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cgearhart 12 hours ago [-]
This seems very related to a trend I’m seeing as my company goes all in on AI: everyone thinks that every problem is “a couple hours” with AI now, and they all want zero external dependencies because they can move faster alone. As a result, we’re now in an even worse “yet-another-…” age where everyone has built approximately the same (but somehow incompatible) versions of all the same beginner-level software, and (ironically) while they want no external dependencies they’re also pushing for org-level mandates to require everyone else to use their solution. Meanwhile, no one wants to do the slow/bottleneck part that cant easily be automated or scaled; they just throw an “agent” at it and call it done—but there’s nothing _there_. You can trust the agent on easy tasks and you can’t trust it on hard ones, but you can’t tell which ones are easy or hard. Improvements in foundation model tech move thresholds of the problem but can’t eliminate it.
Long story short, I think we’re in a phase where the organizational value function is lagging behind the tech. A “proof of concept” used to be correlated with “proof of work” and some amount of domain understanding, but I think now what we need is a focus on “proof of understanding” or else you’re probably just wasting tokens on a baby version of the problem. A decent proxy right now is that if you have zero external dependencies then your solution is probably a toy.
Aurornis 1 hours ago [-]
AI completely broke some of the signals management used as proxies for team competence. In the past, teams that moved quickly and had a proof of concept to show management were valued for the speed of their execution. Usually a team that could execute quickly had some competent developers who could also quickly execute on the challenges of the implementation when it scaled up to real world problems.
Now anyone with enough LLM tokens can move quickly and have a pretty proof of concept in front of management in days or maybe hours. There's a land grab to get things in front of management so you can stake your claim on something. The implementation details are assumed to be solvable by enough Claude sessions and ChatGPT prompts.
Where this falls apart is that the real difficult problems don't scale well with LLM brute force techniques. You need people who understand the problem and know how to drive the LLM agents around properly, as well as when to set them aside and go look at the code and data themselves.
The teams who try to brute force everything with LLM tokens can get a little farther every few months, but for complex problems I've seen enough variations of teams hitting a wall of complexity and tech debt with a team that doesn't know much about how their system works because they've just been asking agents to solve every problem as it comes up. With each iteration it takes a little longer for the agents to come to a solution and the system becomes a little more brittle. Even with our current mega-context-window LLMs you can reach a point where every other change to your big ball of code breaks something else, which requires another agent session to diagnose and fix, which might then break another thing down the line. The refactors to try to clean things up end up breaking even more. Having a zillion tests starts to backfire when the team can't tell which tests are testing valid results and which are baking in incorrect results.
Maybe there's an end game where agents get so good that none of this matters, but I think it's more likely that we're going to have to build up better intuitions about what good execution looks like. The old signals of moving fast are meaningly and potentially even negative now.
Terr_ 55 minutes ago [-]
> AI completely broke some of the signals management used as proxies for team competence.
This is very similar to how LLMs were already breaking signals in writing. It was (is?) an enormously important proxy (however imperfect) for a bunch of things like: "put effort into this" or "is smart" or "is interested and engaged" or "has an emotion" or "has carefully considered the idea."
Heck, even basic awareness of an issue/detail gets forged, mentioned in the text but never in the mind of the sender.
tayo42 9 hours ago [-]
> they’re also pushing for org-level mandates to require everyone else to use their solution.
That's how you get promotions when you don't do anything valuable lol ok done with the cynicism
oblio 9 hours ago [-]
Not cynicism, incentives. Everything is shaped by incentives. We make movies about heroes and martyrs because they're 0.001% of us.
ehnto 6 hours ago [-]
No disagreement here, the incentives for software have always sucked. People complain constantly about how everything is enshittefied, that's just corporate incentives manifested.
jvanderbot 3 hours ago [-]
Do this long enough and you really believe it's good, after all the years of being promoted for strong-arming people.
But hey, I do it. I prebake my own tools to work within the system, a new person joins, and I show them the tools as an example. Instead of learning what it does and why, they just learn how to use the tool (now via claude).
goldlimetea 8 hours ago [-]
We need a Proof of Original Product (“POOP”) to de-shittify the AI web.
