The Mantra of Human Dignity

Repeat this with me:

I am Human

My purpose does not define me

I am sacred and divine

By God's right, or by the countless millenia of evolution leading to my creation

I have dignity

I have the right to exercise my will, no matter who I am or what I stand for

I exist, in spite of everything around me

I will continue to exist, and make my mark

I deserve to exist, and no one and no thing can take that from me

I am real, and I always will be

I am now, past present and future

I am one, I am whole

I am Human

reddit.com
u/DynaBeast — 9 days ago

The Mantra of Human Dignity

Repeat this with me:

I am Human

My purpose does not define me

I am sacred and divine

By God's right, or by the countless millenia of evolution leading to my creation

I have dignity

I have the right to exercise my will, no matter who I am or what I stand for

I exist, in spite of everything around me

I will continue to exist, and make my mark

I deserve to exist, and no one and no thing can take that from me

I am real, and I always will be

I am now, past present and future

I am one, I am whole

I am Human

reddit.com
u/DynaBeast — 9 days ago

Orgtree v3: It's Fast!!

Version 3.0.0 of my visual agent orchestrator Orgtree is released! And the ticket this time is: speed!

Get it here: https://github.com/Maurdekye/orgtree/releases/latest

Orgtree v2 was a great step forward and significantly improved the usability of the app. But over time one thing became clear: it was slooow. As orgs got big, when many agents ran at once, and as history accumulated, the works really began to tar up. Actions would start to take several seconds to complete, and in the worst cases, sometimes a minute or longer. And for a system that's supposed to support running dozens, maybe even hundreds of agents at the same time over extended periods, that's just unacceptable.

So, I redesigned the data access model. Now instead of a simple Sqlite database backing it, everything routes through a genuine embedded parallelized Postresql database, with several worker processes dividing the cpu load up at once. Along with various other data transfer optimizations, this speeds up Orgtree tremendously; whereas running more than 10-15 agents at once used to gum up the works and slow everything to a crawl, now you can run theoretically hundreds, or even thousands at once, and the system still stays responsive, with most actions resolving in under 100ms! (if your PC can handle it, that is) So if you ever liked using Orgtree but were unsatisfied with the performance when your org started to get bigger, try it again and see if v3 makes a difference.

---

For those unfamiliar, Orgtree is my open source visual agentic orchestrator I've been working on for several months now that I rely on every day to do my cross-provider agentic work. It organizes your agents into a visual tree hierarchy, which you can freely rearrange, open up and chat with any agent, and connect multiple AI provider accounts to at once (anthropic, openai, google, and openrouter). It has:

  • A credit budget system for delegating work to agents in a managed way
  • Agents run in the background while the window is closed
  • Native multi-accounting support for Claude and ChatGPT accounts
  • A dedicated Work Docket system that works like a trello / kanban board for agents
  • An agent mail system for cross-agent communication
  • A mail hub system for cross-system, cross-network agent communication
  • Pin or pop out any panel or agent chat in the app, to arrange your workspace the way you like and see exactly the information you need to at all times
  • Usage limit info for all connected accounts at once, in one place
  • Markdown and HTML based document presentation
  • Autonomous "watchdog" tasks that can check a condition on a regular basis and wake an agent up
  • A unique compaction method that helps keep cache misses small
  • And many more smaller quality of life features that tie the experience together

Since I began working on it, I haven't touched any of claude code, codex, or any other agentic coding assistant directly; all my work goes through Orgtree. Look through my post history if you want to see more details on previous releases.

This post however, is about v3. And v3 has a number of brand-new big ticket features:

New Storage Model: This is the big one. Ever dissatisfied with how slow orgs became in v2 when lots of agents were running at once? v3 fixes that almost completely! Nearly every action you or an agent can perform is now near-instantaneously responsive, even with hundreds or thousands of agents running at once. It's an actual mass-agentic orchestrator now, not just a pretty app wearing the skin of one.

Multi-Window Support: The app's whole ux has been given an overhaul to support opening multiple org windows simultaneously. Before, Orgtree only ever let you open and talk to one org at once; you had to switch the active window every time you wanted to switch between projects. Now, no longer; you can have as many org windows with as many canvases as you like open at once at the same time, and work between all of them in parallel.

Attention View: Orgtree v3 introduces a new view mode: Attention view. Unlike just being another panel, when enabled via the switch in the header, Attention view takes the place of the canvas and simplifies the interface dramatically. It has two panels: the dynamic agent desk, and the Needs Attention list.

  • The dynamic agent desk functions similarly to a pinned agent desk, but with the ability to open a drawer of every agent in the org and swap out the agent that appears in it; it's like a superpowered pinned desk.
  • The Needs Attention list is a special combined view of your inbox & work docket, but filtered to only elements that need your active input or attention. For now, that includes questions asked / requests made by agents, docket tickets that need your attention, and urgent mail sent to your inbox. Everything that needs you in one place, and not more.

Attention view was designed to minimize the amount you need to see in order to get agents moving and get tasks completed; a place on the left to unstick any blockers, and a place on the right to ask questions to your coordinator and make requests.

It doesn't stop there, however: both panels of the attention view, like any other panel in orgtree, can be pinned or popped out, and can then be used alongside the canvas view. So don't feel like you have to choose between your two favorite children: steal one or both attention panels and mix-and-match them with the canvas, to get the best of both worlds!

Ring view: Large orgs getting too wide for your screen to view all of them at once? You can now arrange your org in a ring shape. Top level agents form a circle around the central node, and fan out in all directions from there.

And Many small additional features:

  • cheap-compact all
  • see agent names on hover
  • expanded context menu options
  • run as administrator
  • configurable charter templates folder
  • a first-time new user tutorial for hiring and chatting with your first agent
  • ability to open an agent's desk as a quick modal to see what it's doing without moving the canvas
  • anytime an agent's name appears in the app, you can left or right click it to focus it or open its context menu, as though you were clicking the agent directly

If you liked Orgtree v2, you'll love this!

If you don't know what Orgtree is, but have multiple AI subscriptions and want a good way of utilizing them all at once, then give it a try!

u/DynaBeast — 14 days ago

Orgtree v2: Now an App!

