1) What AI subscriptions are you personally paying for? (Claude, ChatGPT/Codex, Cursor, etc)
- Which tiers?
- Have you purchased multiple subscriptions from the same provider (eg two Claude accounts)?
2) Are you using models outside (or instead) of those subscriptions? For example, pay-as-you-go APIs, OpenRouter, or locally hosted models.
- Which models and providers?
3) What coding harnesses and interfaces are you using? Are you sticking with the default CLIs or IDE integrations, or using alternatives like OpenCode, Pi, Aider, Muse Code, or custom-built harnesses?
- What made you switch harnesses (if you switched)?
4) Are you using any agent orchestration or swarm tools?
- For example, Munder Difflin, Gas Town, Ruflo, or something custom.
5) Are you using broader agent platforms like OpenClaw / Hermes Agent / Grok bot / Dots / Muse?
- If you are using them, what are your main use cases?
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I know my workflow has differed significantly from a year ago, and so it would be interesting to capture a snapshot today of what people are using and why.
pay-as-you go on openrouter. use latest DeepSeek or Gemini.
I created my own minimalist/task based harness that checks out a jira issue, downloads attachments, runs sandbox docker containers with configurable gh/local repo as volume mounts depending on jira labels, can load agent instructions from local/remote, has scoped/temporary access to targets (e.g. dev k8s cluster, aws/gcp/azure account, ssh, splunk). secrets loaded from external secret management system/env vars. I have 2 repos for storing my personal/corp agent instructions and I 2 separate harness configurations.
Just those.
https://github.com/oscscull/quarterdeck built my own harness. I had trouble with both claude and codex. In particular, managing multiple tasks in a kanban, syncing between my machines, making sure work is done on the right machine and can be triggered from either. Making sure I ping reviewers, meeting reminders, todos. Parking tickets til conditions are met or time elapses. Automated notifications when I have meetings. I have just kept adding features as I want them. This kind of software is so easy to make nowadays, I don't really think there's any sense in "launching" it for others, but I'm using it all the time. I highly recommend doing so (building your own personal work management software in 2026).
I guess this is also in some sense an agent orchestration tool, I don't use any of those.
Don't use.
I'd say the biggest trick is just to tell it what complete looks like. Be very specific about what you want it to come back with once it's done. That gives it a good idea what the goal is. It'll automatically create subagents and all that stuff. Although if you have money to burn and you're doing something large, you can tell it to just go wide or boil the ocean.
Also, make sure you're working on at least five different things. Otherwise, you're sitting around for one agent.
I cycle between 4-5 work projects and 2-3 personal projects. Every night I tell me agents I'll be going to bed and to not ask questions and keep going. I've always loved building things, but this feels more like an addiction than healthy sometimes.
They're not all done, and half the projects I bench, but this is where my personal projects live. https://wooten-labs.com
No you don’t. You are doing everything right :)
If I hint it might be security sensitive code, it bumps the effort level and burns my usage.
But it works quite well.
The findings are often debatable or unreachable states but it does find stuff and improves the overall quality I find.
What's funny though is that it almost always inevitably finds something wrong, even if you just ran it in another window and fixed everything it found. There is really a point of diminishing returns.
As a solopreneur of a boring SMB.
I still do coding and build my own tools but I don’t see the need for agent swarms or Muse or Grok Bot or any of that.
The reason why I stay away is because I like to do QA on the slop these things generate. Having them run amok just makes me nervous.
- DeepSeekHarness (DSH) Desktop using:
—- with pay as you go DeepSeek tokens, more expensive to use during my night/Chinese daytime, otherwise very cheap
—- oMLX on my MacBook driving mostly a Qwen 3.6 35b A3b MOE (mostly used for benchmarking a less capable model)
I mostly do custom subagent programming and can trigger subagents in AGY and DSH easily enough. DSH supports a Python coordinator orchestrating DSH subagents as conversations via RPC. AGY only supports a sub-agent orchestrating other sub-agents but it works well enough at this point. I plan on releasing my subagent framework soon (called autofab in pypi), which is basically a specification driven code development agent system (using existing agent harnesses rather than implementing my own).
I tried goose, OpenClaw, Claude, codex, etc…and they didn’t really work for what I needed. I might get a $100/month ChatGPT subscription to go with my Google one, primarily to get a different perspective and benchmark openAI models on codex (Claude doesn’t really support what I need it to, otherwise would go for that instead).
At work I'm afforded a Claude subscription that is 5x that much usage and I simply cannot use even half. I'm not coding at all anymore at work, just driving Claude. It only needs a bit of direction.
I also use OpenRouter with OpenCode, and a homegrown harness I wrote initially without AI help but later on with AI help. But I haven't used this setup for a while. I swapped models based on the churn as reported by artificialanalysis.ai but they don't release as much data via their free API anymore.
I also can run Qwen 27B A3B on my NVIDIA 5060 Ti 16GB but I don't bother with that anymore either.
I don't use orchestration or swarm. Occasionally Claude spawns a few sub-agents as it needs more data and is preserving it's context window.
2) I use other models via Open Router, but ChatGPT beats them in value (at the moment) thanks to Tibo's resets.
3) I mostly make Claude coordinate a group of Codex agents. They've set up a communication channel between them, and Claude acts as the coordinator and a second verifier. This saves me time because it's easier to talk to one agent than a group of agents. Codex parent session does only "comms" with Claude, and all the other agents run as sub agents.
4) For non coding usecases, I use https://www.ctlflow.com. This lets me run dozens of agents on tasks like equity analysis. The information a swarm of agents can surface from a large data store can be quite surprising.
5) I have tested OpenClaw, but now I just use ctlflow.com or claude + codex.
Can you tell me more about #4 regarding what your heuristics, methods, and use cases are for equity analysis?
I ask because currently I am building a narrow use case Python app using Claude specifically to filter equities that may have an asymmetric potential to buy LEAP options exceeding 1-2+ years.
I am not a finance/quant bro, but I do want to get better at leveraging AI to be a better investor.
Thanks!
Same here. Are you just using a skill or something else. Beyond direct CLI calls to each other, I’m using contextify to share past sessions between them.
How do people handle this?
Do you keep everything in the same conversation thread?
Ask AI to record in a projects directory memory: LOG.md, HANDOFF.md, DECISIONS.md, a plan folder. Reference code with absolute paths. Keep repeatable processes in skills. Version control it all, and use a dreaming process across multiple sessions to stop repeat mistakes.
That's what's worked for me, but there's many variations of this.
Opus 5.5 for 99.9% of tasks. Fable for the rest.
Harness: Claude Code plugin for VS Code. At some point I guess I'll switch to just the claude code app but tbh this is super ergonomic for me.
No agent orchestration besides literally just letting claude spin up agents for me.
No broader systems.
And I'm _massively_ productive with the setup I describe above. I say this not to gloat, I'm sure others have great methods but I do say this in case anyone is feeling overwhelmed by the options out there. My 2 cents is don't overthink it.
Any kind of problem shaped like map reduce can be accelerated this way: Looking through your banking records, searching through a database, asking Claude to find that one weird file you remember from three years ago but forgot where you saved it, etc.
Just know that there’s no quicker way to hit your limits than to use subagents. So use them if it’s paid for by your work or whenever you need the 5x speed boost.
If you focus too much on optimization, and you do so in the wrong ways, you'll actually find you saved no time/money/tokens vs just letting it decide when to do it. This applies as much to Agentic engineering as it did with programming pre-AI.
tl;dr it will literally do it for you, and it'll tell you when it does so
Nothing else, DS is smart enough to do everything I ask for and more, never hallucinates and never disappoints. Apps in Rust, Swift, Node, we even designed a new language better suited for LLMs, a compiler, and it runs beautifully. Haven't coded a single line since May 2026 and I will remember that date as the day AI took over my mundane job as programmer and promoted me to architect or director of my own apps
A custom plugin to ring a bell whenever a task is finished and a gong when a question needs an answer, that way I can play backgammon or mahjong in the meantime
I can't be happier
I primarily use DS v4.1 Flash @ deepinfra.com with less use of GLM 5.3 Flash and GLM 5.3 @ friendli.ai
I use a locked down (i.e. many tools disabled; shell especially) setup of oh-my-pi in benchmarks for comparison.