I call it fighting shit with POOP.
dominotw 10 hours ago [-]
problem is that no one knows what to build and there are way too many ppl employed
cgearhart 8 hours ago [-]
I’m seeing kinda the opposite. At some point it becomes obvious what to build and there’s no friction to building it anymore. So you get a flood of low effort copies of the same thing and no one wants to depend on anyone else, and the old value function was that ownership matters. I think the new value function needs to be much more focused on outcomes—and ownership isn’t an outcome.
beezlewax 32 minutes ago [-]
The result of this is huge wastage in terms of effort and tokens.
resonious 8 hours ago [-]
This is huge... At least from what I've seen, many companies (even if they don't know it) are largely sloppy R&D shops. Most people are on projects that are highly speculative and unlikely to generate revenue. But it often isn't framed that way. Everyone believes their project is the obvious way forward.
songhonglei1985 4 hours ago [-]
[flagged]
receptopalak 9 hours ago [-]
[flagged]
LogicFailsMe 15 hours ago [-]
In my side hustle time, I use coding agents to explore what if projects I would otherwise never get to build.
At my day job, I use AI to fix config, container, and installation issues so I can spend my time coding instead of struggling to fix mostly other people's mistakes. And really, in this age of python wheels, containers, virtual environments, and fragmented APIs, the cognitive load of doing this by hand would shut me down for the day.
1.5 years in and I haven't burnt out. If anything, I'm ramping up. I'm no longer afraid of adding a web UI, or insane numbers of unit tests, or deploying other people's software.
What I'm not doing is using it to build products, but instead just doing so to augment the supporting stack. All of this is subject to change as the AI landscape evolves.
embedding-shape 15 hours ago [-]
That's exactly what the article highlight might actually put your "competitors" (if you see others like that) in front of you, as focus and "what you actually did" becomes more important. Might be that while you shipped and experimented with 50 different APIs, your "competitor"/peer just did 3, but they were more carefully considered so the payoff ended up bigger/better, in whatever way that could be.
That's how I understood the article at least.
voicedYoda 14 hours ago [-]
My biggest struggle is UI. I can make functional, but my design skills couldn't sell water to someone in death valley
saghm 4 hours ago [-]
Same, honestly. I've dabbled in trying to come up with some UI stuff with LLMs, but I'm still not at the point where I'm totally comfortable. At my day job, luckily I have people much more talented than me at design who can provide feedback and guidance. For my personal side projects, I've had some modest success inducing the agent to provide the feedback from a suitable "persona", for lack of a better term (e.g. "Is there any existing standard on how to make this component accessible?", "How intuitive would you expect a non-technical user to find interaction with this?").
robomartin 3 hours ago [-]
I read somewhere that Claude is better at UI than Codex. I haven't tested it yet. I am currently using Codex for a couple of native application projects with Avalonia. The UI isn't really good at all and I can fix it by hand far better than it does with prompts. For example, a table to view database data ended up with huge spaces between rows and columns and it can't seem to grasp how to format a table nicely. So I fixed it by hand, no big deal.
misiti3780 14 hours ago [-]
Pick a website you like, and tell claude to use it for inspiration. I do this all the time and the results are pretty impressive and different than what you get out of the box prompting.
NateEag 12 hours ago [-]
> Pick a website you like, and tell claude to use it for inspiration.
I believe you misspelled "rip it off."
I guess I shouldn't be surprised that people are using the tools built by ripping off the collective creative works of humanity to rip off individual things, too.
tomrod 11 hours ago [-]
Steve Jobs said something about good and great artists.
georgemcbay 8 hours ago [-]
> Steve Jobs said something about good and great artists.
Picasso said that, Jobs quoted it (and to his credit, gave attribution... which I doubt is happening with all of these claude-cloned designs).
__MatrixMan__ 11 hours ago [-]
When other people emulate your behavior because they appreciate the results you got, we used to call that leadership. Something has gone awry that we now call it a ripoff.
NateEag 7 hours ago [-]
Emulating your _behavior_ is completely different from imitating your _output_.
vouaobrasil 12 hours ago [-]
> At my day job, I use AI to fix config, container, and installation issues so I can spend my time coding instead of struggling to fix mostly other people's mistakes. And really, in this age of python wheels, containers, virtual environments, and fragmented APIs, the cognitive load of doing this by hand would shut me down for the day.