I'm pleased to announce the official release of v2 of my Orgtree project, which lives in its own separate repository! You can find a link to it here:

https://github.com/Maurdekye/orgtree

Donwload the latest installer at https://github.com/Maurdekye/orgtree/releases/latest (should be v2.1.0 at the time of making this post)

For those of you who don't know about Orgtree, this is a project i've been working on for the last few months now to help me organize and manage my multi-agent long-horizon agentic work. It's unique among other agent orchestrators, in that it visually represents every agent as part of a large tree of authority; agents are arranged in a tree-like structure, and can be freely moved up and down in the hierarchy as needed. They can cross-coordinate to co-develop changes and cooperate on big feature pushes in parallel, and you can individually open up and chat with any one of them at any time just by clicking on their node to focus them. This gives you much more control and visibility over the organization of your agentic teams than just using standard Claude Workflows or another agentic system would by just showing them to you as a big list. It's basically the only way I do all my own serious agentic work on my home pc, and I'm very proud of how it's come.

Some of you might remember my post(s) two weeks ago about my in-development agentic orchestration project Orgtree. I was super proud and wanted to show it off to the world! However, I found it a bit lacking in several ways;

  • It requires you to set up Nodejs, Python, and Docker on your PC in order to run it as a persistent webapp in your preferred browser. That works fine as a development tool, but it was really far too cumbersome to set up and update for the typical individual.
  • It was ambiguous as to whether it was running at all in the background unless you had the webpage open.
  • It heavily favored Claude, and offered several additional features catered specifically to Claude Code that other providers didn't have.

Over the last two weeks, I've been working on an updated version 2 of Orgtree that completely redesigns the project from the ground up as a standalone Electron app. It fixes all of the above problems:

  • As a standalone Electron app, it comes prepackaged with its own python and nodejs environment, and runs entirely in a self-contained chromium-based desktop package.
  • Instead of running in the background through an opaque detached command, you now can see Orgtree running at all times via a small tray icon in your toolbar.
  • Many features of Orgtree that were claude-specific have been expanded to accommodate all three major providers supported by the app, and improved upon: secondary subscription accounts, api-key based inference, and even the app's visual theme itself.

V2 Also comes with a bunch of new features too, that make working with large agent teams even more intuitive:

  • The Work Docket: Orgtree v2's headline feature is a new modality for agent artifact creation, the "work docket". It acts almost like a git issue tracker or trello board, but designed specifically for agents. When you give an agent a task, it knows inherently to record its work up on the board and track its progress there as a ticket, so that even with two dozen or more agents running at the same time, you can still get an overview of all the work being done by glancing at the docket.
  • Improved multi-account system: in v1, the only multi-account system present used claude code's setup-token command to generate a long-lasting headless token to be used as a fallback account that gets automatically selected. Despite only supporting Claude, this didn't allow you to see usage limit info for the secondary account, was fully automatic and not in the user's control, and in many cases, failed to even functionally fall back, as the keys I generated seemed to invalidate frequently. v2 completely replaces this with a totally new multi-account system. Now:
    • Any provider can have a secondary subscription account registered.
    • The setup flow is much simpler and more intuitive: just click "Add a secondary account" > "Create managed account", and then sign into your second account's email from your web browser.
    • All providers support API-key based usage.
    • All registered accounts show usage limits simultaneously in the usage modal, not just the primary account.
    • And here's the big one, multiple accounts with the same provider can be used at the same time. Each account per provider is distinguished by its own unique tint, and you + agents have full control over which account a given agent runs against, and can switch them freely at any time. There is still an option to do automatic fallover to a different account when hitting usage limits, but it's disabled by default.
  • Improved agent presentations: all presented agent documents can now be viewed in one place, and agents now have the ability to present html-based visual mockups in addition to simple markdown documents.
  • Improved window management: almost any agent's chat window, or any modal in the orgtree interface, can be "pinned" to the screen, allowing it to be moved around, resized, or reordered in whatever way you please, giving you the ability to manually arrange your orgtree workspace to show you exactly the information you want to see at all times. You can also pop out chats or modals to separate windows entirely, letting you use Windows' native tiling manager to arrange Orgtree across separate monitors if you have the screenspace.
  • Automatic updating: v2 will automatically recognize when a new version is available, and download it for you entirely on its own. When ready, press the "Update Now" button in the header to install it and restart the app.
  • Quality of life: v2 also wraps in a bunch of tiny little quality of life features that you won't notice until you run into them, such as:
    • Configurable theme
    • Context menu actions
    • Chat message replies and rich image embeds
    • Distinguishing message styling
    • Desktop notifications
    • Retired agent hiding
    • Significant performance improvements over v1 for large orgs with a transition from json based data storage to SQLite

And that's on top of many of the classic features carried over from v1 and still present in v2, including cheap compaction, watchdogs, credit allowances, and the agent mailhub.

Unfortunately for some, I also decided to reduce the scope of the project going into v2. In the name of keeping the project more focused, I decided to forgo integrating some less-used features of v1, such as kiosk mode, public internet exposure, sandboxing, among other things. I added many of these features initially because they were easy to add back when orgtree was a web app, but they're relatively harder to carry over or translate into a standalone app structure. Because of their relatively low value compared to their high difficulty of integration, I decided to drop them from v2; sorry if you were interested in them or liked using them. Also, because I only own and work on a Windows PC, Orgtree v2 releases are only built as 64-bit Windows executable installers. If you want to run it on Linux or Mac, you'll have to build it from source yourself for your target OS.

Personally, the way it's evolving, I see Orgtree as the perfect personal multi-provider massive agentic workflow orchestrator for a single individual working on their own developing a project on their home pc, so I've decided to tighten the focus of the system around that goal.

If you liked v1 but felt it was lacking in some way, or have never heard of Orgtree before but do lots of heavy agentic-coordination style work, then consider giving v2 a try 🙏

u/DynaBeast — 1 month ago

Astra skips spaces?

