reedlaw

How do you even begin to define objective measurements of software engineering productivity? You could use DORA metrics [1] which are about how effectively software is delivered. Or you could use the SPACE Framework [2] which is more about the developer experience.

1. https://cloud.google.com/blog/products/devops-sre/using-the-...

2. https://space-framework.com/

Plasma Bigscreen has been around for 6 years: https://itsfoss.com/news/plasma-bigscreen-comeback/

Isn't this the premise behind Dilbert?

LLM-generated snippets of code are a breath of fresh air compared with much legacy code. Since models learn probability distributions they gravitate to the most common ways of doing things. Almost like having a linter built in. On the other hand, legacy code often does things in novel ways that leave you scratching your head--the premise behind sites like https://thedailywtf.com/

Whatever agent I tried would include thousands of tokens in tool-use instruction. That would use up most available context unless running very low-spec models. I've concluded it's best to use the big 3 for most tasks and qwen on runpod for more private data.

This seems like a perfect use case for a local model. But I've found in practice that the system requirements for agents are much higher than for models that can handle simple refactoring tasks. Once tool use context is factored in, there is very little room for models that perform decently.

Maybe a better way to handle "minimize cyclomatic complexity" would be to set an agent in a loop of code metrics, refactor, test and repeat.

I don't know about Opus, but Codex suddenly got a lot better to the point that I prefer it over Sonnet 4.6. Claude takes ages and comes up with half baked solutions. Codex is so fast that I miss waiting. It also writes tests without prompting.

Great feedback. On the Inverness to Gibraltar race the leaderboard has impossible times, including some negative numbers. According to Google Maps the best time is 1 day 8 hours, but this requires leaving Inverness at 6:44. The race starts at 9:00. Then the earliest arrival time in Paris is 22:19. According to Google Maps the best time from Paris to Gibraltar at this time of night is 1 day 2 hours. Despite all this, there are several 1 day records. The best I can do is 2 days 5 hours. Of course I may be missing some better route, but I suspect cheating, especially from names like AdolfHitler.

I'm using the Aristotelian definition of my linked article. To understand a concept you have to be able to categorize it correctly. LLMs show strong evidence of this, but it is mostly due to the fact that language itself preserves categorical structure, so when embedded in geometrical space by statistical analysis, it happens to preserve Aristotelian categories.

Yes, LLMs mimic a form of understanding partly through the way language embeds concepts that are preserved when embedded geometrically in vector space.

That's true. Older books require skill to restore, so choosing old or new is a balance.

This is a fine and useful project, but my experience with newly printed classics is the quality is inferior for a number of reasons. Besides paper and binding, typesetting is something that older editions rarely messed up, but some new editions create a facsimile by scanning all the pages and then re-printing. That means that instead of getting the crisply defined letters of an old printing press, you get fuzzy letters and scan artifacts. This (https://printableclassics.com/harvard_classics) shows what I mean. Not only is the typesetting quality worse, but the price is much higher for the new edition. I don't have a problem with the price on Printable Classics ($885 for a new 50 volume set is reasonable), but you could often find the same thing cheaper used. A used set is $300-$600 on ebay. The value of these PDFs is that you could make a higher quality edition as long as the text is OCR'ed and properly typeset (which is true of the Moby Dick version on the site). For the scanned copies, it would be a big undertaking to re-typeset, but I'm sure LLMs could help.

This article, (https://michaelmangialardi.substack.com/p/the-celestial-mirr...), came to similar conclusions as the parent article, and includes some tests (e.g. https://colab.research.google.com/drive/1kTqyoYpTcbvaz8tiYgj...) showing that LLMs, while good at understanding, fail at intellectual reasoning. The fact that they often produce correct outputs has more to do with training and pattern recognition than ability to grasp necessity and abstract universals.

I've already tried to do what the article claims to be doing: handing-off the context of the current session to another model. I tried various combinations of hooks, prompts and workarounds, but nothing worked like the first screenshot in the article implies ("You've hit your limit [...] Use an open source local LLM"). The best I could come up with is to watch for the warning of high usage and then ask Claude to create a HANDOFF.md with the current context. Then I could load that into another model. Anyone have any better solutions?

Under the Cons section the article says:

> Full analog functionality often depends on proprietary software support (and not all boards execute it well).

Could you elaborate how that works? I'm on Linux. I find with Keychron I can visit the web-based tool to configure the keyboard, but if it's proprietary software I'm out of luck.

From the article I like the characteristics of hall effect better than TMR (although one of the cons under HE, "Since the sensor is reading magnet position, any wobble in the switch can change the magnet’s alignment and affect the signal", is a bit troubling). There are indeed $30-50 ones on Amazon. Any particular brand recommendations?

Could you give examples of excellent typing keyboards from China for $30-50? Every mechanical keyboard I've owned eventually suffered from key chatter or inconsistent actuation.

Great article, but doesn't address the fundamental issue: defining quality. Other than some objective metrics like code coverage, there is little agreement about what constitutes good code. The closest thing to a consensus might be the rules encoded in linters/formatters. Each Rubocop or eslint rule had to go through code review and public scrutiny to be included and maintained. Most often the rules are customized per project/team. Of course this runs into the same problem the article mentions: narrowness of vision. It seems the only way to achieve a high-minded ideal is the BDFL model of software development.

Unfortunately, reading before merge commit is not always a firm part of human team work. Neither reading code nor test coverage by themselves are sufficient to ensure quality.

Gergely Orosz (The Pragmatic Engineer) interviewed Yegge [1] and Kent Beck [2], both experienced engineers before vibe coding, and they express similar sentiments about how LLMs reinvigorated their enjoyment of programming. This introduction to Gas Town is very clear on its intended audience with plenty of warnings against overly eager adoption. I agree that using tools like this haphazardly could lead to disaster, but I would not dismiss the possibility that they could be used productively.

1. https://www.youtube.com/watch?v=TZE33qMYwsc

2. https://www.youtube.com/watch?v=aSXaxOdVtAQ

That sounds nearly perfect for FSRS [1], the default spaced repetition algorithm used by Anki, which aims at estimating the time it takes for memory stability to decline from 100% to 90%. At the estimated 90% stability point, FSRS would require a review, so naturally a mature deck of flashcards would hover between 90-100% stability.

1. https://expertium.github.io/Algorithm.html

John Carmack's and Martin Fowler's coding style advice are diametrically opposed. Carmack advocates inlining complex code that is only used once. Fowler advocates extracting it with a good name to clarify intent. I'm not sure the two views can be reconciled except by noting that they address separate concerns. Carmack prioritizes visibility while Fowler prioritizes intent.

The first sentence is problematic:

> For decades, we’ve all known what “good code” looks like.

When relatively trivial concerns such as the ideal length of methods haven't achieved consensus, I doubt there can be any broadly accepted standard for software quality. There are plenty of metrics such as test coverage, but anyone with experience could tell you how easy it is to game those and that enforcing arbitrary standards can even cause harm.

I'm on my fourth George Eliot novel this year, Adam Bede, which was her first published novel. I started with Middlemarch and proceeded to read Silas Mariner, Romola, and Daniel Deronda. The 1985 film adaptation of Silas Marner is very good and faithful to the novel. The 1970 Daniel Deronda film is similarly faithful and well-acted but the 2002 version is neither.

This even has a way to make flyover animations: https://github.com/magcius/noclip.website/wiki/Studio

How does DSPy.rb differ from BAML?

I had a Pangolin instance compromised by this: https://github.com/orgs/fosrl/discussions/2014

This concept is also known as Borg Complex: https://thefrailestthing.com/2013/03/01/borg-complex-a-prime...