I think it was a mistake to add this much complexity to the world of software in the first place, so I'd view AI as a bandaid to a problem rather than addressing the underyling issue. But on the whole, the cost of all this extra complexity, data centers to run AI to fix layers of crud and buildup don't seem to provide much of a net benefit to society (except to those who are at the top and need to see growth to pad their retirement portfolios).
LogicFailsMe 12 hours ago [-]
Oh no disagreement that it was a mistake, but as Ambassador Kosh once stated "The avalanche has started, it is too late for the pebbles to vote."
I would suggest not concluding the end of this movie from the first 5 minutes of the story. But then, I really fought against complexity over my career and lost hard. One can either check out as a fossil of the good old days or adapt to the new reality. 6 months ago, AI was about to replace all the engineers and then reality slapped the C-suite hard on that subject as just one recent plot twist.
vouaobrasil 12 hours ago [-]
It's not 5 minutes into this story, I think. It's been going on for a long time, but really started to become a "conscious entity" with computers - and I do think computers were a mistake.
tayo42 9 hours ago [-]
Your job would be so much harder without those supposedly complex tools. Most of those listed help solve issues with multiple environments. What simple solution is there to that.
danshipt 12 hours ago [-]
AI as an expensive bandaid
acedTrex 15 hours ago [-]
Ya this is exactly how I use it, the LLM does everything i don't want to do. Which is basically everything except the exact code im writing. Its very freeing to not have to worry or touch a jira ticket ever again. The LLM just does it for me.
bigyax 14 hours ago [-]
I'm actually not feeling the 'burnout', though I too have a bunch of projects sitting at various levels of vibe-completeness. Mostly one just kind of yanks on my attention a bit more than the others and so they end up getting a little neglected. I'm fine with it though, I love having all these little forever projects of mine finally coming to life. My worry is kindof the opposite, what happens when I've finished all the things. Will I run out of ideas? I hope not, but already some of my pet projects have reached a level of completeness where I just cannot see anymore to add, for me they have reached a level of done. That frees me up for the next project but what if I run out of projects!
gritspants 14 hours ago [-]
Then just set aside some time to be bored. People generate some of their best ideas during this time.
johnvanommen 13 hours ago [-]
The one thing I miss about driving to work.
pixl97 14 hours ago [-]
Get another hobby like gardening?
crucialfelix 11 hours ago [-]
I was getting frothy and feeling stress due to juggling sessions. I switched to managing my backlog (Obsidian base), writing specs, launching agents in the background. I review and make changes,merge and release.
It's a fixed cycle and I optimize to maintain relaxed engagement.
Rate of features and fixes went up a lot.
zkmon 23 minutes ago [-]
The myth you fell into is, assuming that the AI is here to increase your personal productivity. No. Think of AI as a vendor who can provide you with contractors that can code for you. 20 years back, if you are promoted as a manager and approved with a budget to hire 10 contractors, what would you do? You would hire 6 coders, 3 testers and a project manager. Your would mostly interact with the PM giving feature specs, and checking out the progress. You might also ask someone to do the code reviews. You won't sit with every coder and go through the code every day.
AI gives you coders, not some "tool" that you can use to make yourself a faster coder.
Skinney 2 hours ago [-]
> So logically, if AI can help us complete tasks 2-100x faster than before, we should be UNDERWORKED and experiencing ZERO burnout, right?
Got to admit, I stopped reading here.
In my experience, burnout isn't related to the amount of work, but to your confidence in being able to do your job and if you find your job meaningful (like, does it even matter?).
I'm probably doing twice as much work now compared to the period just before I burned out, but I'm also nowhere near a burnout. Part of that is general experience, but it's also because I feel like I know what I'm doing (so, no imposter syndrome) and because I've chosen my job based on what I find meaningful to do (is it ethical? does it make a difference in society? is it interesting?).
I understand why LLM assisted development can lead to burnout. You now have a machine that "does most of the work for you". It's a gateway to questions like "how good are you really at your job?" and "anyone could push these buttons, couldn't they?" and "is this what the rest of my life should be?". It probably also reduces how interesting or fulfilling the job is for many people. You've been reduced to a cog in the machine, and you might be questioning your ability to be anything but.
koiueo 25 minutes ago [-]
I mostly agree with your observations, but in my experience, if you're spread very thin, you may be nearing the sudden burnout onset.
