Summarizer

> An over-engineered solution (complete with CLI, storage backend, documentation, unit tests) for a trivial problem which that person would've solved by an elegant bash one-liner only 3 years ago. Importantly, I think AI companies are motivated towards the overengineered solutions as they increase the buyer's token spend. I'm not sure how we can create incentives that optimize for finding the 'right' solution, which may be the cheapest (the bash one-liner). Perhaps a widely recognized but not overly optimized for benchmark for this class of problems?

> Importantly, I think AI companies are motivated towards the overengineered solutions as they increase the buyer's token spend. Yes that, and also, the more complicated the solution, the more likely no one reads or reviews it too carefully, and will instead depend on an LLM to ‘read’ and ‘review it’ Even ignoring token costs, there’s a high incentive for LLMs to generate complex solutions, because those solutions generate demand for further LLM use. (You don’t really want to review that 30,000 line pull request by hand , do you?)

Sure, I agree, but now longer/stuffier things cost half as much as shorter things. In most cases, that cost isn't worth it.

I'm starting to see pushback for this. I know a Product Manager that was fired for padding his documentation with AI to the point there were mistakes and wasted work due to AI hallucinations.

It’s the Red Queen’s Race, where we all run as fast as we can to stay in exactly the same place.

> then would they even notice if the code works or not? it's literally their job to ship functional product features...

Everyone's job is to please their manager. Their job is shipping functional product features only if that's what their manager likes. In functional companies, that should be the case. There aren't many functional companies.

> Everyone's job is to please their manager. Indeed. I've spent my professional career seeking out positions at companies of increasing prestige and technical renown, each with a higher reputation for professionalism and performance than the last. And yet this invariant has held in every position. As far as I can tell, the only difference between each company has been the quality of the manager I was supposed to please, which I have noticed (perhaps predictably) is not strongly correlated with the company's reputation or success.

Don't forget that they're also functionally structured. The managers don't own products or features, they manage functions (engineering, sales, design). And in practice, they usually only manage people, with little control over the function. So the managers aren't particularly interested or tied to shipping product features. The PM maybe, but they don't have reports or own much.

In my last company, what my manager liked was an increase in AI adoption metrics, because that’s what his boss likes.

The practical part of their job for them is to show up and to get paid. Who cares about features or functional - of whether they even know what functional means in that case? That's how it looks more and more...

Because the reviewer ends up doing the real work actually checking it works. The laziness is offloading work down the line.

That’s what this whole thread is about. Appearances of productivity, laziness, and the offloading of real work downstream by sending of “looks good enough” ai generated work.

> If you are going to hire an employee to do work on your behalf, you are responsible for their performance at the end of the day. So, what you are saying is that I should fire the bottom N% of underperforming agent instances? You know, like employers do as opposed to taking any responsibility?

> Reminded me of when I had to be extra wordy to meet the 1000 minimum word limit for my high school essays. Minimum word lengths are the greatest dis-service high school and college have ever done to future communication skills. It takes years for people to unlearn this in the workplace. Max word counts only please. Especially now with AI making it so easy to produce fluff with no signal.

I write the words that I hear in my head, as though I am speaking. With the exception of timed, in-class essays, I always turned in papers far in excess of any minimum during high school. In college, I took a constructive writing course because I thought "Hey, easy A!" After the second or third week, the professor told me that, while the class had a word minimum, I would also be given a separate word maximum . She said I needed to learn brevity and simplicity, before anything else. The point being: I was able to cruise through high school with my longwindedness as a cheat code, never stressing about minimum lengths, despite my writing being crap in other ways. Although I have regressed in the two decades since, it helped me a good deal. I am grateful to that professor for doing that.

> It can take weeks of work to produce a 500 word product vision document. Don't you get dinged as a slow performer? Management expects x5 speed on everything now that AI is available.

> Don't you get dinged as a slow performer? No because the document is not the work. Management wants someone to figure out the solution to their problems. The document is just a step in solutioning. Without the doc, others would have to re-do all that work if you get hit by a bus. Or you’d be stuck in endless meetings conveying the vision instead of figuring out the next problem. Document length is inversely proportional to the quality of your thinking/insight. When you create fluff, everyone can see you didn’t do the work.

Minimum word lengths were really a terrible idea and I wonder what arguments were used to get all the teachers to buy into that system.

