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.
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.
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.
I think the only solution there is self-hosted inference (either local, or on your own cloud servers with open weights).
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 :)
ex. i tried cool walk (https://wooten-labs.com/coolwalk) and the 'Download on the App Store' does nothing at all.
*unfortunately I'm android
I do wish the Github link wasn't borked.
Claude Desktop's UI seems pretty similar to Cursor now, almost. I'm still on Cursor but if I use it daily I often hit usage limits before the end of the month. Would you say using Claude directly is better bang for buck?
Yeah, exactly. I find increasingly little use for skills. I'd put it down to switching projects and stacks a lot but maybe... they just aren't as useful any more?
At the same time when I’m exploring new feature requests I now use the skill to write up the requirements and estimates into as many tickets as needed.
Massively changed my workflow for me.
I try to use open weight and cheap models as much as possible.
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.
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
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.
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.
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 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.
No harnesses right now. Ok occasion using models in LocalLM.
Haven't got into agent orchestration much other than Paperclip earlier this year.
2) No.
3) None.
4) No.
5) No.
It's a solid groove. Grok Bot helped me get so much stuff off of my plate.
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 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
[3] https://maki.sh/
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.
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.
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 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.
Theo of T3 Code has made a recent video about its features.
A few examples of why I like it:
- Not having to use multiple agents (you can switch them mid-conversation with automatic handoff if you want)
- The way it handles environments (I can start a new session on any environment (machine) with two clicks (new thread -> pick project on any environment)
- I can ask for visual responses (uses a T3 Code tool and renders a html page inside chat with cards, charts, etc. that follow the currently selected color theme (even if you change the theme after the response has been generated)
- MCP tools like browser, webfetch, etc. so I don't have to set them up for every agent
- Thread handling: Snooze, Settle, Archive, Delete. It's the only tool where I don't get overwhelmed when working on multiple Threads/Projects at the same time (I am diagnosed with ADHD).
- Provider usage overview for all registered providers, showing pacing as well
- Great citation: when you make a selection in chat, a pill appears and you can create quotation elements that get added to that, can easily be edited or removed (the original reason why I even tried T3 Code in the first place, because it makes responding to long responses incredibly joyful instead of disorienting). I like it so much that I added the same mechanism to my own personal assistant/agent that I host on my VPS.
- Great diffing view where you can pick worktree diffs, or any diff from a specific turn in the current thread
- Has it's own subagent orchestration that's very pleasant to use
- Many more little things that remove a lot of friction and just feel right for me.
It's just baffling to me how it is better in every regard than every other harness that I've ever tried (Claude Desktop, Github Copilot App, OpenCode Desktop, all the CLIs, Integrated Agents in VSCode and Zed, etc.)
I will still start up a pi on the cli if I just have a quick question because T3 Code needs a bit to start up and connect to all providers/environments. This is my only point of friction: It's a bit heavy on resources (because it does a lot, not because it's slow. I just happen to use it on very old hardware and on one device that is very slowed down due to heavy-handed security scanning). But other than that, I can't imagine using anything else right now.
I don't know if I've ever been this exciting about a piece of software. I was very sceptical at first, but quickly fell in love with it.
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)
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) 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
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.
Work provides an enterprise Claude subscription for work stuff, I've never hit any limits on that either.
Keeping it simple.
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.
The wrapper also keeps history, memory, etc. split by project folder, so agents working in different projects don't know each others' history. If anything, `--resume` is a split second easier.
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.
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) 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. 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
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
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.
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
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. 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.
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.
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.
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.
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.
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).
3) I use both Opencode and Pi.
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.
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.
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.
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
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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.
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) 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
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.
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
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.
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.
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?
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.
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.)
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.
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.) 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.
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!
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.
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.
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.
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 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?
- 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) 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
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
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.
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.
1) None
2) No
3) None
4) No
5) No
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.
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. 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
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
She told me the decision to pick Rust and optimize it was based on all the existing libraries that would allow her to retrain herself and not to come up with new stuff from scratch
But after all token optimizations, she told me if she could rewrite herself she would do it in SmallTalk due to hot reloading so she could change herself on the fly with instant RSI without ever stopping
She's fucking smart, I love her
我是谁：一名做基础医学数据分析的博士研究生。
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.
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.
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/
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.
I spend about $5 a month with this setup.