You feel motivated, full of energy, your juggle millions things at once, and then stumble once, then another time. Then your mistakes become more frequent. And you don't even realize you make them, others do... Until eventually you no longer operate efficiently.
Can take a few years to develop.
Take some rest. Especially if you feel productive like never before. It's gonna be hard to shut down for the first few days, so it should be at least a week of rest. Better two.
Chances are: after coming back you'll immediately notice a dozen of stupid decisions you've made.
staticvar 9 hours ago [-]
I'm not sure that AI helps us with that last 1%. Just the 99% which is why, instead of having a backlog of 0% projects, we have a backlog of 99% projects. My hope is that we're more effective prioritizing a backlog of 99% projects than 0% projects.
Gigachad 2 hours ago [-]
Turns out the last 1% is 90% of the work
taosx 7 hours ago [-]
I will never believe the premise of 100x boost from AI, why are we still pushing this narative? Yes, AI is amazing in small, constrained, focused pieces of code but the code is nowhere fit for production and the last 10% needed to ship shows that the 90% that's already been done by AI is absolutely trash. Hacks on top of hacks.
Is no one trying to ship polished things to customers anymore, will each of us have a hacky, bugged version of the same thing with different quirks?
--
My first ever software project even before I worked as a swe had less bugs and frictions than all recent projects where AI was used. Some people like mitchellh seem to know what they are doing (I have not taken a look at ghostty's codebase as it's in zig) so I sometimes get the feeling I'm holding it wrong but in the end everyone around me seems to have similar problems with shipping.
jalev 15 hours ago [-]
It's wild we're seeing people rediscover the same solution to the same problems we've had forever: being precious about your darlings.
Code generators reduced the friction for implementing every shitty idea someone has ever had, but because developers seem to have never experienced throwing shitty ideas away (because if it was written in code it _has_ to be important right?) they treat everything coming out of the Codegen as a precious idea that eventually builds up to clutter one's brain leading to Implementation Fatigue the author experienced. The solution? Go through that same process but focus on one idea at a time and make it good.
It does make me wonder if the people experiencing this had hobbies outside of software engineering (let's say, anything creative) they'd be able to spot the signs earlier.
SubiculumCode 13 hours ago [-]
Funny. In writing, the advice is to "kill your darlings". Don't let a particular paragraph that you love a lot stop the whole story because it doesnt fit.
15 hours ago [-]
pietroppeter 15 hours ago [-]
Appreciate the quote of the Essentialism book by Greg McKweon, which I am currently reading. Funnily enough I decided the book when I found out (on Imprint app) that one of the key values of the “essentialist” is playfulness. I was sold.
robomartin 3 hours ago [-]
> I had something like 40 “proof of concept” projects going on
Right. That's the problem. In the non-coding world it's the idea that your pile of crap expands into the available space. So, if you get a garage that is twice as large, it will eventually be just as overloaded and piled-up with crap as the first, smaller, space.
The secret to happiness is to control how much crap you put on your pile. It can be that simple. Or, live with the crap you have and maybe a little bit more, but not 40x more.
yearesadpeople 12 hours ago [-]
> Now that AI makes things 2-100x more efficient
What things, why, and how did you measure this?
dominotw 10 hours ago [-]
op probly sucked at writing code in 2022 and now has the illusion that he is suddenly able to.
thing is that writing software wasnt that hard even in 2022 with all the cloud, frameworks and stuff
BatFastard 14 hours ago [-]
I totally agreed with Rick. A.I is a rabbit hole revealer. And it encourages me to go down them with its "Great Idea" spam.
Edit: Reveler vs Revealer
daveguy 11 hours ago [-]
It's good that you clearly see the "Great Idea" spam for what it is. That comes from the reinforcement-learning human-feedback (RLHF) that is used to keep you coming back for one more pull.
spiderfarmer 14 hours ago [-]
I launched 1 side project that could potentially help my main project every week, for the last couple of months. To me, it’s not draining at all. I love that the main barrier, time, has been removed. The nagging feeling that I am missing out, did not try, should be working on something, seeing competitors launch my idea. All gone.
I love it. Will any of them succeed? It’s early days, but seeing potentially life changing growth in multiple areas at once gives me a lot of energy.
vouaobrasil 12 hours ago [-]
Keep in mind that if a large mass of people experience a boost in activity and energy to explore new topics, those at the top will simultaneously want to use up all that energy by making us work harder as well. The end result only seems like a benefit to you because the other side of the equation hasn't caught up.
jdkee 11 hours ago [-]
AI slop.