Considering that many high school kids won’t want to put in any effort at all, how else do you convey the amount of detail and effort you expect for a given writing assignment? It’s an imperfect proxy but I can’t think of a better one.

Yeah. 1000 words is not a long essay that requires padding, and any competent teacher marks an essay with 1000 words achieved mainly by repetition and bad sentence construction much lower than one discussing the subject matter in a suitable level of detail, and probably lower than a better- written essay which gets marks deducted for only having 985 words. Since "write an essay" can be anything from three paragraphs to a 50 page paper and the teacher probably doesn't think either is the appropriate response to the task, some sort of numerical guide is a good starting point, even if a fairly wide range is a better guide than just a minimum... (plus actually there are real world work tasks involving composing text that fits within a certain word range, and since being concise and focused isn't AI text generation's strong suit, I'm not sure those work tasks will disappear...)

Yeah, this is seemingly the only effective proxy for "write with some amount of depth." If the word count gets BS'd then it will be obvious when reading the output.

> Yeah, this is seemingly the only effective proxy for "write with some amount of depth." If the word count gets BS'd then it will be obvious when reading the output. My high school professors had a really good solution to this: Minimum word lengths but you have to write the essay in class by hand. You have 2 periods. Some of us still write a lot but having limited time and space (4 pages) really put a hard limit without saying so. In higher classes they started saying “I’m gonna stop reading after 3 pages so make sure you get to the point”

With rubrics, or more simply the teacher could hand out an example essay at the start of the year that conveys the style and level of detail they are looking for when they assign an essay. Then they can refer to that when they make an assignment. Implicitly that gives a word count or number of pages, but allows for marking down for "too much repetition" or "needs more detail"

The ambiguous "needs more detail" thing would lead to a lot of students making it too brief in good faith, too long in good faith and both be frustrated and angry. You can write really good mini essay on a topic. And you can write really good super long essay on the same topic. Demanding that students mind read is not a good strategy. Specifying expected length, checking for it is a good strategy. Teacher should also check for other things - whether paragraphs logically follow, grammar, sentence structure, you name it. But dont make them guess.

When the teacher goes to grade it? If you turn in one sentence with or without a minimum your getting an F...

Many schools these days don't allow an "F" grade if the student makes any effort at all.

Have a second of critical thinking on this topic will make it abundantly obvious why this line of questioning is anti-education and anti-intellectual. You write in school to practice. No just composition, but grammar, spelling, individual sentences. Practice requires volume. Subject yourself to a classroom of kids that you must teach to write, and throw out minimums. Will some students do fine? Sure, of course, and what of the others that turn in one sentence? That never grow? That have to go into the math class and hear their idiot parents say "why are you learning that we have calculators"

Why not have the students write more essays instead?

> Subject yourself to a classroom of kids that you must teach to write, and throw out minimums. Strawman argument; the correct thing to do is not to throw out minimum word count and leave it at that, rather to emphasize the role of brevity and concision while still being sufficiently thorough. It's widely understood that LOC is a poor measure for many coding purposes, so it shouldn't be controversial that word count is an equally flawed measure for prose.

It can help to force depth into a topic that requires it, and more expression and emotion into writing where that is of value. It also forces the writer to think more deeply about the topic and organize their thoughts. While I hated it in high school, but think I better understand it now. I think part of the problem is they never explained the "why" or the "how", just the requirement. I wasn't able to write anything more than a page or two without extreme difficultly until college when the requirements went up to 30 pages. In theory, someone who can write a 30 page paper could effectively distill it down to a short memo when needed, summarizing their primary point(s). Someone who can only write short memos would have a hard time writing something longer one day if/when required. I was trying to do a knowledge transfer one day, opened up Word, and just typed 20 pages on everything I knew about a tool we used heavily, but wasn't documented anywhere. I don't think I could have done that before I was forced to write those longer papers in college.

Where I encounter it at the higher education level is that academic-level research almost universally has maximum word counts or page counts rather than minimums: if you think you can get your point across in fewer words, you should. No reviewer is going to object to the paper being too short, so long as you succeeded in making your case. John Nash's Ph.D. Thesis is notorious for being short: it's still 27 pages (typed, with hand-written equations and a whopping total of two citations) but that's an order of magnitude below average. On the other hand, most of us don't invent game theory. Students used to minimum-word-count essays sometimes have to do some self-retraining to realize that the expectation is that you have more that you want to say than you have room to say it, and the game is now to figure out how to say more in fewer words.

