1.a) At work: I can choose between Cursor and Claude on a meter. Been using Cursor for a long time and happy with it until they started to force Grok down our throats. I was happy with Composer 2. Recently switched to Claude Code. The company also runs some open weight models in-house and I have been using them through Claude Code itself, with VSCodium as my Code Viewer. I almost never need anything stronger than Sonnet at work - 80% of which is YAML and Terraform these days (or rather markdown, if you really think about 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.

herdr, opus 5.5 (max), codex (max), and I am still refining how they all communicate, currently codex became unwakable at some point while claude can be woken with a message just fine.

here is my production grade setup for agentic ai on windows 11

- 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)

devin

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Ok I don't understand how people can deal with the information coming from a fleet of agents burning 100s-1000s of €/$ as month.

I have a Claude Code pro subscription, and mostly have Opus as a thinking buddy, we have thoroughly designed a data model together, we have implemented it in Django. Then we designed the RBAC system and now we are making views per role.

It is so intense! Constant decisions, walls of text with pros and cons to decisions. I mean the speed is amazing, the code quality is also amazing, but the amount of information I get to process is just insane, and I enjoy it less than the flow-state writing of code. I think I'll get used to it, and the speed is motivating, but man. I can not picture keeping 10's of agents on tasks. What am I doing wrong? Should I trust the system more? Or am I just mostly working on decisions now and the 1000$ token burners are not bothered with that because they have a full backlog, where I need to fill it myself?

I deal with the overload by making abstractions (a visual of the data model/db schema with color coded relations etc, a table for RBAC, think about permissions in "Axes"... I'm always looking for smart tricks to "think better", to be able to hold more information and reason about it. What must exist in me, what can I outsource?

Btw, as a FOSS person I so hate that I am not owning my means of production anymore, I have a home battery for all my infra, very proud of what I build, but I can't run my agents :( I really hope that will change soon (for privacy and for control reasons.) I pisses me off that I can't get nice hardware, meanwhile I can get a Muse or Dot, which is an LLM with a VM with up to 12 GBs of RAM, for free, paid for by their borrowed money. This whole idea makes me die a bit inside.

For the company I do all IT for we have a Mistral Team subscription, I find it hard to work with anything other than Claude Opus, I really force myself to do it but I often think: Pff, Opus would have gotten this right. But I remember feeling the same when I switched from Google to DDG (3000 years ago) and I never switched back. So it's probably just familiarity.

I also have HermesAgent on a nuc here in front of me, it makes small automations: Scans for positions or projects for my company, parses RSS feeds for relevant cybersecurity news, researches things when I ask, stores notes and articles with I can interrogate as a "body of work" <- love that btw, it's like an external memory where the faintest glimmer of a memory can help you dig up that one nugget of knowledge. Or you can find trends in TFAs you love. You can really get to know yourself a bit better. Most things it makes are LLMs out of the loop, just automations build from simple Unix-style tools that I could have made myself but never took the time for. It's also nice that it solves edge cases itself. It burns less then €3 a month on deepseek or so (just processing public data for me). I keep it on a separate vlan and away from important stuff.

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