2) Local LLMs on an M1 Max (Unsloth, LM Studio, occasionally direct llama.cpp). Muse Glimmer (because it is good at what it is optimised for: interactive coding sessions). Qwen 3.8 27B occasionally and a couple of other things for fun (an LFM MoE, experimenting with Nemotron Bolt 74B-9B, enjoying the really super Gemma 4 12B QAT when working on creative photography research or non-code planning).
No openrouter (yet) but that will definitely happen.
3) Currently focusing my attentions on Pi via Paseo (and trying Pendant). Pi is just much better in smaller context sizes, and it is the right fit if you are keen to learn from first principles.
I tried OpenCode first. I couldn’t quite get on with it and what ultimately made me switch was trying to understand its terribly messy source code.
4, 5) I am mostly using AI as a coding sidekick so I don’t really have much need for orchestration yet. I did some experiments with Osaurus (really quite impressive) and I actually think that is almost enough by itself, except that I want a little more control over the sandbox container.
I feel that my usage pattern is still settling, because I am not keen to surrender all of my coding to the machine. But I am trying more purely “directed” coding to learn the process, and finally beginning to get a feel for how I will work with that.
For software dev, I primarily use my own harness/orchestrator (that I shared recently), and sometimes Pi. I switched away from Cline + VS Code primarily because code is being generated so fast that I needed to optimize for review.
My harness is modeled similar to my day job: dev team works on stories, tracked on a kanban, and I'm a code-review gate. For example I scrutinize control surfaces, but instead of reviewing the implementation: I skim it and ask questions.
Every now and then I check to see if other harnesses have what I'm looking for, but none seem to have a combination of:
- Strong sandbox - Particular UX (for mobile, code-review, basic IDE, and task management) - Code checkpoints - Great compatibility with local models
2. Experimenting with qwen3-coder-next 80B and a few other local models for coding tasks on my M4 MBP (128GB RAM) - no other models or pay-as-you-go apis
3. I have a custom built setup primarily driven by claude code via telegram with a checked in "brain", a separate "watch" structure of crons that i can setup and tweak, and then a task farm run by that orchestrator with containerized cc (and a mixture of sonnet and local llms based on task) and application devcontainer stacks (if it's coding related)
4. Custom
5. Custom - mainly rebuilding the ideas from there into my own workflows, but not using any of them directly
Trying to split more things out of CC and use it as a pure harness on route to trying other harnesses out like pi, etc -- it's a work in progress as and when I have the bandwidth.
There’s an excalidraw in the reader
My manager described this as incomprehensible lol but it’s modeled on conductor but uses Claude code terminal and mods and glues a bunch of open source stuff with a cli I had Claude write. Herdr for sessions, nvim for code review / searching, cli invoked by /slash commands. Beads cli for task tracking. With multi repo support since I end up doing a lot at work across repos at work for a “feature” which is how I delineate chats now. And I’ve got a nice picker for swapping sessions so screen real estate isn’t wasted. Many incremental improvements the sum of which are compelling ime
2) Not really, the value proposition on the subs are just so much greater.
3) I'm using Claude Code and Codex, crucially thru Muster[0] which I've been working on. It's a herdr inspired Libghostty-powered terminal which understands agents you're running, helps you manage them, supports remote devenvs, and it provides a CLI for agents to spawn, work, and message each other, no matter the harness and across machines.
4) I'm working on my own factory atm, which combines Muster and Kan[1] which is a offline, Kanban-as-plain-files-in-VCS project I'm working on and happens to work really well with agents. I recently added card dependencies to Kan and a kan ready command so I can have director agents orchestrate and hand out tasks based on what's ready and prioritized in Kan.
5) Not at this time. I played around with dots but I haven't been convinced it can do anything for me that my own solutions aren't better at.
[0] https://github.com/amterp/muster
[1] https://github.com/amterp/kan
Nice! I am guessing the intended use is on developers' own machines, not putting on a server and live co-editing in a team meeting. Pls. let me know if I have misunderstood. Thanks.
I also have an OpenCode Go subscription, so I can keep an eye on the capabilities of the Chinese models.
Opus 5.5 medium for the vast majority of coding and code review tasks. I will sometimes save on tokens by dropping to sonnet if I have a well detailed plan built with opus.
I spend a lot of time on the design/architecture of features. These tasks are assisted by Gen AI but I still need to make a lot of corrections. It's my main bottleneck.
For orchestration and sandboxing I've used plain VMs (I have a make VM script which installs Claude in a fresh VM).
I've used Scion at work, which gave me a lot of ideas and got me excited about building a better orchestration, messaging, sandboxing and web UI thingy which I am currently working on (GitHub link in my profile).
My biggest pain point I wanted to address with my tooling is cleanly separating projects and accesses. I do a lot of web dev and sys admin stuff. I'm building Egzo so I can safely grant and monitor access to remote systems and cloud services and keep myself organized.
2) No.
3) Claude Desktop (home/work). Cut and paste when using Gemini or ChatGPT
4) No
5) No.
Claude Code Desktop on Windows: I like it. Simple UI that I started using about 2-3 months ago and have grown with it. Multiple sessions, virtual groups for sessions, etc. I can see my manual workload of managing things is getting larger so I want better project tooling. Some of the default selections tend to stick with what you selected first and I dont like those aspects (new sessions seems to default to your original/first session folder - so we need to clean that up or create some built-in /new-session skills, etc)
However, what I really want now is voice integration without having to click on the speaker icon and talk to it (or a way to keep the speaker icon depressed) . I want the ability to get off my chair and away from my screen and talk to it. This part is easy, I think, and would be a good start. To close the loop I would like to hear the feedback. However... getting the responses to have a 'conversation modality' instead of a 'verbose text modality/Claude speak output' may be a bigger challenge. The workflow will never be 100% display free. But if we can get the audio aspects worked out, projection could be to a pair of smart glasses (XReal, Apple, Meta, Google) - activated only when needed (read something or see a UI design, etc) and then pushed aside.
Anyone one have a minimal keyboard/display approach working for them?
2) I have API usage via Together for a number of toys I have built for my kid, I probably could refactor this but it predates getting a Claude Pro subscription.
3) Claude Code letting it do the work, pure vibes and dropping to vstudio as needed.
4) No
5) Muse, I have it doing things like basic research, waiting on ticket windows and just being a personal assistant. It also does a really good job at scraping churning forums and blogs and has made a few thousand dollars in the last month just on bank and brokerage bonuses. It does all the record keeping and I just sanity check the dates, hold periods and do the account opening / transfer work. I'm eager to see Anthropic's take on this space and hope it uses the same Chrome integration. Muse's biggest flaw is that it runs it's browser actions from a datacenter instead of a local host and a real browser.
2) I primarily use Qwen 3.8 flash q2 on an R9700 with 4x256k context. I also have some Openrouter credits as an escape hatch if I need it (usually to work on my local AI configuration, sometimes to speed up certain tasks).
3) Pi[1] with a suite of extensions and context files that I have built out myself for the most part, with a few external extensions. One of the main external tools that I really like for coding is openspec[2]. I switched to Pi from Codex because I liked the minimalist philosophy behind it, and because at the time I was using a 7900 XTX (which is now my primary desktop gpu, and I also use for auxiliary services like whisper and decision models), and I was having a hard time getting 100k context with any reasonably useful model. The default prompts of Codex ate into that a lot, and Pi was a much better match for the resources I had.
4) I use Herdr (tui)[3] to manage Pi agents. All agent to agent interactions that I do are ad hoc. I'll do things like tell an agent to spin up work in several other Herdr panes that I have opened with Pi in them, or I will do things like tell an agent to inspect the work of another agent and make sure that it continues to stay on task.
5) No.
[1] https://pi.dev/
[2] https://openspec.dev
[2] https://herdr.dev/tui/
2) yes, when claude starts getting too preachy and the task at hand is important to me i use openrouter + api + chinese models. my computer can't even run qwen 3.8 27b.
3) i use claude code because i think using other ones isn't allowed. i don't really like it, and generally prefer opencode (i've had to use it to do some things for my brother). i'll try using other ones though
4) no, and i didn't actually know they existed. opencode and claude code's agentic things are enough for me, though i don't do actually complex projects
5) no, i won't use them unless i get good local inference going (i.e. never).
Harness: when building/troubleshooting I use https://pi.dev TUI most of the time, the rest of the time is via an issue/PR driven workflow also powered by Pi with this action I built on top of its SDK: https://github.com/shaftoe/awesome-pi-coding-agent/
My general take on AI at https://a.l3x.in/ai
Generally speaking, I think I can hardly be happier than what I am already, the quality of open weight models is incredibly good and the only upgrade I could think of is being able to run one on my workstation one day (I don't even try on my Macbook Air M1), which isn't something crazy to dream about, perhaps in 2/3 years running Deepseek v4 Flash or similar model locally won't require too much of an investment in hardware.