Journalists and writers are often given a deadline and a target length. "Give me 500 words of copy by the end of tomorrow." The editor and publisher of a magazine need to get all words and graphics ready by a strict and regular deadline.

It’s easier to judge an objective output like number of words than subjective like quality. Same as lines of code, etc.

I guess, but have you actually encountered a teacher grading an assignment solely based on word count? I certainly wish more teachers encouraged parsimony and penalized fluff and bullshittery, but I'd be surprised to find them doing it outside of some narrow cases where the point is just to make you write something at all. Tthey generally want to encourage their students to engage with the topic at a certain level and practice the thinking needed to research, structure, and implement an argument of a certain length. They want you to put at least 5 pounds of idea in the 5-10 pound idea bag. If you're convinced you've hacked word economy and satisfied the assignment except for this goshdarnpeskyminimumwordcount, you're probably misunderstanding the lesson the instructor is willing to read through a bunch of bad writing to impart and cheating yourself.

That's actually the trick. If you assign word count, MLA style, grammar, you just have to look for the errors. You don't have to engage with the ideas at all, or provide conversational feedback - just cryptic notes in the margins, like "???" or "awk"

The idea was to get people to include more substance. Instead of just saying "Washington crossed the Delaware" to get students to include reasons why, impacts, further narrative, etc. IDK if it was effective or not. Probably at least a little; there's only so many ways to rewrite the same thing over and over. I know in my case though I submitted essays below the word count a few times, but since I actually included the content they were looking for I didn't have any problems

We had maximum word counts

Well, in many layers of overhead in companies people operate at the level of high schoolers, so it is no surprise unfortunately, that the output comes across like that too.

it was only after I had to manage others that I realized the logic for a lot of these simplistic metrics and rules. they are in place to hold accountable the worst performers. a simple example is when i introduced flexible work hours. it was fine with most people, but there are always a few members that abuse the system. they stretch it to the very limit to what can be interpreted as "flexible". as a manager it posed a dilemma for me. i didn't want to take away this privilege just because of a few abusers, but it was both unfair and set bad precedents if I allowed them to get away with this. and let's say they couldn't be easily fired. most of my peers simply ended up going back to a system where people punched in and out.

Could not you just say to those few: 'you can't because I do not trust you'? You are the manager after all, your job is not to make them feel good but to make them work.

I remember my first semester university writing class, when on the first day the teacher told us we had learned to pad our writing in high school, and now we were going to learn how to be short and concise because every assignment would be limited to one page.

Whenever I see AI-generated content put forward for my attention, I extract myself from the situation with the minimum possible time expenditure from my side. It's some sort of a leverage: "I spend 5 minutes prompting, so that you could spend 30 minutes reviewing". Not gonna happen LLM buddies.

I recognise it from regularly talking with fellow programmers at the local tech meet-ups. At least in my area, the work places with result-oriented policies were and still are in the clear majority, and only big companies with likewise big financial reserves could afford to pursue the economically wasteful route of process-oriented policies.

You have described exactly the situation of almost all of my clients. And in some way it is good to see our business model validated as we help steer organisations at this level, also technically. I would only add that the quality of software has improved significantly. From my perspective, the bar for quality at most organisations like this is low, extremely low.

Sadly I don't think management would go and build it properly, this sort of thing happens frequently where the prototype is put directly into production because why waste time redoing something that already exists and works. Just got to clean it up a bit, round off some sharp corners, and put it into production post-haste.

There’s no need to defend LLMs. The article is making the point that a colleague who shouldn’t have been anywhere near specifying work for LLMs to do, was able to fake it and get rewarded for it.

I increasingly see “AI” as a sort of virus tuned to target management, specifically. Its output is catnip to them, and it’s going to be unavoidable for those who want to look good to superiors and peers (i.e. the #1 priority for managers) even as it adds no actual value whatsoever to what they do. People under them, too, will have to start burning tokens on bullshit to satisfactorily perform competence and “doing work”. Meanwhile, none of this is actually productive . It’s goddamn peacock feathers. It’s like some kind of management parasite. I’m not even sure at this point that it’s going to lead to an overall productivity increase whatsoever for most sectors, because of this added drag on everything.

