The use of Claude Code with my day job has been quite different. In my day job, I understand the code and review it carefully, and CC has been a big help.
935 karma · joined May 25, 2011
The use of Claude Code with my day job has been quite different. In my day job, I understand the code and review it carefully, and CC has been a big help.
I like this take. I feel like a significant portion of building out a web app (to give an example) is boilerplate. One benefit of (e.g., younger) developers using AI to mock out web apps might be to figure out how to get past that boilerplate to something more concise and productive, which is not necessarily an easy thing to get right.
In other words, perhaps the new AI tools will facilitate an understanding of what can safely be generalized from 30 years of actual code.
> People who stress over code style, linting rules, or other minutia are insane weirdos
I feel like programmatically enforced linting is like keeping a shared house clean. Suppose you live in a house with roommates. You wipe off the counters, you clean up after yourself, you put dishes in the dishwasher, so that the house is tidy and pleasant. If there's a lint or style rule that requires judgment and is hard to enforce programmatically, perhaps better left as an occasional PR comment.
Programatically enforced linting also has the benefit of removing degrees of freedom that aren't very important and don't merit getting bogged down about.
https://github.com/emwalker/digraph
If you can crowdsource the indexing, you get yourself a manually curated search engine with a nice topic graph that can be traversed. A piece of this puzzle that hasn't been tackled yet is a reputation system to keep the signal-to-noise ratio high and deal with spam.
> What’s an example use case of where you use that system to find a link?
An example use case is that I come across some interesting long-form article on a topic I'm following, e.g., Shackleton's expedition, that's published on a nice website and that I don't have time to read. I can just drop the link in the right topic and get back to it without too much difficulty. Or that's the hope, anyway. (Doesn't always work out that like that.)
Another thing I'm interested in is what the topic structure ends up looking like as it's more fully fleshed out. So sometimes I'll drop in random links even if they're not that interesting, just to build out the topics.
It keeps a history of every change to the graph in Git, so one day you could potentially implement some form of time travel and see what the graph looked like at an earlier point in time without too much difficulty.
I have used the app every day for years. I feel like there's something promising there that is of general interest, but I have not figured out how to communicate the value.
After tackling the refactoring of a complex Rails app that has a rules processing engine implemented on top of ActiveRecord, the true cost of Ruby's lack of static typing has become apparent to me. It's clear now that you can get a web app up and running quickly in a framework like Rails (as one example of a convenient, low-friction framework). But once you need to turn it inside out and make significant changes to the implementation, you're walking on egg shells and relying on previous devs to have built out good test coverage. A web app written in Rust would be easier to refactor in important ways at this point in the life of the app. It is clear there was a cost to using Ruby, but also that it was deferred.
On the backend, at least, Rust would be a significant improvement over Ruby, for example, once a business has gotten past the initial prototyping phase. I've spent years in Ruby development, and the duck typing makes refactoring a production system scary and drama-prone. No matter how carefully you proceed, there will be gaps in test coverage, and you'll regularly see new bugs in production from the refactoring work that would never happen in a typed language. I would gladly work in Rust over Ruby in a web development context. (Although my preferences lean towards Rust, there are no doubt many other typed languages that could do a good job here as well.)
Agreed. It's like being able to call up a map on Google Maps for an area that you're already familiar with. The map can help you remember things about the area and terrain that you might not have recalled right away. A kind of cognitive aid.
https://blog.digraph.app/2020-06-13-democratization-of-searc...
This will import Wikipedia's serious flaws. But I'm hopefully that they can gradually be mitigated.
In the past few months, things appear to have changed, and emails that are obviously spam, complete with the misspelled titles and funky case and punctuation, are now appearing in my Gmail inbox. It looks like the Gmail spam filter is becoming less effective.
I would love for email to be opt-in on a per sender basis. If I haven't opted-in to receive email from someone, perhaps a request is added to a queue that I can check from time to time (with its own spam filter), and until the request has been accepted, no email will arrive from them.
I'd actually use the term "welcoming" in this context.
https://blog.digraph.app/2020-06-13-democratization-of-searc...
In that post, I don't address the reputation management aspect as much, but it's central to making the whole thing work, and I think crowd-sourcing and a well-conceived reputation management system that can influence results are good next areas for exploration.
But, as the author mentioned, a lot of the problem is the inauthentic content on the internet that Google must sift through and filter. What makes Reddit still not half-bad (although this quality is under direct attack by brigading and troll farms) is that you have user-generated, user-curated content and a not-too-bad voting system.
In this context, I think a future iteration on search engines will be hand-curated results, under actual human-curated topics (rather than fuzzy machine-learning-inferred ones). Think of a huge directed acyclic graph of topics that goes down twelve levels or more in some cases. If you have enough people involved in this kind of crowd-sourcing, I think it can be made to work.
A challenge that arises in this context is how to prioritize content added to the wiki search engine by good contributors, and deprioritize content added by the content farms. I think this can be managed with a combination of well-conceived reputation management and providing users the ability to specify other users (people who seem trustworthy and whose tastes are solid) whose preferences will then be used to weight search results.