2. No outside models yet. Working on a setup for that. Sometimes I throw some money at openrouter to check out the mega-cheap options.
3. At home I really like goose (TUI), but have been messing with opencode (TUI mode)lately which is also nice. At work I use Zed with a corporate claude subscription and it's a good setup.
4) Not really. I tried some of the opencode swarm plugins awhile back but they didn't seem to work right. In general I don't really have the energy for messsing with a new plugin ecosystem. I also like to work in a _tight_ loop, conversationally as things are being built, steering all the decisions. I have next to no desire to hand a larger task to a "team of AIs" to replace my input with more AI.
5) No
I drive a lot and spend a lot of time talking to GPT voice workshopping ideas, talking at a conceptual level, looking up things I'm curious about, and discussing design and problems I'm having, sometimes even work problems. I use goose for all kinds of stuff, mostly infrastructure and debugging for now but I've written a couple programs with it as well.
My workflow is a windows terminal app with multiple sessions running under wsl2 in each pane since LLMs seem to do better with bash than PowerShell. I don't trust these things much so I've got a careful list of read only tool calls and filesystem sandboxing set up so it can do some useful stuff like read my task board and publish draft PRs without a ton of overbearing permissions prompts.
I usually chat with that for a bit on a task until it's plan sounds good then I have it spin up a Docker Sandbox microvm under Windows so it can safely run yolo mode and make all it's changes. When it's ready I carefully review and iterate on the result until it's ready to publish the PR.
Bit kludgy but strikes a balance of safety and multitasking I'm comfortable with. IME most folks don't think much about isolation so curious to hear if anyone else has a similarly isolated but better workflow. I'd like to try OpenShell instead of docker sbx but it lacks microvm support for windows and I don't want another layer of nested virtualization since my windows machine itself is a cloud VM.
Work also gives me access to GHCP for personal use so I use it for side projects too. Idk what I'd use if I had to pay out of pocket, probably something a cheap Claude plan. For noncoding personal use I mostly just use free tier Gemini. If this stuff ever slows down I'll invest in some GPU nodes for my homelab and run local models.
``` nix run nixpkgs#llama-cpp -- server --models-dir models -m models/gemma-4-12B-it-Q8_0.gguf --port 8080 ```
open http://localhost:8080.
I also run pi in a docker container to do some vibe agentic coding. But I prefer `cat flake.nix | pbcopy` and paste into the browser. Then I can export the jsonl files and use tools to convert them to md and push to GitHub Pages.
I can do most of AI sessions off-line and only need hotspot to sync with GitHub.
My main use case is to learn and hack nix on Mac. It is fun.
I don't even understand how people can spend thousands of dollars a month on LLM tokens since I've accomplished multiple major projects with this setup. In general, Claude's better at frontend and debug and Codex is better at feature implementation and research from what I've found, which is why I have both.
2. No. GPT 6.1 Sol is very token efficient that I pretty much never run out before the end of the week anyways.
3. Default Codex/Claude app. I only use VS/VSCode to hand-edit/git sync things when needed.
4. No. Swarm is a waste of token imo, and a single good human in the loop beats any automated orchestration tool.
5. I find it unnecessary.
At work, I'm using Codex with the subscription they give me, and I don't really have anything to complain about.
I don't bother picking obscure tools and heavily configuring them since almost all of the intelligence is in the model, and models themselves improve so fast that any complicated setup will be obsolete in a few months. All of the useful behavior just gets trained into the models, and all useful functionality gets added into every harness very quickly.
I'm not using any personal agents since I don't see any use case.
2. I have an OpenRouter $50 pay as you go API key that I use for Mercury 3 at this point, primarily for tokens per second. I also use GLM 5.3 when I inevitably get [cyber] blocked (or for reverse engineering in general, apparently) by the morality police at Anthropic.
3. I run things pretty stock. OpenCode with OpenRouter but otherwise I just use Claude code.
4. I've never used these, but I'm curious about them at this point.
5. Not yet, but also interested. My plan is to use Hermes for some personal agent work on a local model, but I have not set it up to test this yet.
I use both Openrouter and OpenCode to get Kimi, GLM, big Qwen, etc, but not at great scale. I have a security product that consumes API tokens that I built against Opus 4 when that was the strongest available; when I get around to it I’ll likely shift it to prefer GLM or Kimi, slightly for cost but mostly for non-refusal.
I spend a lot of time in Claude Code because it’s the only Anthropic subscription-friendly harness. Additionally use OpenCode and codex. Not much time spent in pi these days. I used Aider before Claude Code’s beta. Claude Code’s plugin framework is pretty decent, so I tend to stand up a repo of custom plugins against every client repo I work with. It’s a nice efficiency layer for me up front and often grows into a bonus client deliverable after a couple months of refinement.
OpenClaw runs persistently, mostly for little calendar tasks and trying to mitigate my ADHD: energy level check-ins, redirects to use attention for things that matter. It orchestrates Hermes under the hood but I don’t interact with the latter directly.
I still mostly just use tmux directly and tell running sessions about each other, sending messages to each other via text files or send-keys/capture-pane. Herdr is installed but mostly unused. The GUI clients aren’t my thing; I’m a born console junkie.
What I really want to change next is pulling this all back into emacs.
Full disclosure: I’m the creator of the project.
https://github.com/ferrislucas/Circus-Chief
Now I'm running qwen 3.8 FN + omp + https://github.com/mattpocock/skills
This combination has pretty much "solved" node/react coding for me, running locally on dual RTX 6000, 200-800 tps depending on concurrency.
An incredible time to be alive.
I wanted to really keep Claude but ChatGPT voice mode is too good tbh and no other comes close. I wish I could use Opus 5.5 for coding.
2) OpenRouter PAYG, mostly for experimenting with Chinese models like Deepseek and GLM, usually for stuff that Codex or Grok refuses to do.
Had been looking into NEAR and Venice for completely private information processing (like emails) but haven't set them up yet.
3) Codex, and OpenCode as harnesses basically.
4) I really wish I could decide on some agent orchestrator without trying them out for weeks. I like my tools highly powerful and trying to find recommendation for this online is hopeless because it's full of opinion from people who never used a terminal before.
5) Grok Bot for running experiments with supplements, calory tracking etc.. Tried to set up Hermes a couple of times but hated it every time. Just gave Rakazo a try yesterday and still hating it.
Gosh, I dream about the time when you could look at a github repo and make a decent guess about the quality of the software.
Have a server at home, so mosh into it and run Claude Code at the lowest level. Use Blink off the iPad.
For normal work though, I have a bunch of services set up to run Claude —-remote-control in every one of my projects, so I just use the Claude app on my phone and iPad.
Also maintain and run https://github.com/common-pattern/claudeflow as a service the bigger projects - it’s an orchestrator that reads GitHub issues and starts a Claude one-shot, automatically handling the routine stuff like CI, commits, PR landing flow etc.
2) No. The subscriptions are too much value compared to API. If i were to start using any model on API, the first one I'd consider would probably be Inception Mercury 3, for the 1000t/s speed.
3) I use my own custom kanban agent management tool named Kotkit, which I have been developing since March. It has a built-in multi window desktop which I can use from my phone as a PWA.
4) I am currently building orchestration/swarm capabilities into my tool. Currently adding multi-agent deep research and code review workflows orchestrated by my tool, so that they are cross-provider and my agents can trigger these on demand, as well as experimenting having one agent complete an epic ticket on the kanban board by orchestrating task agents (this is all wired up so AskUserQuestion and ExitPlanMode, etc. on the task agents are answered by the main agent, and if the main agent is unsure, it delegates to me). Currently doing it on a >20-task code migration epic with a lot of success.
5) No. AI is not yet good enough at long-term planning for these to be useful for real work. You have to build step-by-step up to it. These agent platforms are good for simple personal tasks, but to use them for actual work would be skipping a lot of steps.
For day-to-day tasks, I am using Goose (https://goose-docs.ai) with OpenRouter.
2 - No
3 - I use a lot of Opencode + Deepseek, strategize some of that work with Claude Opus, and some gtm, research, and project stuff in Hermes with its coding agent. When I guide by hand I use Orca Dev, which is lovely.