The rest of the work is inventing new ways to increase their compensation.

Things have probably always been like that, agree. I often try to see AI as a catalyst, that accelerates what already is. In a good culture, with high competence and trust this can yield increased output (to some degree at least) and in a bad culture it will accelerate and expedite the dominating traits instead.

Honestly, the most impactful thing I've seen AI do for any workplace is serve as the ultimate excuse for whatever pet thing someone's wanted to do, that can't stand on its own merits, and what they really need is a solid excuse. Rewrite that old crunchy system that has had 0 incidents in the last year and is also largely "done" (not a lot of new requirements coming in, pretty settled code/architecture)? It's actually one of our most stable systems. But someone who doesn't even write code here thinks the code is yucky! But that doesn't convince the engineers who are on-call for it to replace it for almost no reason. Well guess what. We can do it now, _because AI!!!_ (cue exactly what you think happens next happening next) Need to lay off 10% of staff because you think the workers are getting too good of a deal? AI. Need to convince your workers to go faster, but EMs tell you you can't just crack the whip? AI mandates / token spend mandates! Didn't like code reviews and people nitpicking your designs? Sorry, code reviews are canceled, because of AI. Don't like meetings or working in a team? Well now everyone is a team of 1, because of AI. Better set up some "teams" full of teams of 1, call them "AI-first" teams, and wait what do you mean they're on vacation and the service is down? Etc. And they don't even care that these things result in the exact negative outcomes that are why you didn't do them before you had the excuse. You're happy that YOUR thing finally got done despite all the whiners and detractors. And of course, it turns out that businesses can withstand an absurd amount of dysfunction without really feeling it. So it just happens. Maybe some people leave. You hire people who just left their last place for doing the thing you just did and now maybe they spend a bit of time here. And the game of musical chairs, petty monarchies, and degenerate capitalism continues a bit longer. Big props to the people who managed to invent and sell an excuse machine though. Turns out that's what everyone actually wanted.

> I think for a lot of companies, AI is a destabilizing force that their managerial structure is unable to compensate for. Absolutely. Giving a traditional company AI is like giving an unlimited supply of crystal-blue methamphetamine to a deadbeat pill addict. It enables and supercharges all their worst impulses. Making a broken system more 'productive' doesn't do shit to make the users better off. The work output everyone produces doubles, but the ratio of productive to net-negative work plummets.

I think this may be a consequence of hiring for a position with the word “architect” in it. It implies the need for complexity vs. Getting a gaggle of senior devs together and letting them sort out CI/CD and patterns as they are needed. In a lot of cases, an architect is not needed but must justify themselves.

Yeah, the developers who will argue and teeth-gnash about using an ORM for weeks on the hope it will save a few hours perceived as boring or obvious are, simultaneously, annoyed and upset at being told to save time with super tools that save time and effort… Pay no attention to the software output or quality or competitive displacement of the people selling you tools. LLMs, like cheesy sales strategies, are something so lucrative the only thing you can really do is sell them first come first serve to other people. Makes so much sense. Why make infinite money when you can sell a course/tool to naive and less fortunate companies? So logical.

He doesn't care. When c suite gets fired they get like half a million in severance and go rinse and repeat somewhere else

I usually use git and open source tooling, but I've been working with our internal tech stack recently. It includes an editor with AI-powered autocomplete, and it drives me crazy. It populates suggestions nearly instantly, which is constantly distracting. They're often wrong (either not the comment I was leaving, or code that's not valid). Most of the normal navigation keys implicitly accept the suggestion, so I spend an annoying amount of time editing code I didn't write, and fighting with the tool to STFU and let me work. Sometimes I'll try what it suggests only to find out that it doesn't build or is broken in other stupid ways. All of this with the constant anxiety to "be more productive because AI."

> related, i feel it's likely teams that go "all in" on agentic coding are going to inadvertently sabotage their product and their teams in the long run. They are trying to get warm by pissing their pants.

What is your company producing? Do you think it's worth being passionate and enthusiastic about? Or is it perhaps reasonable to just do the bare minimum to get a paycheck? People see that it's bullshit anyway and the job doesn't result in any actual positive impact in the world. So why care?