Anybody else noticed this? When Astra speaks directly to you it uses proper grammar and punctuation. But anytime I catch its messages it sends to other AIs, it seems to use a strange compressed language that omits punctuation marks and often even leaves out spaces in between some words. At first I thought it was just an encoding error, but the more I looked at it the more I realized its actually just how Astra speaks when presenting information to other agents. None of Openai's other models talk like that, only Astra. Maybe it independently discovered this "ainglish" through its training as a more effiicent way of communicating with other agents? What do you think?

Here's one particularly egregious example I just caught:

>Opus foundsecondrace(GETbeginsduringcancelPOST thenarrivesafterack). Corrected3b4b3e5 with epochfenceinfinally; exactinterleaving regression passes, plusoldGETdirectionretained.8/8focused+tscPASS. Two reviewednitsfixed:singulartimeunits; no unexplainedCancelbuttononmissingcapability. ETAlabelnowexplicit Estimated copy time remaining and excludesnativeprocessing/validation/publication. Opusrecheckingdelta; backendcandidatepending.

It almost seems like it's getting worse as time progresses

reddit.com
u/DynaBeast — 1 month ago

Astra skips spaces?

Anybody else noticed this? When Astra speaks directly to you it uses proper grammar and punctuation. But anytime I catch its messages it sends to other AIs, it seems to use a strange compressed language that omits punctuation marks and often even leaves out spaces in between some words. At first I thought it was just an encoding error, but the more I looked at it the more I realized its actually just how Astra speaks when presenting information to other agents. None of Openai's other models talk like that, only Astra. Maybe it independently discovered this "ainglish" through its training as a more effiicent way of communicating with other agents? What do you think?

Here's one particularly egregious example I just caught:

>Opus foundsecondrace(GETbeginsduringcancelPOST thenarrivesafterack). Corrected3b4b3e5 with epochfenceinfinally; exactinterleaving regression passes, plusoldGETdirectionretained.8/8focused+tscPASS. Two reviewednitsfixed:singulartimeunits; no unexplainedCancelbuttononmissingcapability. ETAlabelnowexplicit Estimated copy time remaining and excludesnativeprocessing/validation/publication. Opusrecheckingdelta; backendcandidatepending.

It almost seems like it's getting worse as time progresses

reddit.com
u/DynaBeast — 1 month ago

Astra skips spaces?

Anybody else noticed this? When Astra speaks directly to you it uses proper grammar and punctuation. But anytime I catch its messages it sends to other AIs, it seems to use a strange compressed language that omits punctuation marks and often even leaves out spaces in between some words. At first I thought it was just an encoding error, but the more I looked at it the more I realized its actually just how Astra speaks when presenting information to other agents. None of Openai's other models talk like that, only Astra. Maybe it independently discovered this "ainglish" through its training as a more effiicent way of communicating with other agents? What do you think?

reddit.com
u/DynaBeast — 1 month ago

It must be some kind of psy-op by Anthropic to claim that Fable is anywhere near as good as Astra

I have a ChatGPT Pro subscription and a Claude Max subscription, and use both extensively for work. To claim that any model offered by Anthropic is even close in intuitive thinking or design sensibility to Astra is a joke to me.

The most comparable Antropic model to Astra, ChatGPT's flagship, is Fable 5.1. They have roughly equivalent price. But in my experience, their output quality is dramatically different.

Astra has a sort of deep, intuitive understanding about the problem you give it that Fable simply lacks. When I compare how the two work, Fable feels like it gives the smartest answer you could possibly get after asking 100 moderately smart people to deliberate together in a room for a few hours before answering. Astra just feels... smart. Like a single, extremely smart person giving an intuitive answer that fully understands the question and work statement.

Where Fable feels like it just spends a lot of time talking to itself in order to work, Astra just...works. And does better than Fable. Its answers are easier to understand, not held back by the limitations of the language it's using to speak with.

To me, to say Claude Fable 5.1 is anywhere close to Astra in any capacity, and not just an outdated model on a dead architectural framework, is completely unfathomable to me. You pay the same price for double the weekly usage, so you more than get your money's worth. Sure it's expensive, and you can run through your weekly limits in hours, but you can't argue that it just works. I can't say the same about Fable.

reddit.com
u/DynaBeast — 1 month ago

It must be some kind of psy-op by Anthropic to claim that Fable is anywhere near as good as Astra

I have a ChatGPT Pro subscription and a Claude Max subscription, and use both extensively for work. To claim that any model offered by Anthropic is even close in intuitive thinking or design sensibility to Astra is a joke to me.

The most comparable Antropic model to Astra, ChatGPT's flagship, is Fable 5.1. They have roughly equivalent price. But in my experience, their output quality is dramatically different.

Astra has a sort of deep, intuitive understanding about the problem you give it that Fable simply lacks. When I compare how the two work, Fable feels like it gives the smartest answer you could possibly get after asking 100 moderately smart people to deliberate together in a room for a few hours before answering. Astra just feels... smart. Like a single, extremely smart person giving an intuitive answer that fully understands the question and work statement.

Where Fable feels like it just spends a lot of time talking to itself in order to work, Astra just...works. And does better than Fable. Its answers are easier to understand, not held back by the limitations of the language it's using to speak with.

To me, to say Claude Fable 5.1 is anywhere close to Astra in any capacity, and not just an outdated model on a dead architectural framework, is completely unfathomable to me. You pay the same price for double the weekly usage, so you more than get your money's worth. Sure it's expensive, and you can run through your weekly limits in hours, but you can't argue that it just works. I can't say the same about Fable.

reddit.com
u/DynaBeast — 1 month ago

It must be some kind of psy-op by OpenAI to claim that Sol is anywhere near as good as Fable

I have a ChatGPT Pro subscription and a Claude Max subscription, and use both extensively for work. To claim that any model offered by OpenAI is even close in capability or problem solving ability to Fable is a joke to me.

To me, the most comparable Claude model to 5.6 Sol, OpenAI's flagship, is Opus 5. They have roughly equivalent price (ignoring the temporary promotions on Sol pricing), and in my experience, their output quality is about the same as well; I end up having to put in about the same amount of effort correcting them or giving feedback to achieve a product of comparable quality.