4 - Claude drops GitHub issues that Opencode picks up on a schedule. It’s simple and resilient enough for me. Hermes has a lot of scheduled tasks to move things forward.. it has gtm and research and dev loops (the latter builds autonomously for future projects vis a vis my attention, I’ve used quite a bit of it).
5 - Hermes Agent, which has become a core tech for me. I’ve tried to use Openclaw but it has not been something I can keep running. It spirals and crashes after a week in ways I’ve never experienced from Hermes, doing the same things. I have little interest in those generalist agents, maybe after a year.
2) No
3) Claude Code
4) Custom WIP https://muster.town/
5) Custom personal agent setup https://github.com/mitchellgordon95/miniclaw
Usage is mainly wiki building around personal info (finances, topics of interest), calorie counting, and doing various things from my dumb phone (rideshare booking, checking MTA Bus schedules, etc.)
[1] https://github.com/mickael-kerjean/filestash
[2] https://github.com/mickael-kerjean/fdrive
Also tried Docker Sandboxes which worked fine during the try out but my trust in Docker products with regards to security is low in general, so I'd wanted to wait a bit whether problems show up.
Then used Codex for the built-in sandbox but it's buggy like hell, documented features just do not work properly. Nobody there every seemed to actually try using the stuff they are documenting as working.
Ended up with 3code right now, which also has built-in configurable sandboxing.
2, no, except at work where I have a whole agentic helpdesk system that self improves, creates documentation, and is quite awesome really. Pretty cheap to run also.
3, my own that I keep iterating on, but I do use the clis, though with codex, the app is just awesome, don't use the tui (its good, but the app is better). Claudes app sucks in comparison, though is often better than the TUI.
4, my own tools, mostly because I started on my own ones ages ago.
5, dots, It's kind of like a project manager for the side hustle, its really coordinating a lot of stuff between all the things I have in flight
Had a Hermes set up with a dual NVIDIA DGX Spark and Deepseek v4 Flash, but then built my own harness (getcinnamon.ai) and pretty much switched to that 100% including family members.
I really want to use 6.1 Terra, but the way copilot is set up in visual studio proper, they don't handle reasoning models correctly (or maybe my install is screwed up). Eventually, I will dust off that old winforms project and get my custom harness working with the latest responses API contract.
I prefer (pre) paying for tokens. You can offer me all the proof you want but I'll still never believe that those subsidized tokens are always the same as the ones I get through the API.
It has a 5 hour usage limit, and if using the wonder model, you basically only get 1 or 2 prompts. However, I find it will basically do unlimited 'turns', so as long as I give a good prompt, I can get my work done.
No ide/harness. I only do light coding and don't have time to actually sit at my computer.
Opus 5.5, fast mode, xhigh/max reasoning, ultracode as needed. Usually 5-8 agents going at any given moment. In-house frameworks for Claw-like workflows and agent orchestration.
At home:
Cry
I used to have two Mistral subscriptions, because I needed the extra capacity, but quickly realised I'd need three or more, so switched to the two providers above.
2. Providers covered in the first point. Regarding models I use a combination of GLM5.3, GLM5.3 Flash and Deepseek 4.1 Flash 1017. Which model I use depends on the task. GLM5.3 Flash for general chat and co-ordination tasks. Deepseek 1017 for most coding related work and GML5.3 for adversarial batteries and documentation.
3. Maki[3], although quite customised with various plugins. No python permitted, only Janet for scripting. Extremely limited bash calls, instead preferring to use the built in harness tooling, or plugin tooling I've written. AGENTS and skills used extensively. Mechanical gates also used to prevent certain actions, like remote git pushes without explicit prior approval.
I switched to Maki for the token saving strategies and stayed for the ergonomics, which I think I like, but maybe just feel comfortable with now.
4. None listed. The closest I come is a multipane Zellij setup with different agents running in different panes. Orchestration is still human in the loop though.
5. None
[1] https://melious.ai
[2] https://entrim.ai
[3] https://maki.sh/
2. Locally hosted qwen 3.8 flash next on a wake on lan machine rtx5090
3. Currently orca as front end orchestrator to a mini pc with pi for coding and hermes for general purpose
2) I use models on open router occasionally, primarily GLM and Deepseek models. I’ve experimented with Qwen locally but the models that run on my hardware are too dumb for extended use cases and too slow for quick questions.
3) Personal use: Primarily Zed. I use employer paid Claude Code in the day job but it eats tokens at a rate I’m not willing to pay for for personal use. I’ve tried OpenCode but their security track record is uninspiring and I’m way more defensive about my personal hardware than my employer is about their hardware fleet.
4) No
5) No
Moving towards long-running, asynchronous delegation where I use a locally running instance of Fizzy kanban board to manage and track all work.
When I think of something I might want an agent to do, I create a card. When I want to delegate I assign to agent and move to To Do. I usually try batch things, then use a slash command to invoke a fizzy skill. I do this in a terminal and then close it and do other things.
Couple hours later I'll check the board and see what's in review column for me. Read comments, look over PRs, etc. Agent has broad access to specific project folders and repos.
In general feeling more like working with a colleague than chatting with a bot.
For the actual agents I use Claude Code for my Claude subscription, Codex for my OpenAI subscription (I usually only keep one of those at a time), and pi for my OpenCode Go subscription.
I mostly use Sonnet 5.5 medium and Sol 6.1 medium for everything. But lately I have been using DeepSeek 4.1 Flash a lot and find it very capable.
At work I use T3 Code as well, but it isn't connected to my personal machines or subscriptions and use Github Copilot in T3 Code via ACP. Model choice is similar, but for more involved tasks for architecture analysis or design, big features that touch a lot of interconnected subsystems, etc. I'll turn up reasoning effort to high or use Opus 5.5 on medium or high. But when actually implementing, I try to break up my tasks into smaller pieces and the models usually do well even without reasoning turned up.
Most of my work goes into rewriting prose in reports, commit messages, PR summaries, etc. because all models still struggle with that. (Claude models less than GPT ones in my experience, but still ...)
It is probably weakest at customizability and making sure you have parity in all your agent harnesses with skills/etc, granted I just set an agent to ensure that so the point is a bit moot.
Overall I have really been enjoying the inbox style workflow and it has been a joy to work with. It jives with how I like to work across streams.
2) I have a "live Zoom call audio transcription" setup that uses Silero VAD, Qwen3-ASR-1.7B, Qwen3-4B-Instruct, and pyannote speaker-diarization-community-1.
3) Claude Code in the Desktop UI using remote control environments.
4) Custom orchestrator for having Codex review Claude or vice-versa: https://github.com/navels/neal
5) I have built over time a personal assistant using Claude remote control running on a mac mini, this is likely similar to Dots?
2) yea openrouter free models, usually nemotron coz they have decent availability and I don't get constantly rate limited like with the gemma models on there.
3) honestly still using the default IDE, used to use claude code cli but nowadays i just launch claude remote control and just talk to it through my phone.
4) something custom, i wired it all up in slack so i could easily talk to agents through the same place i do my work
5) Used to use openclaw on a raspberry pi to experiment with like autonomous development but i needed something with a bit more transparency so i moved everything into slack.
Separately I'm evaluating https://ampcode.com/ which is very polished, but I feel like the diff-reading part is not very prominent there which I find a bit odd. After watching many of their videos I feel like that's because they are opinionated on this not being necessary any more as the models are good enough. I kind of agree, but still like to give it a last glance before committing.
I use OpenCode to update my Home Assistant automations. Home Assistant also does two lightweight checks a day using gpt-5-luna (Look at this photo is the pool cover on or off?). I also use OpenCode for a few other small basic tasks.
This is me personally. At work I have a ChatGPT sub an a, seemingly limitless (I don't use it much tho) OpenAI API key.
Herdr is awesome - it pings me when an agent is done or needs my attention and shows me all my terminal panes that are running an agent that I can access with one click.
I am now 90% Herdr terminal, open IDE maybe 1-2 times a day just for more convenient way to look at something. I searched ways to stay in the terminal - found lazygit and love it!
I use long-running worktrees (e.g. named worktree-1, worktree-2, worktree-3, ...) and have parallel work going on in them so I can work on whatever I want.
