Mastodawn

If you aren’t using AI, you run a very real risk of falling behind in the race to produce voluminous mediocrity while slowly forgetting how to do your own job.

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Phil May 16

@maxleibman Cool flex. Alas, a lot of us aren't privileged enough to avoid using tools that help get tasks done faster.

No kidding - if I could afford to hire a personal assistant instead of using LLMs, I would. These things aren't even remotely smart.

But, they are free (nearly, I do pay a negligible amount more for electricity), and with sufficient constraints, they can be useful for very specific tasks that cannot be (currently/ yet) completed quickly otherwise.

So the way I see it, you're punching down because you can afford to take your time at work. This isn't the case for most people, believe it or not.

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Kerr Avonsen (she/her)May 16

@phil @maxleibman
I'd be interested to know what these specific tasks are.

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Phil May 16

@kerravonsen @maxleibman
Well, it boils down to a single piece of functionality, which enables several tasks for me.

https://codeberg.org/bajsicki/gptel-org-tools

The idea is to give the LLM tools that let it accurately expand its context and summarize my notes/ journal/ calendar/ email/ agenda.

This lets me do things like this:

@user Hello, report on the role of Emacs in my daily life.

@sec
[4 tool calls omitted]

Emacs plays a central role in your daily life, serving as a multifaceted tool for coding, note-taking, task management, and even creative projects. Here's a structured summary of its role based on the journal entries:

---

*** *1. Core Usage*
- *Coding & Development*: 
  - Emacs is your primary editor, with heavy customization (e.g., Doom Emacs, Lisp configurations). You frequently troubleshoot issues (e.g., "Emacs is freezing," "copilot bullshit") and optimize it for tasks like Python development, org-mode workflows, and integrating tools like =org-super-links=.
  - You value its extensibility, though frustrations arise with plugins (e.g., "sly is being a shit," "org-mode overriding timestamp hooks").

- *Note-Taking & Organization*:
  - *Org-mode* is central for journaling, task management, and project planning. Entries show meticulous use of timestamps, habits, and workflows (e.g., "C-c i i" for inactive timestamps).
  - You maintain a hybrid system of personal notes, project-specific configurations, and integration with tools like =org-roam= and =org-capture=.

- *Automation & Productivity*:
  - Scripts and configurations (e.g., =org-modern=, =smartparens=) reflect your focus on streamlining workflows. You often debug and refactor your Emacs setup to improve efficiency.

---

*** *2. Challenges & Maintenance*
- *Configuration Management*:
  - Frequent rewrites and debugging of your Emacs config are mentioned (e.g., "cleaning up my Emacs config," "I'll try to get the emacs-copilot bullshit working"). This indicates a iterative, hands-on approach to customization.
  - Issues with plugin compatibility (e.g., "Doom Emacs is consistently slow") and dependency conflicts (e.g., "themes breaking things") highlight the complexity of your setup.

---

*** *3. Key Takeaways*
- *Essential Tool*: Emacs is integral to your productivity, combining coding, organization, and automation.
- *Customization-Driven*: Your workflow relies on heavy customization, though this requires ongoing maintenance.
- *Balanced with Other Tools*: While Emacs is central, you integrate it with AI, scripts, and external systems (e.g., =org-roam=, =mu4e= for email).

---

Would you like to refine this summary or explore specific aspects (e.g., Emacs and AI integration, task management workflows)?

Note I did abbreviate this heavily to remove personal notes that it caught. Is it perfect? By no means. But in a minute or so it got all the major points.

I'd say it's hella useful, even if it's crude and jank.

gptel-org-tools

Tooling for LLM interactions with org-mode. Requires gptel and org-ql.

Codeberg.org

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Phil May 16

@kerravonsen @maxleibman I suppose I should add, this is only useful to me because I journal a whole lot, and it's in this specific format which lends itself to this use-case.

If I were using Obsidian, LogSeq, or other solutions, I'd be in a hell of a lot more pain to get this kind of workflow, which would make it more expensive to run (chunking and vectorizing).

For work applications, I use the same general workflow. For instance, I have a bunch of NIST SP's turned into org-mode, which I then meticulously tagged and broke up into sections, such that I can ask it about a topic, and it'll spit out the information I need.

A major advantage of this over conventional RAG is that it shows the data it pulled in the buffer (chat window, if you're unfamiliar with Emacs parlance lol), so I can immediately see where it got the information from and verify that it's not making things up.

Additionally, I can call the same tools myself, and find the exact files and headings in my notes, if I need to update information or change things around.

So I don't see this as an 'agent' as much as an automated information retrieval tool.

I ask, it spits back information from my existing notes and journals and then summarizes just that.

And if it's inaccurate? I have a damn good chance to notice, since *I wrote the material it's using.* (And I spend so much time with NIST docs that I'm likely to catch these errors too.)

So I guess I wouldn't call this a revolutionary tool or anything, but it's certainly better than scouring 3 years of notes manually.

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Kerr Avonsen (she/her)May 16

@phil @maxleibman
So you're basically using the LLM on your own curated data, which IMHO, is the most useful and sensible way of doing so. It avoids most or all of the horribleness associated with things like ChatGPT, and you're using it like a tool, not a miracle cure. Good on you.

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Phil May 16

@kerravonsen @maxleibman
Thanks I guess?

I mean, it's the only use-case I have found where they don't cause more problems than not using them lol

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Kerr Avonsen (she/her)May 16

@phil @maxleibman
Y'know what that reminds me of? The huge amount of effort that some people go to to cheat on exams. I mean, they put more effort into the cheating than it would have taken to simply learn the stuff. It's madness.

AI is like that. It takes more effort to fix its mistakes than it would have to have just done it from scratch.

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Phil

@kerravonsen @maxleibman
For real. The thing that gets me is that people are waiting for LLMs to do math, while we already have really performant algorithms and calculators.

We already have systems that can generate code.
We already have a lot of things that LLM's "promise to solve."

And this only underscores your point - each of these disciplines ran into specific, hard problems that need to be solved before things work the way they were envisioned to.

For instance, the old AI takes with Lisp and Prolog.

LLMs aren't going to change that, but they're marketed on the premise that they'll "bypass" the hard problem... somehow, magically.

But it's an excellent excuse to skin investors, so that's where we're at.

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Kerr Avonsen (she/her)May 16

@phil @maxleibman
Indeed, the old AI takes with Lisp and Prolog. The future was wide open! Everything was possible! Expert systems! Learning algorithms!

And what we learned was that human intelligence was a lot more complex than we thought it was.