Do you have any suspicion of why they are not putting in the effort then? Do you think they think their output is better this way? Or maybe actually they don't really give a damn deep down?

is it a net-win for the company? Are the AI-TOD any good?

> The article almost reads like a practical manual for increasing perceived productivity inside a company. I think the truth is that at many (most?) places, perceived productivity and convincing is all that matters. You don't actually have to be productive if you can convince the right people above you that you are productive. You don't have to have competence if you can convince them of your competence. You don't have to have a feasible proposal if you can convince them it is feasible. And you don't have to ship a successful product if you can convince them it is successful. It isn't specifically about AI or LLMs. AI makes the convincing easier, but before AI, the usual professional convincers were using other tools to do the convincing. We've all worked with a few of those guys whose primary skill was this kind of convincing, and they often rocket up high on the org chart before perception ever has a chance to be compared with reality.

I agree. but,In practice, the important thing is that, whatever one thinks of management, you still have to speak in terms they recognize and want to hear. The target changes, but the mechanism is similar. This is often criticized, but it is also necessary even in ordinary conversation. The core skill is the ability to guide the agenda toward the place where your own argument can matter. I do not believe that good technology necessarily succeeds. Personally, I see this through the lens of agenda-setting. Agenda-setting matters. I am usually a third party looking at organizations from the outside, but when I observe them, there are almost always factions. And inside those factions, there are people with real influence. Their long-term power often comes from setting the agenda. From that perspective, AI slop looks like a failure of agenda-setting around why the market should need it. They encourage people to exploit human desire and creative motivation. But the problem is this: the market still wants value and scarcity. From that angle, this mismatch with public expectations may be a serious problem for the AI-selling industry.

One important part is not expanded on - incentives. If you really think about it that is the crux of the problem. If I am recognized for creating documents, PRs, features, decks, token use, and NOT for doc/PR/deck reviews or feedback or fixing features, then the outcome is what we see now. An example of a new feature in the company goes the following way: - some request is raised by person1 - PR is generated with an "agent" by person2 - PR is reviewed using an "agent" by person3 - feature is merged and shipped - person1 is happy and records a video with a feature to be shown to the clients - in a next call with the leadership this feature is declared as a success It all looks good until you look at the implementation, not only that there is very little time to intervene. I find myself recently trying to quickly review PRs before they get quickly merged, just to be on a safe side as people do not even look at the code.

You already realised that you aren't paid to review code manually. Why waste the time? And maybe even get the wrath of your management by "wasting" time?

> He produced a great deal of code, a great deal of documentation, a great deal of what looked, to anyone who did not know what to look for, like progress. He could not, when asked, explain how any of it actually worked. Solution: managers need to ask 'how does $THING_YOU_MADE actually work?'. Pre-AI, it could be taken for granted that if someone was skilled enough to write complex code/documentation then they have a sound understanding of how it works. But that's no longer true. It only takes 5 minutes of questioning to figure out if they know their stuff or not. It's just that managers aren't asking (or perhaps aren't skilled enough to judge the answers). On the issue of over-enthusiasm from upper management, this may be only temporary since it makes sense to try lots of new ideas (even the crazy ones) at the start of a technological revolution. After a while it will become clearer where the gains are and the wasteful ideas will be nixed.

>Solution: managers need to ask 'how does $THING_YOU_MADE actually work?'. "Claude please tell me how $THING_YOU_MADE works in easy to understand language so I can explain it to my manager." Memorise that and there you go. If the manager doesn't know how it works and has to trust the engineer, what are the chances that a memorised articulate explanation will satisfy them? The issue (like most corpo issues) is one of incentives. Everyone's incentivised to do more work more quickly for a cheaper price. It's very fast to generate output but very slow to properly vet it. What could change the current dynamics is if generation becomes way more expensive. Maybe that will happen because the token economy starts being subsidised? Maybe someone will eventually establish a monopoly on the agentic coding market and will start squeezing companies dependent on them?

If people were incentivized to solve problems with least amount of token spend that would help.

I think the author is describing the new incarnation of the Death March. In the Death March, contributors know that an active project will be dead-on-arrival, or cannot be redeemed. Maybe a small difference here being that the AI-equipped contributors won't be aware of the project status (i.e. futile). Maybe this means AI has democratized Death Marches.