In each Herdr workspace, I have three tabs: 1st is for ~3 panes, one for Claude and two or more to run the app and basic terminal. Tab 2 for lazy git, and Tab 3 for an extra terminal when I need one. For example, right now I have ~20 Herdr workspaces open now between a few projects, multiple worktrees per project and a few across remote machines ready in case I need them. When in the zone, I might have 1-8+ agents working on completely different tasks.
I have a couple remote machines over SSH that I use when I need a task to run and I need to close my laptop.
I have a keyboard shortcut to init my workspace to that setup. lazygit is amazing.
I ask claude to do everything for me, for example: "Let's do it, open a jira ticket, assign to me and put into sprint. Fix it and open a pr"
I create artifacts all the time to share findings with team or as a checklist of manual testing I need to do.
I find that gh copilit does pretty good review on PRs, and I have a claude skill to go address all the copilot feedback (review, validate, reply, resolve, push changes if any were made).
I was on the 200/mo Claude plan but had to switch to the Team plan, so I pay 120/mo for two users and I swap to the 20 plan when I hit my 5hr limit on my 100/mo plan.
[1]: https://lexfridman.com/podcast -> DHH: Future of Programming, AI, Agentic Engineering, Vibe Coding & Linux [2]: https://herdr.dev/
Focus is pi + self hosted GLM Flash.
Pi is lightweight and easily extensible and creates minimal extra noise. the output I get is very close to what I want to see.
my workflow is focused on clear turns between planning, testing and implementation. Any useful/recurring tasks, like getting/filtering logs, checking statuses etc get regularly folded into a project cli and agent skills that are local to the project.
I spend time interactively iterating on the plan/design and acceptance tests, then let it do its thing. Usually I have multiple interactive sessions at once that I'm steering this way. 1-2 assigned projects, 1-3 side projects (additional automation, experiments/POCs, workflow/process efficiency etc.). I generally don't do sub-agents. When I need throughput I automate first, frontloading the "deterministic" parts.
Obviously not feasible for (just) personal use, the model is too large for consumer hardware.
For 4 years now I’ve tried the latest and greatest once annually before my summer course starts— just to know what to expect and how to instruct. The artificial stuff is definitely getting more refined, but using it doesn’t yet make sense for me personally.
Not committed to using it.
Until recently my mental health post-burnout has been so absolutely poor that I have been learning all of this just to try to concentrate on anything so I don’t feel further out of the loop. Most days I still feel like I should quit IT.
In the limited ways I am actually using it in a productive rather than self-educational sense, I tend to be using it to combat burnout: helping get past blank page problems, rough ideation and keeping track of ideas, doing slightly more cohesive research than just ending up with dozens of open tabs and some unclear notes, generating helper processes (like content migrations) that I might otherwise not be able to make myself write, and exploring using it to do the unthrilling work like automated test generation.
I don’t plan on becoming someone who sits back and specifies loops, and that doesn’t fit with the work I am doing. I have far too many disjointed things I have to work on.
But it is definitely a more varied rubber duck, and that has some potential. I feel a little less stuck, sometimes.
I now use Muse as my primary agent and then spin up and manage Codex and Claude agents as needed on an Oracle server.
2) Yes, trying different models and harnesses through many providers (free/trial). mimo-v2.6-flash, minimax-m3.1-flash, glm-5.3-flash, deepseek-v4.1-flash, gpt-oss:120b, nemotron-3.5.-super-vl.120b-a12b, and others.
3) Mostly eca.dev on Emacs, and Claude Code at work. Now trying the OpenCode one too.
4) No.
5) No.
For my main work at my startup, we're very careful with how these are setup.
Everywhere else, I simmer in chaos.
I also have strong boundaries around generated prose. I don't like making other people read AI slop, but I don't mind having AIs read it.
I get a lot of value from having an LLM to talk to LLMs for me. It can automatically set up adversarial reviews from other ecosystems, or just prompt the implementation LLM to adhere to certain standards. My goal is to have fewer touch points when implementing. I want to speech to text a paragraph or two giving "taste" to the process; everything else is just toil.
我是谁:一名做基础医学数据分析的博士研究生。
2) Yes, Anthropic models usually, at work. Pay as you go API. Company is trialing limits, routers and open weight and even local models. Since the Anthropic 5.5 models none seem reasonable to use any longer (for now at least)
3) Claude Code at work. Tried Aider early on and it failed to even read its initial context (Claude models like a year+ ago). I dropped it dead after that - unusable if you need me to specifically "load" and point our files. That's not agentic coding, sorry. Have not used the actual features my IntelliJ Ultimate subscription provides in quite a long time, though I loathe to tell IT/finance that. I do use it from time to time to double check what Claude tells me. Used `pi` w/ local models (some gemma and qwen that'd run on my hardware. nothing usable w/ the work code base - or much anything for that matter, like I'd not even get through an interview coding challenge with that if you ask me)
Did use Codex maybe like 8 months or so ago to ping pong implementation plans and reviews between GPT and Anthropic models but then just stuck with Anthropic for some reason.
4) Nope.
5) Nope. But we do have our own in-house review agent and software factory agent. Like think CodeRabbit et. al.
2. GLM-5.3 and OpenCode for cybersecurity
3. Primarily custom built harness. Rust centric, heavy on the production engineering gates and a bunch of graph networks for context control.
4. Custom.
5. No.
My general ethos is that if taste is what is important going forward, my code generation must have it's own taste. If you can download my tooling off the shelf, I am replaceable by anyone who can do the same. My end goal is to drop Claude Code once the harness prices start to drift to API pricing. In the meantime, anything that can be automated into traditional and efficient code will be one more thing in my control regardless of future token prices. When I hit my limits for the week, I spend the remainder of the waiting time going over the framework data to see what are my largest sources of consumption and iterate in automating that more.
Since agents can message each other nowadays, most of the time I just talk to one Opus 5.5 session (because of its 1M context window) and let it talk to all the other sessions, acting as an orchestrator that I use from the cli and the mobile app. I also have some of my agents reachable over IRC through a small CLI I'm building.
I subscribe to both Claude and Codex. Mostly at the top tiers, but I downgrade every once in a while based on how much I'm using them.
I don't use Codex directly as much, even though their harness has gotten a lot better and snappier over this year. Most of the time Claude is the one using Codex on my behalf. I was using this delegation workflow a lot until Anthropic fixed the word salad issues on Opus 5.5. Nowadays I mostly do it to load balance my token usage.
I also use locally hosted models (both via CUDA and MLX), but much less for coding unless it's for asynchronous tasks that I can't use subscriptions for. My main use case for local inference is privacy and tinkering.
I've also been building my own harness focused on security and privacy for the past year or so, but it's still a work in progress.
My employer pays for copilot, business plan. It also pays for Gemini.
2) Are you using models outside (or instead) of those subscriptions?
Gemini, company-wide. I mostly use it for general research, making clip art, and occasional programming questions / technical questions. I don't use it everyday, but when I use it, I really like it.
I no longer use ChatGPT or Claude's general-purpose chat bots.
3) What coding harnesses and interfaces are you using? Are you sticking with the default CLIs or IDE integrations, or using alternatives like OpenCode, Pi, Aider, Muse Code, or custom-built harnesses?
IDE integration with Visual Studio, and Copilot code reviews on Github. I mostly use agent mode; sometimes I use ask mode, and sometimes I use plan mode. (One very important thing is to instruct copilot, in .github\copilot-instructions.md, to only use its edit tool and not use Powershell to edit files. Otherwise you need to babysit it and approve cryptic find and replace commands.)
For Copilot in Visual Studio, I almost always use Claude Opus 5.5. Some of the GPT models "appear" to work well, but they leave the code harder to maintain.
We now do a round of Copilot reviews with our pull requests in draft mode before asking others to do the review; and we're not spending as much time "reading" code when looking at pull requests.
We don't (yet) have agents running unattended with high-level instructions and then making pull requests.
4) Are you using any agent orchestration or swarm tools?
No
5) Are you using broader agent platforms like OpenClaw / Hermes Agent / Grok bot / Dots / Muse?
No
------
One important thing: I'm after my boss to dedicate time (1-2 weeks) for me to set up and learn more of the hands-off tools. I love working with co-pilot, but it's best for work where I need to be hands-on. I really need to be able to offload simple work, or work where lower-quality results are okay, to a bot that I don't need to supervise.
2) I tried a local Qwen model but my poor old 1660 Ti did not enjoy it, and it wasn't all that useful.
3) I primarily use OpenCode running in a podman container for actually working on stuff. Also use the default free chats with Gemini 3.5 Flash for general searching, ChatGPT for brainstorming, and Claude to answer more code related things if they come up.
