I don’t understand the Scrum one. Scrum is also agile with short development cycles, and prioritizes communication with the product owners and stakeholders.
I’ve never heard of lean development, but not a fan of “lean manufacturing,” at least not the way it’s commonly implemented in the U.S. (using primarily temp workers so they can ramp up and down their workforce as needed; and it also exacerbates supply-chain problems).
This goes for most LLM things. The time it takes to get the word calculator to write a letter would have been easily used to just write the damn letter.
Its doing pretty well when its doing a few words at a time under supervision. Also it does it better than newbies.
Now if only those people below newbies, those who don’t even bother to learn, didn’t hope to use it to underpay average professionals… And if it wasn’t trained on copyrighted data. And didn’t take up already limited resources like power and water.
This is what it is called a programming language, it only exists to be able to tell the machine what to do in an unambiguous (in contrast to natural language) way.
This reminds me of a colleague who was always ranting that our code was not documented well enough. He did not understand that documenting code in easily understandable sentences for everybody would fill whole books and that a normal person would not be able to keep the code path in his mental stack while reading page after page. Then he wanted at least the shortest possible summary of the code, which of course is the code itself.
The guy basically did not want to read the code to understand the logic behind. When I took an hour and literally read the code for him and explained what I was reading including the well placed comments here and there everything was clear.
AI is like this in my opinion. Some guys waste hours to generate code they can’t debug for days because they don’t understand what they read, while it would take maybe two hours to think and a day to implement and test to get the job done.
I don’t like this trend. It’s like the people that can’t read docs or texts anymore. They need some random person making a 43 minute YouTube video to write code they don’t understand. Taking shortcuts in life usually never goes well in the long run. You have to learn and refine your skills each and every day to be and stay competent.
AI is a tool in our toolbox. You can use it to be more productive. And that’s it.
I think there might be a lot of value in describing it to an AI, though. It takes a fair bit of clarity of thought to get something resembling what you actually want. You could use a junior or rubber duck instead, but the rubber duck doesn’t make stupid assumptions to demonstrate gaps in your thought process, and a junior takes too long and gets demoralized when you have to constantly revise their instructions and iterate over their work.
Like the output might be garbage, but it might really help you write those stories.
When I’m struggling with a problem it helps me to explain it to my dog. It’s great for me to hear it out loud and if he’s paying attention, I’ve got a needlessly learned dog!
I haven’t been interested in AI enough to try writing code with it, but using it as an interactive rubber ducky is a very compelling use case. I might give that a shot.
I have a bad habit of jumping into programming without a solid plan which results in lots of rewrites and wasted time. Funnily enough, describing to an AI how I want the code to work forces me to lay out a basic plan and get my thoughts in order which helps me make the final product immensely easier.
This doesn’t require AI, it just gave me an excuse to do it as a solo actor. I should really do it for more problems because I can wrap my head better thinking in human readable terms rather than thinking about what programming method to use.
The art style is nice but the content makes no sense. Kanban and scrum are parts of agile. They are not their own systems.
Lean also doesn’t mean you have no money. It’s a system of manufacturing where you cross train people to do the jobs on either side of them so they can pick up slack if needed and keep things moving without hiring more people.
Someone shared this on Mastodon so I’ll just repost my thoughts from there. (Bonus for Lemmy, I was forced to squeeze all my thoughts into 500 characters, so this is the most succinct I’ve been on this site!)
Pretty incredible how little people seem to understand these. For one thing, every method other than waterfall is a subtype of agile methodology. The major distinction is that waterfall has a series of phases from design through building, testing, and delivery that attempts to plan the whole project up front. Agile methods focus on smaller iteration cycles with frequent, partial deliverables.
Something like kanban is designed for continuous delivery: we want to go to mars weekly.
LEAN development is a scam though, that one is accurate.
The author is also hyping up waterfall too much. Agile was created because waterfall has its shortcomings (e.g. the team realizes too late that what they’re building isn’t what the customer wants).