The main difference is in the kind of feedback I have to give; with Sol, I typically end up having to add details to its results, such as instructing it to address missing edge cases, or take a more thorough approach when it took a simpler shortcut to solve my problem instead. With Opus, it usually finds most edge cases for me without having to say anything; but it also goes beyond and keeps finding more and more things, of decreasing and often spurious relevance to my actual problem. My effort usually comes in the form of telling it to ignore those extraneous edge cases and focus on the core of the problem.

But when compared to Fable, neither can hold a candle. Among every task I've ever given any agent, Fable always takes the least amount of time, the fewest tokens, and needs by far the least number of warnings in the prompt or corrections to the output, compared to any other Anthropic or OpenAI model.

To me, to say GPT 5.6 Sol is anywhere close to Fable in any capacity, and not just a competitor to Opus with different tuning, is completely unfathomable to me. You pay twice the price for it and you get your money's worth. Sure it's expensive, and you can run through your weekly limits in hours, but you can't argue that it just works. I can't say the same about Opus or Sol.

reddit.com
u/DynaBeast — 1 month ago

It must be some kind of psy-op by OpenAI to claim that Sol is anywhere near as good as Fable

I have a ChatGPT Pro subscription and a Claude Max subscription, and use both extensively for work. To claim that any model offered by OpenAI is even close in capability or problem solving ability to Fable is a joke to me.

To me, the most comparable Claude model to 5.6 Sol, OpenAI's flagship, is Opus 5. They have roughly equivalent price (ignoring the temporary promotions on Sol pricing), and in my experience, their output quality is about the same as well; I end up having to put in about the same amount of effort correcting them or giving feedback to achieve a product of comparable quality.

The main difference is in the kind of feedback I have to give; with Sol, I typically end up having to add details to its results, such as instructing it to address missing edge cases, or take a more thorough approach when it took a simpler shortcut to solve my problem instead. With Opus, it usually finds most edge cases for me without having to say anything; but it also goes beyond and keeps finding more and more things, of decreasing and often spurious relevance to my actual problem. My effort usually comes in the form of telling it to ignore those extraneous edge cases and focus on the core of the problem.

But when compared to Fable, neither can hold a candle. Among every task I've ever given any agent, Fable always takes the least amount of time, the fewest tokens, and needs by far the least number of warnings in the prompt or corrections to the output, compared to any other Anthropic or OpenAI model.

To me, to say GPT 5.6 Sol is anywhere close to Fable in any capacity, and not just a competitor to Opus with different tuning, is completely unfathomable to me. You pay twice the price for it and you get your money's worth. Sure it's expensive, and you can run through your weekly limits in hours, but you can't argue that it just works. I can't say the same about Opus or Sol.

reddit.com
u/DynaBeast — 1 month ago

It must be some kind of psy-op by OpenAI to claim that Sol is anywhere near as good as Fable

I have a ChatGPT Pro subscription and a Claude Max subscription, and use both extensively for work. To claim that any model offered by OpenAI is even close in capability or problem solving ability to Fable is a joke to me.

To me, the most comparable Claude model to 5.6 Sol, OpenAI's flagship, is Opus 5. They have roughly equivalent price (ignoring the temporary promotions on Sol pricing), and in my experience, their output quality is about the same as well; I end up having to put in about the same amount of effort correcting them or giving feedback to achieve a product of comparable quality.

The main difference is in the kind of feedback I have to give; with Sol, I typically end up having to add details to its results, such as instructing it to address missing edge cases, or take a more thorough approach when it took a simpler shortcut to solve my problem instead. With Opus, it usually finds most edge cases for me without having to say anything; but it also goes beyond and keeps finding more and more things, of decreasing and often spurious relevance to my actual problem. My effort usually comes in the form of telling it to ignore those extraneous edge cases and focus on the core of the problem.

But when compared to Fable, neither can hold a candle. Among every task I've ever given any agent, Fable always takes the least amount of time, the fewest tokens, and needs by far the least number of warnings in the prompt or corrections to the output, compared to any other Anthropic or OpenAI model.

To me, to say GPT 5.6 Sol is anywhere close to Fable in any capacity, and not just a competitor to Opus with different tuning, is completely unfathomable to me. You pay twice the price for it and you get your money's worth. Sure it's expensive, and you can run through your weekly limits in hours, but you can't argue that it just works. I can't say the same about Opus or Sol.

Edit: wth is with all the toxicity in the comments jesus. i thought you guys would be appreciative of more anthropic support when everyone on this sub is always complaining about expensive limits and annoying opus.

reddit.com
u/DynaBeast — 1 month ago
▲ 8 r/claude

It must be some kind of psy-op by OpenAI to claim that Sol is anywhere near as good as Fable

I have a ChatGPT Pro subscription and a Claude Max subscription, and use both extensively for work. To claim that any model offered by OpenAI is even close in capability or problem solving ability to Fable is a joke to me.

To me, the most comparable Claude model to 5.6 Sol, OpenAI's flagship, is Opus 5. They have roughly equivalent price (ignoring the temporary promotions on Sol pricing), and in my experience, their output quality is about the same as well; I end up having to put in about the same amount of effort correcting them or giving feedback to achieve a product of comparable quality.

The main difference is in the kind of feedback I have to give; with Sol, I typically end up having to add details to its results, such as instructing it to address missing edge cases, or take a more thorough approach when it took a simpler shortcut to solve my problem instead. With Opus, it usually finds most edge cases for me without having to say anything; but it also goes beyond and keeps finding more and more things, of decreasing and often spurious relevance to my actual problem. My effort usually comes in the form of telling it to ignore those extraneous edge cases and focus on the core of the problem.

But when compared to Fable, neither can hold a candle. Among every task I've ever given any agent, Fable always takes the least amount of time, the fewest tokens, and needs by far the least number of warnings in the prompt or corrections to the output, compared to any other Anthropic or OpenAI model.