4) Nope.
5) Not at the moment. I've been eyeing using Hermes, but since I don't feel comfortable paying much at the moment I haven't really tried.
2) pretty much just opus
3) claude code - but with Orca + app (being able to dev remotely via the app has been great for personal projects)
Work has me stuck with Cursor, which I don't find as good, even when using claude models.
I've moved all my ssh keys into a key-agent which prompts for key use as I got alarmed by claude attempting to login to remote systems to verify things as it worked through problems.
2. Kimi on OpenRouter, Abliterated.ai as needed
3. Claude Code (with all models), Claude Desktop, tried pi.dev, opencode
4. No
5. No
Main use case(s):
- Software applications
- One-off automations (calendar sync from scraped data, email alerts)
- Deep research and planning for personal stuff
things i run locally using apple mlx models: general llm, coding llm, text-to-image, text-to-video, image-to-video, text-to-music,
everything is holding up well. I may eventually swap the m1 max for a higher memory bandwidth device once they are available for a reasonable price in 6+ years
I generally use open weight models (Kimi K3.1, Mistral Large 4, GLM-5.3, DeepSeek v4.1 Flash, Mimo v2.6 Pro is the current quiver) but I use closed frontiers enough to stay up to date.
2) I use OpenRouter if I have a specific need, audio transcription (MAI-Transcribe 2) being something I use often enough. Also using it just to test random models.
Not much local anymore except classifiers / decision models that I've played with.
3) Pi all the way.
4) I use Paseo to orchestrate agents, I have a couple plugins I've written for it that manages pipelines and such. I generally start a workflow with a simple skill and if it proves useful I like to make it deterministic if possible. Models be dumb sometimes.
6) No but I have some Paseo plugins for personal use, though it's very limited what I find useful. I also don't find that I want any claw type stuff at all.
2) No.
3) None.
4) No.
5) No.
2. I use both qwen 3.6 35b-a3b and qwen 3.8 27b on my Macbook Pro (M5 Pro, 48GB, 18/20). I use those with ollama and hermes (and Obsidian, to an extent)
3. Hermes Agent, Claude CLI and Claude in VS Code
4. No
5. Hermes Agent
I use a carefully curated selection of agents for my professional work. Agents to handle adversarial code review, planning, questioning, dev work, etc. I also have custom instructions for various repos that need them (where I can define things like repo norms that are not immediately obvious, data models where needed, etc.
I tried setting up a script so Claude could automatically call agy, but it kept hitting timeouts, and letting Claude control that tends to burn my usage too quickly anyway (and if I'm not copy-pasting into different terminals, where's my value add in all this?).
Argon hallucinates, so I rarely use it for impl, but I've actually had better results with it than Opus for SwiftUI and AppKit work.
I try not to run more than three sessions at once, or I get anxiety about having to keep all the session caches fresh and end up typing silly things into some of them every 30-45 min so they don't expire or auto-compact.
I'm sticking with Default CLI/Desktop apps + built my own to combine them for my specific workflows. Used previously OpenClaw and Hermes but it seems to fall apart when you give it any real work. Ending up giving up because I just don't have to tinker / fine-tune it.
I will say, I enjoy Muse a lot for some reason for personal things. I don't overshare anything I wouldn't mind saying in public.
Within the last month, I basically use Claude Design exclusively for front end work and Codex for backend work. Codex just works but sucks as design. Claude is great at design (with enough references) but can't seem to actually get anything to completion.
I've had the same experience as you with Claude, and I have to choose a single subscription, so I'm on Codex. I definitely wish I had access to Opus 5.5 right now.
1a) OpenAI API subscription, integrated into an office suite + media pipeline I wrote 1b) OpenAI codex $100 mo plan
2) Current count, 318 additional generative models across LLMs and then media generation of image, voice, music and video. The LLMs are mostly Qwen variants, and the media models are pretty much all the popular media models. These are organized, managed, and API operated locally through WanGP (open source model host) and two additional apps I wrote. One of those apps is a mobile phone pairing remote live video processor, so one can use their phone like a remote live camera at events, and the other is a plugin to WanGP so my software can securely operate WanGP remotely.
3) I use OpenAI Codex in a terminal as a coding assistant. Through that same account I also run the OpenAI Desktop app, and that integrates with my web apps through WebMCP and two additional types of agents in my apps: 1) all my UIs have knowledge assistants that explain how to use the UI they are associated, and they know more complex workflows that UI is a component. 2) My apps have "method actor agents" that are conversationally programmable experts located on specific interfaces, which users then tune to be experts in their work tasks. That's like a smart assembly line worker waiting to be told what they are making. Then, through WebMCP, external agents will interact with my app resident agents, and together they act. Which is kind of amazing. So, in a way, they create a harness through their collaboration, which also includes the user, collaboratively.
4 & 5) no.
My work interest is in creating an environment that promotes deep intellectual flow. One could use my setup and automate a bunch of things and sit back while their brain rots. Or one can also participate in the work at an interactive creative stream level, where the agents and software are doing work but all the creative and impactful decisions delegate to you. You're in complete control over a swarm of virtual expert personalities that work for you, and you make their decisions. The work is office and media, which is broad.
2. OpenRouter PAYG - glm or opus for most things
3. OMP or CC
4. Zellij/Vim — some things never change
5. No
I've rarely been so inspired by a project.
It's publicly readable, but writable by a group of ~20.
https://magenta.cryptograss.live/
I spend about $5 a month with this setup.
2. I use OpenAI/Anthropic APIs for various workloads (app features, automations, etc.), but not for personal inference/coding. Recently both of these providers started giving $200/mo in API credits, and OpenAI already gives free tokens, so I don't usually pay for this usage.
3. I always use the provider's preferred CLI: Claude Code, Codex CLI, Grok CLI, Kimi CLI, Antigravity CLI, Muse CLI. I use this with herdr to manage everything, and then a small custom app to keep track of my usages since I hit limits quite often.
4. No. Just the CLIs. For very large projects I've found Claude Code to be the best -- it can very easily manage many subagents.
5. I've tried OpenClaw, Hermes, Dots, and Muse. I really just haven't found great use cases for these tools
I use Claude & Codex for most of my personal coding/projects. For the other providers I mostly want to have broad experience with different models/harnesses. It's very interesting to see how each performs and what kind of tasks they do/don't excel out. The only con of having cheap plans is you really can only give them simple tasks.
---
At work I use AWS Bedrock w/ Anthropic + OpenAI models at API pricing. Each employee is given a rolling 28-day budget w/o access to Fable/Astra. I use the same Claude Code/Codex CLI + Herdr.
2. OpenRouter, DeepSeek, Luna, and testing out models here and there
3. Claude Code and Codex for the respective subscriptions. Played with OpenCode and Pi some as well
4. I've tried a number of these tools and settled on my own tool (not released) to oversee my agents
5. Played with OpenClaw and Hermes in the past, cool ideas but execution fell flat. I currently use Dots and Duet for little things (mostly monitoring communications). Dots is much better than Duet today but I hope Duet gets better.
2) Not really, messed around with Openrouter and Deepseek for some stuff that Claude refused to do
3) I use Claude Desktop (Linux) and a heavily modified pi.dev at work VSCode as IDE. At home just use the iOS app and Claude Desktop (Windows).
4) No
5) I have Hermes Agent setup at work and home but don't really use it.
In my personal life, I'm extensively using Hermes. If you look at some previous comments you can see what I use it for. I genuinely think personal AI agents are the future, the way I feel when I use it is how I felt when I tried out the first iPhone. In 5 years time, I think most people will have a personal AI agent in the same way the most people now have an e-mail address.
