I've been increasingly interested in language-oriented programming and denotational design. So i get claude to create a domain specific language in Racket modelling the software i'm trying to build, we create nouns and verbs whose meaning fits the behaviour i'm going for, then when we find bugs or notice we need more exceptional (less-elegant) one-off behaviour to tackle edge-cases, we iterate on the language in such a manner that it these are tackled emergently with preferably less concepts, more cohersion and composition. It's somewhat similar to how memory safety is handled at compile time in Rust but for business logic.

- Wrapper : Orca

- Harness : oh-my-pie

- Models : OpenAI $20 sub (mostly using Sol/Luna) + Deepseek + JEV

- Skills : Mostly Osmani's agent skills, ub-mode, agency skills for personas + custom stuff

I'm kinda reworking everything as the moment, I'm having issues with other people's workflows (whether it is Pokock, Osmani or Uncle Bob) even though there are bit I like and I'm still looking at how to balance quotas, thinking levels, velocity.

$200/ea plans on Claude and Codex, plus OpenCode Zen for experimenting with other models, plus Qwen3.8-28b locally. (I test-drove DS4 Flash locally in a 128GiB MBP for a while, but the tokens per second were too slow to be useful for more than being a toy.) At my prior anchor client I had an additional max20 plan; at my current anchor client they have a teams plan.

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.

1. I'm personally paying for Chatgpt Plus, single account. I mostly use it for personal stuff, and occasional coding - one-off scripts I do from the chat interface, and I used Codex for a more complex project.

2. I sometimes have questions I don't want to associate with my main account, I use duck.ai or chatgpt.com in a private tab. I also dabbled with self-hosting, but it's mostly curiosity, testing abliterated models, testing linux-amd integration etc.

3. Sticking to the defaults. My dayjob pays for Copilot, which means a Copilot plugin in IntelliJ

4. I haven't even looked into agent orchestration and swarms.

5. Not using agent platforms either.

1) Claude ($100) and ChatGPT ($20)

2) No.

3) I mainly use Claude as my main, Pi (with ChatGPT) for any automations. I manage them all with herdr. I cd into a path, kick off a claude/codex/pi session, then kill the session and manage it from anywhere with iceghost. (https://github.com/sharkjets/iceghost)

4) Negative.

5) I tried openclaw but found it a waste of my already scarce tokens. :D I build my own runners when I need a loop or cron-based automation.

I use a tool I made that lets me orchestrate lots of AI agents (claude/codex/gemini) both on my laptop and on a k8s cluster. I set them up to run on various triggers and access them from my phone/laptop: https://github.com/jonwiggins/optio

OpenAI $100 account, Claude $200 account and a Linux desktop with 2 RTX 3090s and 128gb ram. I'm generally working on about 2 projects at a time, sometimes more on the weekends.

Claude code CLI, rotated with codex CLI (monkey patched to be able to message with Claude sessions over the Unix socket thingies).

Local ollama server running qwen and a bunch of other models.

I'm having an absolute blast!

My projects accumulate here: joemattie.com

I use xAI and OpenAI subscriptions, switching between them, even mid session, using my Lunar harness: https://github.com/gszr/lunar. This is a very productive setup for me. As it also supports API keys, I throw in other models in the mix when I want to play around. I have not incorporated an orchestrator in my workflow, but I can see the appeal.

I am using mainly claude code on a Pro subscription.

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.

I'm currently on Raven as a sort of "meta harness". The main chat is with the orchestrator, which delegates all work to other harnesses. I just use different seat-based plans. Mostly the latest Sol with my corp chatgpt account.

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.