To me, to say GPT 5.6 Sol is anywhere close to Fable in any capacity, and not just a competitor to Opus with different tuning, is completely unfathomable to me. You pay twice the price for it and you get your money's worth. Sure it's expensive, and you can run through your weekly limits in hours, but you can't argue that it just works. I can't say the same about Opus or Sol.

reddit.com
u/DynaBeast — 1 month ago

Maurdekye/claude-orgtree: a Multi-agent Orchestrator for Claude Code (& Codex / Gemini)

https://github.com/Maurdekye/claude-orgtree

For the past few months, I've been developing an open-source visual multi-agent orchestrator that organizes agents in an authority hierarchy, for multi-agent development workflows. It's a fully dynamic, draggable canvas that allows you to reorder and reorganize agents as you wish for large projects. The gallery above shows pictures of actual organizations I maintain that I use for various projects I'm working on.

Orgtree started with a simple question: "Man, I wish my chats could talk to each other so they don't keep stepping on each other's toes while working". That turned into a simple personal project that I wrapped up in a day that allowed independent chats to send messages to one another. It worked okay, but the persistent issue I kept running into was chats constant issue with authority: they would distrust all chat-to-chat communication innately, and needed my personal step-in and approval for every little confusion or communication between one another. So I thought to myself, "wouldn't it be better if you could just arrange agents in a hierarchy? Then they wouldn't have any doubts about how authority structure is arranged". That idea slowly grew over time until it became Orgtree.

For the last month, Orgtree is basically the exclusive way I've been interacting with agentic development on my own machine. I don't touch the claude code or codex extensions at all anymore. When I have a new feature to build and plan, instead of going through the manual hassle of spawning one agent to run at a time so I can manage each project individually, I just tell my coordinator agent about an issue or new feature I'd like, and it hires a subordinate to take care of it. If I want multiple features going simultaneously, I just hire multiple subordinates, and the coordinator works between all of them to ensure everything is well organized and shipped sensibly. I've already gotten a few of my coworkers on board to try it, and even my boss is interested.

Orgtree is more than just an orchestrator, though; it has a bunch of extra useful features I've added on to support multi-agent workflows:

  • Usage visibility: View all your account usages directly in the app, without having to check the extension or visit claude.ai
  • Fallback accounts: Supports using multiple simultaneous Claude Code subscriptions at once through the use of fallback keys, allowing you to use secondary or tertiary claude accounts as fallback accounts with the long-standing token you get from running `claude setup-token`.
  • Multi-provider: Orgtee supports not just Claude Code, but also Codex and even Gemini CLI out of the box. If you already have any or all of those environments configured on your system, Orgtree with automatically pick all of them up and let you hire agents from any one of them, letting them all talk to one another seamlessley.
  • Credit system: One of Orgtree's defining features is its credit system, visualized as a blue bar to the left side of each agent. Every live agent takes up a "seat" that holds onto a set amount of credits during its lifetime, roughly proportional to its model cost. Every agent has a bank of credits that it uses both to maintain its own seat, as well as free space to hire seats for subordinates. This credit limit doesn't limit the user in any way (outside of kiosk mode, which is explained below), but is useful for preventing subagents from hiring too many of their own subordinates if you don't wish for them to have the ability to do so. Give an agent a large credit bank for a massive, agentic multi-agent task, or restrict its budget to just its own seat to prevent it from hiring any subordinates at all, if you just want it working on its own.
  • Better compaction: Adds a unique, optional alternative chat compaction method I've dubbed "cheap-compacting": instead of having the agent write up its entire life story in one long turn at the end of its life, it keeps a continuous trail of breadcrumbs in a .md file in its workspace of every task it handles over the course of its lifetime. Then, compaction is both instantaneous and doesn't use a turn: the agent can just immediately resume from where it left off by going off the breadcrumbs. This is also fantastic for waking long-context agents from a long break in execution, as it can automatically cheap-compact them before sending the turn up, preventing the massive cache misses you might typically get from waking an agent with a 500k token context.
  • The Orgtree Mailhub: an optional secondary extension that allows independent agent chats from claude code or codex to speak directly with orgtree orgs or even each other via an MCP server. It even works over the network, so agents on different computers can send messages and coordinate seamlessley.
  • Kiosk mode: A mode that allows you to publicly expose a single sandboxed and resource-limited org to the open internet, in case you want to share your claude or codex usage with friends / family (without fear of them messing with your files)
  • Enhanced agent requests: when an agent has a question for you, or a request for some access / resource allocation, it doesn't have to give you detailed instructions on how to visit its configuration panel and set a particular setting to a value it wants; it can just display a credit grant request / permission increase request directly in-panel for you to review, just like they would present a question to you. This makes it seamless for agents to ask for and receive the permissions they need to get the work done that they need to do.
  • Charter presets: When hiring an agent, you can specify its "charter" (effectively its system prompt) which tells it what to do. Orgtree comes with the ability to select a number of preset charters from a list, so if you have a common workflow pattern you like to replicate, you can canonize it as a charter preset in /docs/charters, and then select it from there every time you want to create an agent bound by it. Orgtree also comes with various preselected charters designed around it's function: one of my favorites is the `coordinator` charter, which I use very frequently, and I suggest you give it a try as well.

Be warned; all the agent-to-agent communication can really chew through usage, so be careful with how many simultaneous projects you're working on at once unless you have a Max x20 account. Make sure to turn on the auto-cheap-compact setting in your org, it can avoid tons of wasted cache miss usage.

If you use Claude Code or Codex for work extensively, then give it a try. It removes so much of the manual hassle of coordinating between agents yourself manually.

u/DynaBeast — 2 months ago

Maurdekye/claude-orgtree: a Multi-agent Orchestrator for Claude Code (& Codex / Gemini)

https://github.com/Maurdekye/claude-orgtree

For the past few months, I've been developing an open-source visual multi-agent orchestrator that organizes agents in an authority hierarchy, for multi-agent development workflows. It's a fully dynamic, draggable canvas that allows you to reorder and reorganize agents as you wish for large projects. The gallery above shows pictures of actual organizations I maintain that I use for various projects I'm working on.