This is what makes measuring productivity so hard. Let's say you're a worker that is responsible for updating a status of an order with a bunch of metadata. One day, 100 orders come in for you to update. The next day, you get 50 orders to update. Did your productivity just get cut in half? If you get 200 orders on the third day, did you just quadruple your productivity from the previous day?

Problem is that it does not produce better or more work, it actually shifts the work to a different/future engineer. Today’s slop which gets engineer 1 a promotion, is engineer’s 2 problem next month when they are oncall and the codebase makes no sense. Your horse riding analogy, is like riding a horse into battle without your weapon because it’s slowing you down. Sure you got through the enemy first by outmanoeuvring, but you missed the point all together. Maybe you got a shiny medal but all your mates are dead.

External success for any business is defined as dominating the peers in selling. People call it as "wins". This percolates into internal context as well. Business units compete with other, teams compete, and peers within a team compete or performance ratings. If you say you never think of competing with your peers, you are probably not being honest.

But it's a team sport. For example, in Dota 2 you should be trying to dominate your opponents. If you are trying to dominate your teammates instead (by prioritizing better KDA) you are most likely ruining the game.

Quality of work is not the goal? What is the goal, then? Maximizing profit for the corporation? I would not want to work anywhere where that is the only goal, even at the employee level. Maximizing profits is not very popular at the moment, for good reason, look at what it's done to the world.

If profit is not the root goal, only hobbies exist, not work or any business. Quality is a means for profit, never the root goal. People pretend that quality and performance are the root goals, because they don't want say the fact that those two are the means for profit. Even for opensource, the quality and performance are desirable aspects only because success of that opensource is directly tied to it's usage in profit-oriented products.

You have it backwards. Why is profit a goal? It's nolever a goal in and of itself, it can only ever be an instrumental goal. "With profits, we can achieve <goal>". If profit is the main goal of all economic activity, then we are doomed to destroy humanity and the environment.

Maximizing profit for the corporation is the goal of any corporation by law, isn't it? Apparently not in the US, but for example the Finnish law explicitly states that the goal of a corporation is to generate profits for the shareholders. If you for example give away company assets for free, it can be considered breaking the law. This probably is just culturally different understanding of the phrase, because US corporations indeed feel to act greedy, and there is no similar level of protection of the employees. However, the thing is, in the long term, the business has to make profits to be sustainable. If the company does not make profits, it will die. Its the short term thinking that breaks down companies. You can maximize profits and be ethical at the same time, if the goal is to do it in the long term. I do understand that the "maximizing profit for the corporation" is a synonym often for short term thinking and vulture capitalism, but for me it meant something else. This is actually quite fascinating now that I think of it, because this phrase means completely different things in different cultural contexts. So I guess the trigger is that "maximize short term profits over long term sustainability" is the kind of company where I'd never work for.

Oh I'm aware of Finnish law on the matter (moikka), and that is my point. I think the LLC (OY), which is the political institution that creates this profit maximizing incentive, is _the_ main driver of the current multi-crisis situation that he world finds itself in. LLCs and the profit motive will not save us from climate change, they will drive us deeper into it. Sustainable human living and continuous economic growth are not compatible.

> It doesn't matter if it's slop as long as it works I agree with most of what you said, but that statement doesn't take the time dimension into account. Slop accumulates, and eventually becomes unmanagable. We need to teach AI to become lean engineers too.

Back around 2005, I worked with a guy who was trying to position himself as the go-to expert on the team. He'd always jump at the chance to explain things to QA and the support team. We'd occasionally hear follow-up questions from those teams and realize that he was just making things up. He was also had a serious case of cargo-cult mentality. He'd see some behavior and ascribe it to something unrelated, then insist with almost religious fervor that things had to be coded in a certain way. He was also a yes-man who would instantly cave to whatever whim management indicated. We'd go into a meeting in full agreement that a feature being requested was damaging to our users, and he'd be nodding along with management like a bobble-head as they failed to grasp the problem. Management never noticed that he was constantly misleading other teams, or that he checked in flaky code he found on the Internet that triggered multiple days of developer time to debug. They saw him as a highly productive team player who was always willing to "help" others. He ended up promoted to management. Anyway, my point is that management seems to care primarily about having their ego boosted, and about seeing what they perceive as a hard worker, even if that worker is just spinning his wheels and throwing mud on everyone else. I'm sure that AI is only going to exacerbate this weird, counter-productive corporate system.