2. Yes, per above
3. Mostly Claude Code, occasionally OpenCode and Codex. Rex/Ghostty as the interface to it all.
4. Yes, lightly, a custom orchestrator
5. Not actively, have tried most ex Grok Bot, but haven't taken the time
- setup windows 11 with Rufus boot to disable online MS account creation https://rufus.ie/en/
- [download window 11 x64 iso from here ](https://www.microsoft.com/en-us/software-download/windows11)
- then download vmware workstation pro (you ll need to create a free account to get the download link on their website)
- install vmware workstation pro
- turn internet off
- plug your pendrive in with the rufus w11 x64 iso on it (mind ya, this pen drive ll first need full formatting before burning a w11 image to it)
- press f2 to reach bios in vmware settings and make it boot from pendrive
- turn internet off on your machine (DO NOT keep it on)
- install w11 (keep a 100gb for vmware)
- without updates it ll load real fast and you wont need an MS account (rufus takes care of it)
- while it installs, download revo uninstaller pro on a separate machine https://onefiles.net/9d170d01078634b5 (latest version 5.4.x) and put it inside a second pendrive / portable hdd
- once w11 loads, it ll ask you to enter a password, keep existing password blank and enter literally anything for a new password
- voila you are done with w11 setup inside vmware
- now connect the 2nd pendrive with revo and install it (need to clean uninstall many tools, hence we need this one)
- now go to search bar and type check for updates and update everything on w11 inside vmware
- next stop get unigetui from ms app store or from here https://devolutions.net/unigetui/ (it is a package manager responsible for installing just about everything else with auto updation of all packages)
- the open unigetui and search for the following packages vlc, winrar, winhance
- winhance is the fully customizable debloater you ll need to turn off all telemetry (we ll debloat after installing all the other requirements)
- next go to ms app store and install python or open powershell and type python
- the open unigetui and search for the following packages vlc, winrar, winhance
- winhance is the fully customizable debloater you ll need to turn off all telemetry (we ll debloat after installing all the other requirements)
- next go to ms app store and install python or open powershell and type python
- mind you this installs a python version manager that lets you install and uninstall multiple python versions
- after this python version manager is setup, install a specific version of python like
``` py install 3.13 ``` - next we need a node.js version manager, use fnm for it
https://github.com/Schniz/fnm - once installed, it may need to be added to environment variables manually
- once again choose a specific version of node.js and install it using
``` fnm install 23.12.0 ``` check fnm --help for commands - next we need a java version manager, use jvms for it
https://github.com/ystyle/jvms
- pretty self explanatory
- now install git and again it ll give you some trouble over environment variables, command not recognized etc, fixable with some gpt help
- at this point, we got git, node version manager, java version manager and python version manager and are ready to rumble
- install vscode/ visual studio whatever
- install codex
- install claude
- install opencode (both cli via npx and desktop app) and check their plans out https://opencode.ai/console/go
- install ghidra , ghidra-mcp (mind you open ghidra-mcp first because it only works with specific versions of ghidra and java) this is the reason we installed a java version manager
- check out setup for rea https://github.com/morluto/rea requires npx setup for rea and ghidra both, read documentation
- run winhance, check recommended settings under optimize and every other tab and restart the vm a few times for full debloat with 0 telemetry services
- congrats you have a full blown agentic environment at this point (if I missed anything i ll come back and update)
2) personally, no. At work there is a Gemini Enterprise and Kiro Pro+ subscriptions
3) pi.dev inside herdr; both at home and work. I just pile the APIkeys and stick to same harness.
4) mostly, pi-subagents has an orchestration mode
5) no.
1) None
2) No
3) None
4) No
5) No
In my day job I use Claude Code & Codex subscriptions (Codex is mostly for review, second opinion, and as a backup).
Personally I use both oh-my-pi and Hermes with a Codex subscription. I tend to use OMP more now though, since I find its interface a bit nicer when working on the laptop.
2) I do use Openrouter for side projects that need an embedded AI. For example, on Halloween I made a talking pumpkin to greet trick or treaters as they came to the porch.
3) Mostly code. I've tried muse, grok, gemini, codex, and pi w/ openrouter, but I always come back to code.
4) no
5) I have a grok bot account I use to manage personal stuff. It organizes my email and calendar, keeps me up-to-date on news, does health tracking, trip planning, and shopping research. As an example, there's a website where I order lunch for my kids. I like to know each morning if I need to pack their lunch, so I have grok bot log into the website and sync it to my calendar. I then get a notification in the morning with everything I need to start the day, like whether to pack lunches, what the weather will be, or if I need to help my kids study for a test.
Most coding via Opus 5.5.
Codex for text and some non-coding tasks.
Separate virtual desktop and clone on dev drive with VScode for each task (much prefer its diff tool and use it to launch builds etc).
I never come close to running out of tokens because I still do code reviews often enough to throttle usage.
It's a solid groove. Grok Bot helped me get so much stuff off of my plate.
2) No.
3) Opus 5.5 on high for all the work. Reviewed by Codex by default. Additionally by Grok and Gemini (agy) for critical work.
I switched from Claude CLI to a custom-built harness because I got overwhelmed by walls of text in parallel sessions. Now I have a canvas per project where I spatially lay out cards. Each card spawns an agent in a worktree. The chat with it is condensed to WhatsApp style chat bubbles with all the thinking and tool calls folded away. The result of a card is a demo, usually a narrated video that I can comment on to trigger another iteration. Everything voice first, I mostly speak. Phone companion so I can keep working on the go.
I used to work with up to 6 Claude CLIs in parallel and couldn't go further. With my custom UX, I can do 20+ with fun. Now the bottleneck is actually my machine, so I added remote worker support to my harness to distribute the load to more machines.
(I open sourced the harness in the hope of sharing the fun. If you want to try it: https://github.com/sadilek/obeya)
4) No Paperclip or Munder Difflin or anything. I actually think it doesn't make sense to create persistent agent personas. Just spawn an agent when needed, give each full access to all skills and docs, and they'll figure it out.
5) Hermes Agent running, sending me regular news research reports, but frankly, it's just a cronjob and the whole Hermes setup isn't really adding value for me.
I try to use open weight and cheap models as much as possible.
2) Openrouter. I don't have a preference right now. All the top open-weight models work fine for my projects. Currently using Mistral.
3) I used pi for a while and lately I started using openrouter's ori coding agent. Working great so far.
4) None
5) None. I tried Muse for a while and it was too slow to do anything useful.
2. Pay-per-token for work through Vercel AI Gateway (mainly same models + grok, but trying out others too)
3. Claude Code, Codex & OpenCode
4. Homebuilt https://svall.dev/
5. No
Work provides an enterprise Claude subscription for work stuff, I've never hit any limits on that either.
I also gave in after seeing my co-founder use it, and gave GrokBot a go. I use this for everything that's not coding or design... so marketing, email reading, right now it's currently inputting my meter readings to my electricity company after emailing the building management company and getting photos back. It's super useful at little chores that eat up time. I have it daily check the status of my various projects and services. I love it tbh. I've also built my own version, which I might move to... though now it's all set up it's quite sticky, and it already spotted an error my accountant made on some taxes so it's already saving me money and I'm feeling quite positive about it.
I'm getting a bit frustrated with having to run things on my laptops though -- it feels a little pets not cattle, and wish it was all in the cloud. I'm toying with building out an agent factory, but frankly there's no super-cheap way of doing this so I'm holding off, though I can see me building a tool that connects those laptops to it creating sandboxes with Apple's `container` (which I'm using successfully on my grokbot replacement).
No. I moved off of subscriptions earlier this year. I don't trust the subscription model from any frontier lab. Just look at what Anthropic has done. The first time I tripped a safety classifier on a seemingly irrelevant task, I canceled everything.
2) Are you using models outside (or instead) of those subscriptions? For example, pay-as-you-go APIs, OpenRouter, or locally hosted models.
Local first. I have a box running Muse Spark on my desk. My main inference box is a launch day DGX Spark (I saw the hardware shortage coming) and has my entire local AI stack. OpenWebUI and everything that feeds it. I moved away from SearXNG and started using SlopSearX (it's quite good).
Everything else goes to Openrouter. I use few models but GPT-6 Luna is my go-to, sometimes I switch it up. Really depends on the task I need to perform.
3) What coding harnesses and interfaces are you using? Are you sticking with the default CLIs or IDE integrations, or using alternatives like OpenCode, Pi, Aider, Muse Code, or custom-built harnesses?
Github Copilot for work. It's meh. Personal projects and general personal use? I started with OpenCode and have since migrated to Pi (omp specifically).
4) Are you using any agent orchestration or swarm tools?
I thought about it. I haven't really felt like I would derive value from changing my workflow and tools. It took me a while to find a good mix of utility, control, and efficiency and haven't wanted to change it until at least next year.
5) Are you using broader agent platforms like OpenClaw / Hermes Agent / Grok bot / Dots / Muse?
I have a dedicated Mac Mini to run Hermes. It is pretty much integrated into my entire life now. I could live without it, but automating general purpose things is the entire point of why I put that machine together.
How is this different from this time last year? Radically different to say the least. The pace of change has been EXTRAORDINARY to say the least.