Orgtree started with a simple question: "Man, I wish my chats could talk to each other so they don't keep stepping on each other's toes while working". That turned into a simple personal project that I wrapped up in a day that allowed independent chats to send messages to one another. It worked okay, but the persistent issue I kept running into was chats constant issue with authority: they would distrust all chat-to-chat communication innately, and needed my personal step-in and approval for every little confusion or communication between one another. So I thought to myself, "wouldn't it be better if you could just arrange agents in a hierarchy? Then they wouldn't have any doubts about how authority structure is arranged". That idea slowly grew over time until it became Orgtree.

For the last month, Orgtree is basically the exclusive way I've been interacting with agentic development on my own machine. I don't touch the claude code or codex extensions at all anymore. When I have a new feature to build and plan, instead of going through the manual hassle of spawning one agent to run at a time so I can manage each project individually, I just tell my coordinator agent about an issue or new feature I'd like, and it hires a subordinate to take care of it. If I want multiple features going simultaneously, I just hire multiple subordinates, and the coordinator works between all of them to ensure everything is well organized and shipped sensibly. I've already gotten a few of my coworkers on board to try it, and even my boss is interested.

Orgtree is more than just an orchestrator, though; it has a bunch of extra useful features I've added on to support multi-agent workflows:

  • Usage visibility: View all your account usages directly in the app, without having to check the extension or visit claude.ai
  • Fallback accounts: Supports using multiple simultaneous Claude Code subscriptions at once through the use of fallback keys, allowing you to use secondary or tertiary claude accounts as fallback accounts with the long-standing token you get from running `claude setup-token`.
  • Multi-provider: Orgtee supports not just Claude Code, but also Codex and even Gemini CLI out of the box. If you already have any or all of those environments configured on your system, Orgtree with automatically pick all of them up and let you hire agents from any one of them, letting them all talk to one another seamlessley.
  • Credit system: One of Orgtree's defining features is its credit system, visualized as a blue bar to the left side of each agent. Every live agent takes up a "seat" that holds onto a set amount of credits during its lifetime, roughly proportional to its model cost. Every agent has a bank of credits that it uses both to maintain its own seat, as well as free space to hire seats for subordinates. This credit limit doesn't limit the user in any way (outside of kiosk mode, which is explained below), but is useful for preventing subagents from hiring too many of their own subordinates if you don't wish for them to have the ability to do so. Give an agent a large credit bank for a massive, agentic multi-agent task, or restrict its budget to just its own seat to prevent it from hiring any subordinates at all, if you just want it working on its own.
  • Better compaction: Adds a unique, optional alternative chat compaction method I've dubbed "cheap-compacting": instead of having the agent write up its entire life story in one long turn at the end of its life, it keeps a continuous trail of breadcrumbs in a .md file in its workspace of every task it handles over the course of its lifetime. Then, compaction is both instantaneous and doesn't use a turn: the agent can just immediately resume from where it left off by going off the breadcrumbs. This is also fantastic for waking long-context agents from a long break in execution, as it can automatically cheap-compact them before sending the turn up, preventing the massive cache misses you might typically get from waking an agent with a 500k token context.
  • The Orgtree Mailhub: an optional secondary extension that allows independent agent chats from claude code or codex to speak directly with orgtree orgs or even each other via an MCP server. It even works over the network, so agents on different computers can send messages and coordinate seamlessley.
  • Kiosk mode: A mode that allows you to publicly expose a single sandboxed and resource-limited org to the open internet, in case you want to share your claude or codex usage with friends / family (without fear of them messing with your files)
  • Enhanced agent requests: when an agent has a question for you, or a request for some access / resource allocation, it doesn't have to give you detailed instructions on how to visit its configuration panel and set a particular setting to a value it wants; it can just display a credit grant request / permission increase request directly in-panel for you to review, just like they would present a question to you. This makes it seamless for agents to ask for and receive the permissions they need to get the work done that they need to do.
  • Charter presets: When hiring an agent, you can specify its "charter" (effectively its system prompt) which tells it what to do. Orgtree comes with the ability to select a number of preset charters from a list, so if you have a common workflow pattern you like to replicate, you can canonize it as a charter preset in /docs/charters, and then select it from there every time you want to create an agent bound by it. Orgtree also comes with various preselected charters designed around it's function: one of my favorites is the `coordinator` charter, which I use very frequently, and I suggest you give it a try as well.

Be warned; all the agent-to-agent communication can really chew through usage, so be careful with how many simultaneous projects you're working on at once unless you have a Max x20 account. Make sure to turn on the auto-cheap-compact setting in your org, it can avoid tons of wasted cache miss usage.

If you use Claude Code or Codex for work extensively, then give it a try. It removes so much of the manual hassle of coordinating between agents yourself manually.

u/DynaBeast — 2 months ago

Maurdekye/claude-orgtree: a Multi-agent Orchestrator for Claude Code (& Codex / Gemini)

https://github.com/Maurdekye/claude-orgtree

For the past few months, I've been developing an open-source visual multi-agent orchestrator that organizes agents in an authority hierarchy, for multi-agent development workflows. It's a fully dynamic, draggable canvas that allows you to reorder and reorganize agents as you wish for large projects. The gallery above shows pictures of actual organizations I maintain that I use for various projects I'm working on.

Orgtree started with a simple question: "Man, I wish my chats could talk to each other so they don't keep stepping on each other's toes while working". That turned into a simple personal project that I wrapped up in a day that allowed independent chats to send messages to one another. It worked okay, but the persistent issue I kept running into was chats constant issue with authority: they would distrust all chat-to-chat communication innately, and needed my personal step-in and approval for every little confusion or communication between one another. So I thought to myself, "wouldn't it be better if you could just arrange agents in a hierarchy? Then they wouldn't have any doubts about how authority structure is arranged". That idea slowly grew over time until it became Orgtree.

For the last month, Orgtree is basically the exclusive way I've been interacting with agentic development on my own machine. I don't touch the claude code or codex extensions at all anymore. When I have a new feature to build and plan, instead of going through the manual hassle of spawning one agent to run at a time so I can manage each project individually, I just tell my coordinator agent about an issue or new feature I'd like, and it hires a subordinate to take care of it. If I want multiple features going simultaneously, I just hire multiple subordinates, and the coordinator works between all of them to ensure everything is well organized and shipped sensibly. I've already gotten a few of my coworkers on board to try it, and even my boss is interested.

