr 5mo ago
    time to support open source and local models
dieselgate 5mo ago
> 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"
- radley 5mo ago
  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.
ofModel35ba3b 5mo ago
[dead]
strangattractor 5mo ago
%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.
- fuzzfactor 5mo ago
  Those percent estimates look about right :0 Good 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 :\
  - strangattractor 5mo ago
    If you replaced one CEO that was making 300 times the average salary of an employee - that is equivalent to firing 300 employees. You can have your AI and Reduction in Force without losing all those pesky people with institutional knowledge.
Yokohiii 5mo ago
> 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.
newsicanuse 5mo ago
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.
BLKNSLVR 5mo ago
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.
safety1st 5mo ago
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.
ilteris 5mo ago
Amen. Or I should say RIP.
leokennis 5mo ago
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.
BobbyJo 5mo ago
Software companies really are just operations companies that use software to deliver services.
ksec 5mo ago
Or more like the last 20% of work takes the same effort as first 80% of work. Which is the 80/20 rule. But increasingly I believe the 90/10 rules works better. As a matter of fact I tend to think of it the first 80% is 80% of work, the 80% of the 20% left is same as first 80% of work. The last 4% polishing is another first 80% of the work. I think that is a good rule for general project management.

aplomb1026 5mo ago

[flagged]

pknomad 5mo ago

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.

socketcluster 5mo ago

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.

tauserfunnel 5mo ago
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.
- brianwawok 5mo ago
  Get a dozen users word of mouth? They will tell friends? Won’t scale forever but it gets you going.
- mjr00 5mo ago
  "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.
  - tauserfunnel 5mo ago
    I really appreciate you writing this down. Thank you. This has helped a lot more than you probably think.
- newsicanuse 5mo ago
  Sorry to burst your bubble but the cost of creating software has not, bloatware definitely has.
cornholio 5mo ago
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.
- ChrisMarshallNY 5mo ago
  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."

mullingitover 5mo ago

> 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.

lokar 5mo ago
Every line of code is a liability
- ChrisMarshallNY 5mo ago
  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.
ChrisMarshallNY 5mo ago
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.
- KerrAvon 5mo ago
  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.
  - ChrisMarshallNY 5mo ago
    > 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.

himata4113 5mo ago

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.

lokar 5mo ago
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.

stasomatic 5mo ago

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.

ChrisMarshallNY 5mo ago
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.
- stasomatic 5mo ago
  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.
  - ChrisMarshallNY 5mo ago
    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.

hintymad 5mo ago

> 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).

californical 5mo ago
> 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.
- claysmithr 5mo ago
  time to support open source and local models

dieselgate 5mo ago

> 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"

radley 5mo ago
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.

ofModel35ba3b 5mo ago

[dead]

strangattractor 5mo ago

%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.

fuzzfactor 5mo ago
Those percent estimates look about right :0 Good 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 :\
- strangattractor 5mo ago
  If you replaced one CEO that was making 300 times the average salary of an employee - that is equivalent to firing 300 employees. You can have your AI and Reduction in Force without losing all those pesky people with institutional knowledge.

Yokohiii 5mo ago

> 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.

newsicanuse 5mo ago

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.

BLKNSLVR 5mo ago

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.

safety1st 5mo ago

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.

ilteris 5mo ago

Amen. Or I should say RIP.

leokennis 5mo ago

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.

BobbyJo 5mo ago

Software companies really are just operations companies that use software to deliver services.

ksec 5mo ago

Or more like the last 20% of work takes the same effort as first 80% of work. Which is the 80/20 rule. But increasingly I believe the 90/10 rules works better. As a matter of fact I tend to think of it the first 80% is 80% of work, the 80% of the 20% left is same as first 80% of work. The last 4% polishing is another first 80% of the work. I think that is a good rule for general project management.