No harnesses right now. Ok occasion using models in LocalLM.
Haven't got into agent orchestration much other than Paperclip earlier this year.
3) I use both Opencode and Pi.
2) My main model is Deepseek flash via the API.
3) Claude Code CLI inside OpenShell. I like Claude Code's UX. Lots of custom skills and scripts.
4) No
5) No
1. Claude Max (upsold me as of today); generally Sonnet 5.5 with the occasional Fable 5.1 when it gets stuck or I am executing a high value step; and Perplexity Pro (legacy).
2. Mostly local voice-to-text w/Parakeet Unified EN 0.6B via Handy[0] (awesome; use it!). Not for coding, but for note taking, AI interfacing, and general typing reduction and RSI avoidance.
3. None. I tried Pi and after much kerfuffle I don't like any of the harness interfaces. I find the type of work I do they are not very useful, because I often switch between variant approaches, planning, data, and don't want unrestrained context bloat.
4. No.
5. No.
I would add that I am very interested in obtaining good enough hardware to run this level of model locally at any pace, believe Qwen is basically there but too slow locally to use as a daily driver on my current rig, and can see myself making that investment in single digit years. Not right now, the hardware is overpriced for what it is versus venture funded cloud AI subsidies.
[0] https://handy.computer/
2. Early in experiments with locally hosted GLM Next, not writing code with it beyond experiments.
3. Claude Code, system prompt, minimal skills; mostly bash scripts for common actions.
4. tmux send-keys for messaging between panes.
5. No. Claude Code does that, too.
Keeping it simple.
2. Also have some API keys for some open weight models in Europe, but currently not using those.
3. I've personally used OpenCode, Claude Code and Codex and of those, I liked Codex the most, till bugs kept on accumulating and they started doing all kinds of shit like that daemon recently. I now switched to https://github.com/capocasa/3code which is a small, simple agent harness but with built-in sandbox, unlike so many other simple harnesses. I really like this one, plus the author is very responsive to feedback
4. No. And I don't think that stuff works in the long run with current quality of code output
5. No.
I avoided building anything custom until I had to, and I avoided adding more than a single agent until I had to.
My preferred way to use AI for coding has been to work closely with a single coding agent with the code open. That changed wth 5.6-Sol and a handful of skill files. I stopped needing to watch closely to keep it from fucking up the codebase. With the right request, that combination will get the job done 9/10 times.
That unlocked a new workflow: as soon as a change is requested, a coding agent reads it and gives me a PR. I want a complete proposed code change in front of my eyeballs by the time I open the change request myself.
So I have a custom solution in place to manage a handful of agents aligned with this workflow.
Custom solutions are so cheap and easy now... it's really hard to put up with solutions that are only mostly right for the job.
- agents work in their own lxc spawn automatically in a proxmox node, where they can go wild without sandboxing or isolation, network is firewalled too
- all sync sessions and everything to a centralized agentsview in a realtime, where I get to track and watch it from anywhere on the go
- i just ssh into the lxc if i needed anything
- different harnesses depending on the task, maki is great one, but I use others
- I also have other stuff but I won’t mention it here regarding the tokens for obvious reasons
I tried most of the tools like herdr or paseo or desktop clients but they never clicked with me
2.) Text Editor or IDE.
3.) A compiler/interpreter/SDK and potentially other dependencies.
Super lame and boring, but that's basically it.
As for my day job, it's the same minus #1 -- AI is banned.
2) kapitsa + pi + Qwen 3.6 35B a3B q4. pi is the harness, kapitsa is the inference engine
people that I considered intelligent have associated Qwen with "chinese cloud" when it implies not using a cloud at all. I think that's weird. I think there is a "western" centric view that limits perspective to using A cloud, instead of aspiring for locally run
1) I also pay for Claude, I should downgrade again to the $100 plan, thanks for the reminder, but currently the $200 max x5 plan
4) no. I handroll my agents
5) I use Claude desktop as an agent platform
1. Claude Code with $20 Claude subscription. This used to be a terrible value but now it's a great value, probably because of the IPO. I do a lot of coding and other things and I rarely get close to my weekly limit. I mostly use Opus 5.5 medium. Codex with gpt used to be good value but recently I canceled it cause I kept reaching my limits.
2. When I want a "different pair of eyes" to review things I'm working on with Opus, I use Pi with other model providers and just pay API prices.
3. Deepseek harness with a deepseek API key. Really great value.
4. I have a Muse $5/month subscription that I keep as a backup although I don't really need it.
I also use cloud agents to setup reoccurring jobs. For expensive agent runs, like visit 5000 websites and extract something from each, I would set up something cheap with an agents sdk and for the model use either Muse, Deepseek, or GPT-6-luna using their batch API.
I maintain all my dotfiles and agent files / context in a github repo so that I can switch easily between harnesses and providers.
2. No (only the API for projects)
3. Buzzpot.app (my app)
4. No
5. No (I tried them, but couldn't find a use case for them)
2) payg on opencode
3) standard claude code and opencode driven by t3 code
4) nope
5) grok bot - at work, to manage my tasks, and to highlight what happened on slack when i was off; random one offs there
Openclaw is the answer to question "do X if Y happens". An agent per each type of Y channel manages the flow and memory. And user input is just another case of 'Y'. It is a very powerful model I am having lots of fun with it.
the plumbing is a chore though, thinking of trying out grokbots to see if they solved it.
1.b) For personal stuff I maintain an Opencode GO subscription, USD40 tier. I also have a Google One subscription which is supposed to have some AI capabilities, haven't tested it yet.
2) Besides my Opencode GO subscription, I sometimes add a few bucks to use Zen. It's rare: my USD40 is usually fine for the month. I've recently started using Nvivia NIM free tier models for some time insensitive tasks too. I have a Qwen model available on my Mac (M1 PRO 64GB) but haven't found it to be useful, as I need my laptop for everything else I'm doing beyond inference.
GLM 5.3 Flash and Deepseek 4.1 Flash do most of the work for my personal stuff. Nemotron does the time insensitive stuff, which is mostly summarizing text. I've been using GPT Luna 6 a lot because it's currently cheap as hell, so I'll often talk to GPT Luna and hand off coding to GLM or Deepseek. I find that Luna communicates MUCH better than the Chinese models - I assume because it does not go through the extra language barrier step between English and Chinese. GLM, Qwen and Deepseek are incredible tool callers, but their prose is insufferable.
3.a) At work I'm using Claude Code for the Anthropic models and Opencode for the self-hosted ones. Ditched Cursor recently. I've been meaning to try to integrate the self-hosted models into Claude Code but haven't yet, so hand-offs between the two harnesses involve a lot of markdown.
I've switched out of Cursor because A. they've been bullying us into using grok for everything and B. The company setup would not support the use case of mixing the self-hosted and closed models in the same harness - this limitation is on our side.
3.b) For my personal stuff I've been using mostly Hermes. Some actual coding goes into Opencode, often piloted by Hermes itself. I'm using Zed as my code editor, but with the AI features disabled. My opencode subscription is actually configured in Zed, but I prefer the UI without them.
4) No. I don't really need them. I run 5-6 parallel sessions at most, otherwise I can't keep track of what's being done anyway. Each parallel session is on a different task, so I generally don't need them to spit enormous amounts of code. I rarely have to wait more than a few minutes for a task to finish, and I'm always thinking or writing or managing something else in between anyway - not looking at the screen waiting.
5) Hermes. Generally happy with it - despite it being extremely unstable between updates, with frequent regressions, weird UI bugs and half assed features (bot mode, anyone?). I have 3 distinct instances (laptop, home server, VPS) doing different things - all hooked up to the same memory provider (honcho) under a single user profile, and a handful AI profiles on each. All have limited access to my Obsidian Vault, which is synced between them using Obsidian Sync.
I generally use the laptop instance for day-to-day use: planning work, assigning tasks to myself and to the other agents, capturing ideas, light coding, etc. The homeserver instance manages a limited set of features on the server itself, from upgrades, documentation and more devopsy stuff to organizing files, managing transcoding queues, etc. The cloud hosted version automates is not very used yet. I plan to have it pilot an n8n instance I keep to automate some boring stuff, like filing weekly tax records and automatically forwarding bureaucratic e-mails, nothing fancy.
I am just getting into setting up Hermes on a VPS. If you have any high ROI tips/tricks/advice on how to make this work well, please let me know!
Appreciate it!