Orgtree is more than just an orchestrator, though; it has a bunch of extra useful features I've added on to support multi-agent workflows:

  • Usage visibility: View all your account usages directly in the app, without having to check the extension or visit claude.ai
  • Fallback accounts: Supports using multiple simultaneous Claude Code subscriptions at once through the use of fallback keys, allowing you to use secondary or tertiary claude accounts as fallback accounts with the long-standing token you get from running `claude setup-token`.
  • Multi-provider: Orgtee supports not just Claude Code, but also Codex and even Gemini CLI out of the box. If you already have any or all of those environments configured on your system, Orgtree with automatically pick all of them up and let you hire agents from any one of them, letting them all talk to one another seamlessley.
  • Credit system: One of Orgtree's defining features is its credit system, visualized as a blue bar to the left side of each agent. Every live agent takes up a "seat" that holds onto a set amount of credits during its lifetime, roughly proportional to its model cost. Every agent has a bank of credits that it uses both to maintain its own seat, as well as free space to hire seats for subordinates. This credit limit doesn't limit the user in any way (outside of kiosk mode, which is explained below), but is useful for preventing subagents from hiring too many of their own subordinates if you don't wish for them to have the ability to do so. Give an agent a large credit bank for a massive, agentic multi-agent task, or restrict its budget to just its own seat to prevent it from hiring any subordinates at all, if you just want it working on its own.
  • Better compaction: Adds a unique, optional alternative chat compaction method I've dubbed "cheap-compacting": instead of having the agent write up its entire life story in one long turn at the end of its life, it keeps a continuous trail of breadcrumbs in a .md file in its workspace of every task it handles over the course of its lifetime. Then, compaction is both instantaneous and doesn't use a turn: the agent can just immediately resume from where it left off by going off the breadcrumbs. This is also fantastic for waking long-context agents from a long break in execution, as it can automatically cheap-compact them before sending the turn up, preventing the massive cache misses you might typically get from waking an agent with a 500k token context.
  • The Orgtree Mailhub: an optional secondary extension that allows independent agent chats from claude code or codex to speak directly with orgtree orgs or even each other via an MCP server. It even works over the network, so agents on different computers can send messages and coordinate seamlessley.
  • Kiosk mode: A mode that allows you to publicly expose a single sandboxed and resource-limited org to the open internet, in case you want to share your claude or codex usage with friends / family (without fear of them messing with your files)
  • Enhanced agent requests: when an agent has a question for you, or a request for some access / resource allocation, it doesn't have to give you detailed instructions on how to visit its configuration panel and set a particular setting to a value it wants; it can just display a credit grant request / permission increase request directly in-panel for you to review, just like they would present a question to you. This makes it seamless for agents to ask for and receive the permissions they need to get the work done that they need to do.
  • Charter presets: When hiring an agent, you can specify its "charter" (effectively its system prompt) which tells it what to do. Orgtree comes with the ability to select a number of preset charters from a list, so if you have a common workflow pattern you like to replicate, you can canonize it as a charter preset in /docs/charters, and then select it from there every time you want to create an agent bound by it. Orgtree also comes with various preselected charters designed around it's function: one of my favorites is the `coordinator` charter, which I use very frequently, and I suggest you give it a try as well.

Be warned; all the agent-to-agent communication can really chew through usage, so be careful with how many simultaneous projects you're working on at once unless you have a Max x20 account. Make sure to turn on the auto-cheap-compact setting in your org, it can avoid tons of wasted cache miss usage.

If you use Claude Code or Codex for work extensively, then give it a try. It removes so much of the manual hassle of coordinating between agents yourself manually.

u/DynaBeast — 2 months ago

Maurdekye/claude-orgtree: a Multi-agent Orchestrator for Claude Code (& Codex / Gemini)

https://github.com/Maurdekye/claude-orgtree

For the past few months, I've been developing an open-source visual multi-agent orchestrator that organizes agents in an authority hierarchy, for multi-agent development workflows. It's a fully dynamic, draggable canvas that allows you to reorder and reorganize agents as you wish for large projects. The gallery above shows pictures of actual organizations I maintain that I use for various projects I'm working on.

Orgtree started with a simple question: "Man, I wish my chats could talk to each other so they don't keep stepping on each other's toes while working". That turned into a simple personal project that I wrapped up in a day that allowed independent chats to send messages to one another. It worked okay, but the persistent issue I kept running into was chats constant issue with authority: they would distrust all chat-to-chat communication innately, and needed my personal step-in and approval for every little confusion or communication between one another. So I thought to myself, "wouldn't it be better if you could just arrange agents in a hierarchy? Then they wouldn't have any doubts about how authority structure is arranged". That idea slowly grew over time until it became Orgtree.

For the last month, Orgtree is basically the exclusive way I've been interacting with agentic development on my own machine. I don't touch the claude code or codex extensions at all anymore. When I have a new feature to build and plan, instead of going through the manual hassle of spawning one agent to run at a time so I can manage each project individually, I just tell my coordinator agent about an issue or new feature I'd like, and it hires a subordinate to take care of it. If I want multiple features going simultaneously, I just hire multiple subordinates, and the coordinator works between all of them to ensure everything is well organized and shipped sensibly. I've already gotten a few of my coworkers on board to try it, and even my boss is interested.

