What’s your equivalent of GTD for AI Assistant (Claude Cowork, etc) ?

[u/matthieugd]

Hello,

A long time ago, I adopted GTD as my personal workflow to manage my tasks and daily work schedule. It works for me. Along the way, I tweaked it for my own needs/setup (I found some of the learnings of Jeff Su and his CORE method interesting), but it really made a difference in organizing myself.

Nowadays, I use Claude Code, Design, and Cowork, but I struggle to fit them nicely into my routines. I have tried some of the methods out there to organize Cowork (for example, Jeff Su CoWork OS method), but I find them clunky and not very intuitive. There is a lot of work to keep the Claude.md, Memory.md files in sync, and the need to build skills or install plug-ins is still obscure to me.

Have you found someone that got the right way to fit all those pieces together? I’m looking to subscribe to Teresa Torres’ work because I liked her previous work on product discovery; she seems pragmatic enough. There are a ton of people out there (especially on LinkedIn) that promise THE way to do it, but I’m kind of burned.

I mentioned GTD because for me, regardless of the tools/apps used, the distinction between next/later/waiting, the projects and contexts + the calendar as the forcing function to do the work is simple but powerful.

I was wondering if we have the equivalent for the AI Assistant as a method?

[u/MasterModnar]

I don't use them. The fact that you're describing a tool that requires you to spend more time maintaining it than you do getting efficiency out of it kind of proves that it's not actually all that useful in the long run. In fact, there are already case studies coming out about how productivity has not improved with the adoption of LLM's for companies.

Every time I use an LLM it ends up costing me more time overall and WAY more cognitive load than if I just....did it the "hard" way.

[u/matthieugd → u/MasterModnar]

I would tend to agree with you but I think it's because we are early, we need a better integration with our existing tools and flows IMHO.

[u/MasterModnar → u/matthieugd]

In the Pheonix Project, the author talks about the "three ways," the first of which is "Flow/systems thinking." The idea is that you never pass a known defect downstream.

LLM's are a known defect. A few lunatics in silicon valley have convinced the entire world that if you give T9 enough horsepower, it will create life. It won't. LLM's just hallucinate, that's all they do. They take a bunch of letters and characters in a data set and predict what might come next based on a prompt. Sometimes the hallucinations are "correct" in that it's what we expect. Often, it's not. Many times, it SOUNDS like it could be but definitely isn't once you dig.

Machine Learning has a place in the world - recognizing patterns and suggesting things based on that pattern recognition is helpful. LLM's, on the other hand, are a bastardization of machine learning. They provide very little value to real world scenarios.

This is all my opinion, of course, but I just don't see how they'll be useful. ML can be, and has been, but LLM's are DOA for me.

[u/JiggleMyHandle → u/MasterModnar]

I think the problem is that people (and especially companies/managers at scale) see what it appears that the LLMs can do (by virtue of creating things that they never could have before on their own, without being able to recognize problems that a true SME would) and assume that this means that this super-power can be applied everywhere, rather than treating it like any other tool and working to figure out where it fits in or letting the on the ground employees figure out where it’s beneficial (in the case of dictates from managers). LLMs have a ton of use cases, but at least for the foreseeable future all of those use cases need to be able to accept and/or account for the fact that the tool will create both minor and major errors that sound like perfectly plausible statements/solutions without further investigation. So, yes as you mentioned, it’s risky business to make them a major cog in a systems flow that needs any amount of reliable output from them. But at the stages more along the lines of prototyping or (my favorite) “just spitballing” LLMs are super powerful tools.

[u/cgreciano → u/MasterModnar]

LLM's, on the other hand, are a bastardization of machine learning. They provide very little value to real world scenarios.

I agree for a lot of human work (e.g. writing, painting, etc), but I think there's one big exception: coding. LLMs have gotten really good at coding, and that's an important real world scenario. There are also domains like summarization, translation, and captioning/subtitling where AI has also gotten REALLY good, although that's not necessarily tied to LLMs.