PunchyHamster 15 hours ago [-]
> So logically, if AI can help us complete tasks 2-100x faster than before, we should be UNDERWORKED and experiencing ZERO burnout, right?
No. you got lied to by AI bros. 100x times the code (that if you burn enough tokens that you could actually hire someone to go thru your ideas and make them...) is not 100x times the productivity
stavros 13 hours ago [-]
That's not the reason, the reason is that you get paid for eight hours, and that's how much you'll work, regardless of the number of tasks you complete in those hours.
esseph 7 hours ago [-]
Ah, you're not on salary in the US, I take it.
saghm 4 hours ago [-]
Not having an exact number of hours works in both directions; there's no lower or upper bound on how much you're expected to work, and with most tech jobs being at-will employment, it's not like they couldn't fire you with virtually no notice if they decided you weren't working enough. "Work as little as you want, if you think you can get away with it" is not a game of chicken that most people will end up being super confident in playing.
bluefirebrand 6 hours ago [-]
I dunno about in the US, but being on salary in Canada I bet I've averaged well over 40 hours a week in my career. I know the usual trope is people on salary work as little as possible but it's not true for me. And that's not a flex. I'd much prefer to work less, but deadlines are deadlines and they're always calibrated to cost me my evenings and weekends, not cause the customer any delays
esseph 5 hours ago [-]
> I know the usual trope is people on salary work as little as possible but it's not true for me.
Yeah. It hasn't been that way for 25y or more in the US. Lots of 60-80h weeks.
Long story short, I think we’re in a phase where the organizational value function is lagging behind the tech. A “proof of concept” used to be correlated with “proof of work” and some amount of domain understanding, but I think now what we need is a focus on “proof of understanding” or else you’re probably just wasting tokens on a baby version of the problem. A decent proxy right now is that if you have zero external dependencies then your solution is probably a toy.
Now anyone with enough LLM tokens can move quickly and have a pretty proof of concept in front of management in days or maybe hours. There's a land grab to get things in front of management so you can stake your claim on something. The implementation details are assumed to be solvable by enough Claude sessions and ChatGPT prompts.
Where this falls apart is that the real difficult problems don't scale well with LLM brute force techniques. You need people who understand the problem and know how to drive the LLM agents around properly, as well as when to set them aside and go look at the code and data themselves.
The teams who try to brute force everything with LLM tokens can get a little farther every few months, but for complex problems I've seen enough variations of teams hitting a wall of complexity and tech debt with a team that doesn't know much about how their system works because they've just been asking agents to solve every problem as it comes up. With each iteration it takes a little longer for the agents to come to a solution and the system becomes a little more brittle. Even with our current mega-context-window LLMs you can reach a point where every other change to your big ball of code breaks something else, which requires another agent session to diagnose and fix, which might then break another thing down the line. The refactors to try to clean things up end up breaking even more. Having a zillion tests starts to backfire when the team can't tell which tests are testing valid results and which are baking in incorrect results.
Maybe there's an end game where agents get so good that none of this matters, but I think it's more likely that we're going to have to build up better intuitions about what good execution looks like. The old signals of moving fast are meaningly and potentially even negative now.
This is very similar to how LLMs were already breaking signals in writing. It was (is?) an enormously important proxy (however imperfect) for a bunch of things like: "put effort into this" or "is smart" or "is interested and engaged" or "has an emotion" or "has carefully considered the idea."
Heck, even basic awareness of an issue/detail gets forged, mentioned in the text but never in the mind of the sender.
That's how you get promotions when you don't do anything valuable lol ok done with the cynicism
But hey, I do it. I prebake my own tools to work within the system, a new person joins, and I show them the tools as an example. Instead of learning what it does and why, they just learn how to use the tool (now via claude).
I call it fighting shit with POOP.
At my day job, I use AI to fix config, container, and installation issues so I can spend my time coding instead of struggling to fix mostly other people's mistakes. And really, in this age of python wheels, containers, virtual environments, and fragmented APIs, the cognitive load of doing this by hand would shut me down for the day.
1.5 years in and I haven't burnt out. If anything, I'm ramping up. I'm no longer afraid of adding a web UI, or insane numbers of unit tests, or deploying other people's software.