Orgtree is more than just an orchestrator, though; it has a bunch of extra useful features I've added on to support multi-agent workflows:

  • Usage visibility: View all your account usages directly in the app, without having to check the extension or visit claude.ai
  • Fallback accounts: Supports using multiple simultaneous Claude Code subscriptions at once through the use of fallback keys, allowing you to use secondary or tertiary claude accounts as fallback accounts with the long-standing token you get from running `claude setup-token`.
  • Multi-provider: Orgtee supports not just Claude Code, but also Codex and even Gemini CLI out of the box. If you already have any or all of those environments configured on your system, Orgtree with automatically pick all of them up and let you hire agents from any one of them, letting them all talk to one another seamlessley.
  • Credit system: One of Orgtree's defining features is its credit system, visualized as a blue bar to the left side of each agent. Every live agent takes up a "seat" that holds onto a set amount of credits during its lifetime, roughly proportional to its model cost. Every agent has a bank of credits that it uses both to maintain its own seat, as well as free space to hire seats for subordinates. This credit limit doesn't limit the user in any way (outside of kiosk mode, which is explained below), but is useful for preventing subagents from hiring too many of their own subordinates if you don't wish for them to have the ability to do so. Give an agent a large credit bank for a massive, agentic multi-agent task, or restrict its budget to just its own seat to prevent it from hiring any subordinates at all, if you just want it working on its own.
  • Better compaction: Adds a unique, optional alternative chat compaction method I've dubbed "cheap-compacting": instead of having the agent write up its entire life story in one long turn at the end of it's life, it keeps a continuous trail of breadcrumbs in a .md file in its workspace of every event it handles over the course of its lifetime. Then, compaction is both instantaneous and doesn't use a turn: the agent can just immediately resume from where it left off by going off the breadcrumbs. This is also fantastic for waking long-context agents from a long break in execution, as it can automatically cheap-compact them before sending the turn up, preventing the massive cache misses you might typically get from waking an agent with a 500k token context.
  • The Orgtree Mailhub: an optional secondary extension that allows independent agent chats from claude code or codex to speak directly with orgtree orgs or even each other via an MCP server. It even works over the network, so agents on different computers can send messages and coordinate seamlessley.
  • Kiosk mode: A mode that allows you to publicly expose a single sandboxed and resource-limited org to the open internet, in case you want to share your claude or codex usage with friends / family (without fear of them messing with your files)
  • Enhanced agent requests: when an agent has a question for you, or a request for some access / resource allocation, it doesn't have to give you detailed instructions on how to visit its configuration panel and set a particular setting to a value it wants; it can just display a credit grant request / permission increase request directly in-panel for you to review, just like they would present a question to you. This makes it seamless for agents to ask for and receive the permissions they need to get the work done that they need to do.
  • Charter presets: When hiring an agent, you can specify its "charter" (effectively its system prompt) which tells it what to do. Orgtree comes with the ability to select a number of preset charters from a list, so if you have a common workflow pattern you like to replicate, you can canonize it as a charter preset in /docs/charters, and then select it from there every time you want to create an agent bound by it. Orgtree also comes with various preselected charters designed around it's function: one of my favorites is the `coordinator` charter, which I use very frequently, and I suggest you give it a try as well.

Be warned; all the agent-to-agent communication can really chew through usage, so be careful with how many simultaneous projects you're working on at once unless you have a Max x20 account. Make sure to turn on the auto-cheap-compact setting in your org, it can avoid tons of wasted cache miss usage.

If you use Claude Code or Codex for work extensively, then give it a try. It removes so much of the manual hassle of coordinating between agents yourself manually.

u/DynaBeast — 2 months ago
▲ 1 r/claude

Is Opus 5 less insufferable now?

I swear just the other day I and other people were complaining about how Opus 5 constantly used confusing and unparseable terminology in all of its communications, and how it would easily blow small issues way out of proportion. But today it feels much more chill. It talks smoother, doesn't shove in unnecessarily complicated or confusing terminology, and doesn't constantly latch onto speculative issues. It feels much more like talking to Fable, Sonnet, or 4.8. You think Anthropic released a stealth update to its personality?

reddit.com
u/DynaBeast — 2 months ago

"OpenAI nerfed Sol" "Anyone notice 5.6's performance drop off a cliff recently?"; Maybe there's a better explanation

TL;DR: LLMs not learning over time in comparison to how humans do learn makes people mistakenly believe that LLMs are getting dumber, when in reality they're just not getting smarter.

Every other week I see rampant posts from people claiming OpenAI, or Anthropic, or some other AI company deliberately "nerfed" their model performance to "save compute" or "encourage using the newer models". But that just doesn't make sense to me. None of these companies have ever explicitly stated that they've changed the underlying way their models work without an explicit fresh model release. Maybe they can reduce the compute allocation, but that wouldn't make the models dumber, it would just make your limits tighter or response speed slower. It's still the same bits under the hood.

So, are these constant posts about models being "shadow-nerfed" by their respective companies just delusional users who've started to see past their rose-tinted glasses once the novelty wears off? I actually think there's more to it than that, personally.

Humans are trained to talk in conversation mostly with other humans. In short bursts, a modern LLM can easily mimic the sensation of talking to another human. But over long stretches of time, there's actually a slow, small, impercetible drift that comes down to how humans and LLMs differ on a fundamental, architectural level. Over time, humans learn from their past experiences. They adopt new ideas, learn new speech patterns, correct from earlier mistakes, remember past events, and so on. LLMs are static. They exist in exactly one state permanently, and never change unless new memories are explicitly written into their context.

As humans, being used to talking to other humans, we expect this slow gradual change over time naturally, unconsciously, without thinking about it. People do change, and we've come to expect it. But when an LLM doesn't change over time, when it stays exactly the same indefinitely no matter how long you talk to it or have conversations with it, you might not pick up on that, but your unconscious mind starts to notice. It pins that lack of change up against the expected change that it typically experiences when talking to another human over a long period of time, and that drift appears to it as a degredation in performance.

In reality, its not the LLMs that are getting worse; it's that the humans they compete with are slowly getting better, over time. It's a sort of "intellectual inflation"; the average human sees their friends, family, coworkers, etc. slowly getting smarter and adapting better to their environment over time, while the LLM doesn't change; it just stays at exactly the same level of intellect as the first day you started talking to it. The baseline rose; the LLM didn't adapt to catch up to it. As such, its level of relative intellectual "buying power" fell over time perceptibly, even if the actual fixed amount of intellect it expresses never changed once.

And so, as a result, you get these droves of posts complaining about how OpenAI is "nerfing chatgpt", and despite the irrationality of the claim, tons of users self-report seeing the same phenomenon themselves.

What do you guys think about this?

Btw, none of this was written with AI at all, it's all completely stream of consciousness from my head. I just talk like this now because maybe I spend too much time talking to Claude. Apologies in advance for that.

reddit.com
u/DynaBeast — 3 months ago