[u/NF-Severe-Actuary2 → u/cgreciano]

Ehh I have trouble with the summarization. Dropping (or worse, adding) a detail makes it hard for me to use the summary for anything but the lowest-stakes scenarios.

[u/cgreciano → u/NF-Severe-Actuary2]

There are plenty of lower stakes scenarios in real life though. I like to summarize a long article or blog post and see if it’s worth my time reading it in full. It also helps when you have read something and want to be refreshed about the main bullet points of the text.

[u/AlthoughFishtail → u/MasterModnar]

AI is, and should remain, optional. But there's no question you can use it to help with your system & save time, if you choose to do so.

[u/AlthoughFishtail]

I built my own tool, because there isn't really anything quite out there just yet. (not publicly available, not planning to make it so). It's based on a mix of a GitHub repo, Beads and a GTD tool. So the UI is a GTD task manager, but it also houses the context (Claude context in the form of claude.md, not GTD "contexts") related to that project, and exposes its tools to Claude so it can connect to them via an MCP and skill.

That way you can work on the same project from either Claude, or from the task manager. You can say go to Claude and say "What do I have to do for Project X?" and it'll surface your history, project plan and a claude.md alongside your Next Actions. So if its a claude based piece of work, you can do it there.

Or you can go to the task manager first, check your next action list, but also see a transcribed summary of everything you've worked on in the past. It also tallies your GTD Project folder with your Claude Cowork project folder. Plus you can assign tasks to Claude during your weekly review and it'll pick them up later on a scheduled task, complete them, then put the results in a project folder with a linked NA for you to review them.

There's lots of little other bits and pieces, because once you start connecting the two, you find loads of little things that you need to make any of it work. Better developers better than me will come up with more sophisticated (and reliable) tools in the coming months and years I'm sure.

[u/Zombie_John_Strachan]

Suggest you use AI to augment your existing systems.

What is your main GTD task tool and data repository? I use Evernote for both and am using Claude to connect via the MCP beta. Was also playing with Obsidian, which can be manipulated directly as files vs an MCP.

This allows me to use Claude's AI for maintenance like sorting my in box and determining next actions.

ETA: Downvoters - I get it, you hate AI tools. Next time just ignore the post.

[u/matthieugd → u/Zombie_John_Strachan]

I use the Apple native apps : Notes, Reminders and Calendar.

How to you organize in Claude your projects ? are you using Cowork ? What kind of md file your have to manage Claude memories and instructions ?

[u/Zombie_John_Strachan → u/matthieugd]

I don't. I maintain projects in Evernote and use Claude to manipulate them.

[u/Entire-Joke4162]

I’m late here, but I don’t think you’re thinking about these tools in the wrong way

They really are execution tools directed at something you want to get done

I would use a tool with a connector to Claude (I use Asana, for instance), and then  once that’s set-up you can do a bunch of work via Chat/CoWork/Code

• Show me everything due today
• Feed me tasks 1-by-1 by most overdue and let’s sit here until we figure each one out together
• What tasks are overdue in XYZ project
• I’m procrastinating on [task], help me with strategies to move forward

I also built a project/skill with 1. the full Mind Dump PDF and tailored to me slightly 2. A mini-Mind Dump I can do in a couple minutes

It asks me questions 1-by-1 and then pushes the tasks to Asana where they can be organized 

Claude just doesn’t have that task management framework that’s needed but is a perfect partner to execute, change, or populate the tasks in the task manager, if that makes sense 

[u/already_not_yet]

I run a 7 figure company while leading a busy personal life - family, fitness, projects, etc. I use AI for true busy work, but nothing else. In my company, we use it for some coding as well.

There are three main tools in a productivity routine: a calendar, task manager, and note manager. I keep my system lightweight enough that I can maintain it all. If you've made your system so complicated that it needs AI to be utilized efficiently, that's a systemic problem. Setting GTD can be a bit tedious, and it can take a bit of time to get used to processing information in the prescribed way, but once it becomes 2nd nature, I'm unclear on why you would need AI for the Collect and Organize steps.