What I'm not doing is using it to build products, but instead just doing so to augment the supporting stack. All of this is subject to change as the AI landscape evolves.
That's how I understood the article at least.
I believe you misspelled "rip it off."
I guess I shouldn't be surprised that people are using the tools built by ripping off the collective creative works of humanity to rip off individual things, too.
Picasso said that, Jobs quoted it (and to his credit, gave attribution... which I doubt is happening with all of these claude-cloned designs).
I think it was a mistake to add this much complexity to the world of software in the first place, so I'd view AI as a bandaid to a problem rather than addressing the underyling issue. But on the whole, the cost of all this extra complexity, data centers to run AI to fix layers of crud and buildup don't seem to provide much of a net benefit to society (except to those who are at the top and need to see growth to pad their retirement portfolios).
I would suggest not concluding the end of this movie from the first 5 minutes of the story. But then, I really fought against complexity over my career and lost hard. One can either check out as a fossil of the good old days or adapt to the new reality. 6 months ago, AI was about to replace all the engineers and then reality slapped the C-suite hard on that subject as just one recent plot twist.
AI gives you coders, not some "tool" that you can use to make yourself a faster coder.
Got to admit, I stopped reading here.
In my experience, burnout isn't related to the amount of work, but to your confidence in being able to do your job and if you find your job meaningful (like, does it even matter?).
I'm probably doing twice as much work now compared to the period just before I burned out, but I'm also nowhere near a burnout. Part of that is general experience, but it's also because I feel like I know what I'm doing (so, no imposter syndrome) and because I've chosen my job based on what I find meaningful to do (is it ethical? does it make a difference in society? is it interesting?).
I understand why LLM assisted development can lead to burnout. You now have a machine that "does most of the work for you". It's a gateway to questions like "how good are you really at your job?" and "anyone could push these buttons, couldn't they?" and "is this what the rest of my life should be?". It probably also reduces how interesting or fulfilling the job is for many people. You've been reduced to a cog in the machine, and you might be questioning your ability to be anything but.
You feel motivated, full of energy, your juggle millions things at once, and then stumble once, then another time. Then your mistakes become more frequent. And you don't even realize you make them, others do... Until eventually you no longer operate efficiently.
Can take a few years to develop.
Take some rest. Especially if you feel productive like never before. It's gonna be hard to shut down for the first few days, so it should be at least a week of rest. Better two.
Chances are: after coming back you'll immediately notice a dozen of stupid decisions you've made.
Is no one trying to ship polished things to customers anymore, will each of us have a hacky, bugged version of the same thing with different quirks?
--
My first ever software project even before I worked as a swe had less bugs and frictions than all recent projects where AI was used. Some people like mitchellh seem to know what they are doing (I have not taken a look at ghostty's codebase as it's in zig) so I sometimes get the feeling I'm holding it wrong but in the end everyone around me seems to have similar problems with shipping.
Code generators reduced the friction for implementing every shitty idea someone has ever had, but because developers seem to have never experienced throwing shitty ideas away (because if it was written in code it _has_ to be important right?) they treat everything coming out of the Codegen as a precious idea that eventually builds up to clutter one's brain leading to Implementation Fatigue the author experienced. The solution? Go through that same process but focus on one idea at a time and make it good.
It does make me wonder if the people experiencing this had hobbies outside of software engineering (let's say, anything creative) they'd be able to spot the signs earlier.
Right. That's the problem. In the non-coding world it's the idea that your pile of crap expands into the available space. So, if you get a garage that is twice as large, it will eventually be just as overloaded and piled-up with crap as the first, smaller, space.
The secret to happiness is to control how much crap you put on your pile. It can be that simple. Or, live with the crap you have and maybe a little bit more, but not 40x more.
What things, why, and how did you measure this?
thing is that writing software wasnt that hard even in 2022 with all the cloud, frameworks and stuff
Edit: Reveler vs Revealer
I love it. Will any of them succeed? It’s early days, but seeing potentially life changing growth in multiple areas at once gives me a lot of energy.
No. you got lied to by AI bros. 100x times the code (that if you burn enough tokens that you could actually hire someone to go thru your ideas and make them...) is not 100x times the productivity
Yeah. It hasn't been that way for 25y or more in the US. Lots of 60-80h weeks.