I am a heavy Typora user and I really like it except when it starts to glitch with longer documents (> 5000 words). How is this different from Typora? To be clear, I think it is ok if it isn't, the world is big enough for multiple markdown editors :-)
Also, what does the term "greco-roman" have anything to do with Markdown editors?
I get that sometimes we like to build useless things because they are elegant, or beautiful, or "cool" in some sense of the word. But CMake is not cool in any sense of the word! I can barely use it to write build files, and that too I have gladly offloaded to AI. Sometimes when looking at CMake files in a large project, I become nostalgic about Makefiles, but then I think about what the rewrite would entail, and I resign myself to my fate.
An exercise in understanding gpt2, flexing the author's cmake skills, while demonstrating the absurd complexity of what it allows similarly to 'c++ templates are turing complete' or 'doom on my calculator'.
I have had very similar experience! I wanted to learn Probablistic ML, checked out a couple of MOOCs, but didn't find any that were at my level - some were too advanced, some too beginner level. Claude was unable to one-shot a course, so I am now asking it to generate it module by module. But even here, it is not doing a very good job. I muddle through the concepts that it has written, do a whole bunch of back-and-forth, which tbh is exhausting, and then rewrite everything in my words so it actually makes sense to another human being.
> I get exhausted reading LLM prose
So much this! If I see one more sentence with the words "genuinely" juxtaposed with "load bearing" my head is going to explode!
i’m personally deriving a huge amount of value from the custom materials fable is assembling for me. for example i asked it to write a focused expository math paper on reed solomon to accompany an implementation module that it wrote for me. it’s remarkably useful to steer it to create graphs and diagrams of exactly how you like the material presented. or the bibliography researched and cross-linked with the body or the order you want your questions addressed.
it also researched vision correcting displays for me and i can finally put that idea to bed - i was never really going to pick up an optometry textbook tbh. plus it was able to pull together a bunch of geometric and physical context about light and the eye plugging exactly my personal knowledge gaps.
in general i suspect these materials might not be that interesting to others because they are so custom to my learning style and personal needs and preferences.
these are usually not one shot documents but rather many prompts deep before i get something I’m willing to sit down and read or study. but dramatically quicker than assembling it myself from primary sources. i wouldn’t say it matches master expositors but then they’re not available to write on any topic i happen to need right now.
plus I’ll just have a live voice discussion with the system when i go for a walk and there are still things bothering me on a topic. it takes a little patience but if i’m in the mood it’s amazing.
i generally find that it can help track down specific references if i suspect hallucinations. but especially on factual topics my experience so far has been extremely encouraging.
Good point. Same with me. Despite it being very tiresome, all the back and forth that I do with it really deepens my understanding of the topic. I have been on Opus so far, let me try Fable and see if it gets better. I haven’t tried voice either. Next time I go for a walk I’ll try that!
"carefully architected solution" is not what they are saying. A "buggy big ball of mud" will not generally "do the right thing", if it did, it would not be a "buggy big ball of mud". Straightforward requirements do not imply straightforward solutions. In the early 2000s Facebook wanted a quick way to search for friends updates, a straightforward requirement. Turned out they had to build a full graph DB inside MySQL, not straightforward code at all.
The percentages are different for different types of SWEs, not all SWEs spend 80% of their time on XFN comms. I agree with your larger point that a non-trivial amount of a SWE's time is spent on XFN comms and team alignment. My argument is that if an individual contributor is not spending a majority of their time on problem solving and implementation (including maintenance of legacy code), they are not maximizing their potential. If they are spending 80% of their time on non-coding activity they are better suited for an Manager role (Engineering or Product). At the end of the day, coding is not hard only if you are a good coder to begin with. If you are a good EM/PM then people issues will not be hard (which coders often complain about).
I'm talking from the perspective of working in big tech. Working in a fast paced startup, percentages are definitely different. But alignment/deciding where to spend resources is more important than coding especially the higher you go, the more resources at your disposal (staff+ eng). Junior eng again different percentages.
There does seem to be a need for a semi-deterministic workflow where nodes in the workflow are agentic, i.e., powered by LLMs, but the workflow itself remains deterministic. Lets say my daily workflow is to download a PDF from some website, extract some information from it, and email that information. I cannot just ask an agent to script this workflow, because the website will keep changing, the PDF layout will keep changing, etc. I need a "download agent", an "extract info" agent, and so on which will examine the website, PDF, etc. and generate any one-off scripts everytime the workflow is run.
My solution for that is to use skills and add a omnibus shell script in each particular skill folder that does all the deterministic steps and then write the skill markdown to only use the script, usually passing a command line step parameter to the script. I also usually add a note in the skill markdown that it should monitor how it calls the script and suggest any improvements when the skill is used.
As an example I have a `today` skill that has a today.sh script that can check my email, bug tracker, calendars, custom timesheet system and other systems via the script and then the skill assembles a nice summary of what is happening today along with a suggested schedule.
I guess the tradeoff is doing it in a workflow builder vs just dumping all your requirements in a single agent, With LLMs getting smarter, they can create sub agents automatically if required and take the abstraction away from the user.
I have been grappling with a similar sentiment for a while now. I hate to think of myself as a Luddite, but I love the act of writing code. A blank VS Code in front of me is a beautiful sight full of wonder and possibilities :-) Here is how I rationalize the two - the pride and satisfaction I get from my work depends on how much effort I put in applying some previously acquired specialist knowledge, which itself took some decent amount of effort to acquire. This is why a beginner programmer is just as proud of their temperature convertor as a professional distributed systems engineer of their new 2PC module.
A quote that I read somewhere, possibly by Naval Ravikant, strikes at the heart of this - "a creation without a (human) creator is meaningless".
Neither the Github nor the HF repos have anything on the XiaomiRobotics-1 model or datasets :-( They have a bunch of assets (datasets, code, model, etc.) for XiaomiRobotics-0 however, but I don't know much about that family of models.
Also, what does the term "greco-roman" have anything to do with Markdown editors?
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