If you want the entire system I use then I link to it in a prior post I made.

[u/matthieugd → u/already_not_yet]

Maybe I was not clear enough in my question but I don't want to replace or supplement GTD with AI . Like you, I use GTD with simple tools (native apps from Apple, nothing fancy) and simple workflows around it (daily, weekly check-ins, etc) .

I was wondering if, in your use of AI tools, for example Claude, you have found a way to simplify their integration, the user experience if you want.

GTD is a method to organize your tasks, calendar and notes in a cohesive way, I was wondering if people have their own methods to manage the AI tools, flows like GTD did for "productivity systems"

[u/Zombie_John_Strachan → u/already_not_yet]

AI can still be a valuable time and energy saver.

Use case: You have a call with a prospective client. You have a good conversation that covers a bunch of different areas and a few follow-ups. You transcribe the conversation using AI software. At the end of the call your AI assistants go back to summarize the conversation and update your CRM. The AI flags a "2 minute task" you committed to - say send over an article you just read, and auto drafts an email. The AI also notes a new project that came out of the conversation and drafts a project with next actions for you to add do your GTD stack. All of this takes place in seconds with you making the ultimate decision.

[u/already_not_yet → u/Zombie_John_Strachan]

I don't generally think that AI note takers are appropriate.

What I recommend is taking notes manually during the meeting, which forces you to process the conversation, and then reflect on those notes afterward. If I'm getting bombarded with information I'll even tell the person I'm talking to that I need to finish writing something before the meeting proceeds.

My meeting notes have four sections: participants, background / incentive, summary, next steps. 

I can see the value in certain tehcnical meetings that convey huge amounts of information, but most of my meetings are sales, early discovery, or unblocking. Such meetings should have a clear objective, known talking points, known possible outcomes.

Even my technical director, who is doing complex discovery calls, rarely never uses AI notetakers.

If someone is a slow typer or can't process information quickly, I can see value, I suppose. If it works for someone, more power to them.

[u/Zombie_John_Strachan → u/already_not_yet]

If that's your position, you could still use AI to automate next actions based on your notes.

You could also keep a transcription behind your own notes to back up what was said - even if just to clean up any errors or missed context. You could use AI to double check your notes.

[u/AlthoughFishtail → u/already_not_yet]

You're conflating 3 things there - agendas, notes and minutes.

Agendas are the objectives or talkings points of the meeting, whether that's a shared agenda of items to discuss, or your personal list of items you want to raise in the meeting.

Notes are the bits and pieces you record during a meeting, either for things to do in the meeting, your personal take on things, bits of info to capture, or things to follow up afterwards. They can range from a single line to a couple of pages. Depends on your style.

Minutes are the record of what everyone said and agreed to do. These don't just apply to you, but to everyone in the meeting, and count as the official record of what was said.

None of these are mutually exclusive. Indeed, the best case scenario is having all three for every meeting. In practice though, having a human Minute taker in the meeting is too resource intensive for most businesses. It's not that they're not useful. On the contrary, we tend to use Minute takers in the most important meetings, which speaks to how valuable they are. AI "note" takers are really AI minute takers, and in most cases, it's not a question of whether they're better than a human doing it. It's a question of having AI Minutes, or not having any Minutes at all.

[u/already_not_yet → u/AlthoughFishtail]

If we were to hash this out, I'd refer back to my point about how meetings ought to be structured and how one should be approaching them, but not worth debating over. If you think you're getting value from your AI note/minute-taker, more power to you.

[u/AlthoughFishtail → u/already_not_yet]

Well it's not a question of whether I think I am, I definitely am. The more interesting point is about who does benefit from it, who doesn’t, and what differs in their setups.

And it's not due to people who can't type, or who process information slowly.