But I also think it also represents how poorly implemented these ideas are. People say they do agile/kanban/scrum, but in reality they do some freak version of these.
It’s barely waterfall planning either. Often there’s no planning, at least no coordinated one.
Currently at my current workplace we lack coordinated planning between teams. It seems like everybody is working in their own directions and it can take months until we get feedback from other teams. Mostly a product management problem.
I agree, but agile and scrum are not meant to be followed to the letter no matter what. So people are doing it right if they notice some part of the process should be changed to make it work for them.
After each iteration, project managers discuss bottlenecks, identify waste and develop a plan to eliminate it.
1st iteration:
Project Manager A: Requiring approval of multiple Project Managers for the same thing is causing a bottleneck. So is having to wait for a specific manager for a specific topic.
Resolution: Let all managers approve everything and need only a single manager’s approval.
2nd iteration:
Project Manager B: There are too many redundant managers. It’s a waste of resources.
Resolution: Get rid of all mangers but one. Actually, let the engineers manage themselves.
I’m a senior dev, and copilot as a productivity tool usually pays for the monthly license multiple times per week.
Whenever I hear someone say it’s useless, that tells me they are either some godlike dev who knows everything already (lol), they haven’t actually used it, they are not good at integrating new tools into their workflow, or they simply haven’t learned how to use it yet.
Whenever I hear that its useless I ask them to show me how they’re using it. Its almost always exactly what’s happening in this comic with just a tiny bit more detail lol. I think a lot of people are stuck under the assumption that a smaller more concise query is better when its really the opposite that is true. The more information you give and the more you let the LLM work through a problem with followup questions, the better the output. Its like a new Jr Dev who knows their stuff, but struggles with asking clarifying questions.
Yeah, I remember the time i had a project manager who’d come over from the construction industry, used construction industry metaphors, and thought everything would be the same.
PO: Someone else figure out how to repeat what he did.
Second developer: Sorry, I tried to make sense of his rocket design but I can’t figure out how to make a copy that doesn’t explode before we even put the fuel in.
This is the experience of a senior developer using genai. A junior or non-dev might not leave the “AI is magic” high until they have a repo full of garbage that doesn’t work.
SO gives you very specific, small examples. GenAI will happily generate entire projects, test suites etc. It’s much easier to get caught into the fantasy that the latter creates.
Makes sense. It’s like having your personal undergrad hobby coder. It may get something right here and there but for professional coding it’s still worse than the gold standard (googling Stackoverflow).
Nah, you just need to be really specific in the requirements you give it. And if the scope of work you’re asking for is too large you need to do the high level design and decompose it into multiple parts for chatgpt to implement.
If you were 100% specific you would be effectively writing the code yourself. But you don’t want that, so you’re not 100% specific, so it makes up the difference. The result will include an unspecified percentage of code that does not fit what you wanted.
It’s like code Yahtzee, you keep re-rolling this dice and that dice but never quite manage to get the exact combination you need.
There’s an old saying about computers, they don’t do what you want them to do, they do what you tell them to do. They can’t do what you don’t tell them to do.
I give instructions to AI like I would to a brand new junior programmer, and it gives me back code that’s usually better than a brand new junior programmer. It still needs tweaking, but it saves me a lot of time. The drawback is that coding knowledge atrophy occurs pretty rapidly, and I’m worried that I’m going to forget how to write code without the AI. I guess that I don’t really need to worry about that, since I doubt AI is going anywhere anytime soon.
Not sure about GP, but that’s basically what we did under “SAFe” (Scaled Agile Framework). PI planning means taking most of a sprint to plan everything for the next quarter or so. It’s like a whole week of ticket refinement meetings. Or perhaps 3 days, but when you’ve had 3 days of ticket refinement meetings, it might as well be the whole work week for as much a stuff as you’re going to get done otherwise.
It’s as horrible as you’re thinking, and after a lot of agitating, we stopped doing that shit.
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