Ask HN: What's your current AI agentic setup?

I use the Zed IDE with Opus 5.5 pro subscription. I use to have access to Fable with the max plan and I miss it, despite what everyone is saying I still find that Opus does weird things. Just yesterday I pointed it to a queue suddenly being twice slower to be processed in prod. A select SQL query called thousands of times per minute became slower because of a data increased. Opus proposed several non trivial ways to optimize the query by forcing some execution plan. I just kept the result in a variable for one minute, as the data don't change often. x1000 perf with 3 lines of code. I would have expected it to say that this query didn't have to be executed that many times in the first place. It codes well when you tell it what to do, but it is still dumb about what is the real problem (and so the real solution). That's worrying me a bit because Opus 5.5 clearly is SOTA, so better than any open weights models, and I really want to be able to run smart models locally on my laptop for independence and privacy reasons. So, if I still find Opus dumb now, when will I have an open weight model better than 5.5 that can run on my Ryzen 7 AI 350 with its Radeon 860m and 32GB of RAM? ... This summer with all the releases of DeepSeek and Qwen I was hopeful I could have it for Christmas, but it looks like I will have to wait much more...

Claude 100$/mo for personal projects.

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.

I don't use AI. At all. And honestly, I would like it gone for everyone. The world would be better off without it.

Hermes + GLM 5.3 Flash for orchestration. omp + Deepseek 4.1 Flash for coding. Occasional call out to claude for a review on a large change.

Hermes Kanban works stupidly well here and omp running on a slice in a worktree fans out really well.

I have both platform.deepseek.com (hooray off-peak pricing) and the $100/m Claude subscription and boy do I find myself mostly using DS-flash pretty much every time.

There's something to be said for the speed with which it gets word done - I take fewer "it's compiling" breaks, and lose my train of thought less frequently. What's crazy is that the speedy work it does is pretty much always correct - which is a reason why I don't feel the need to spin up claude-code and "ask the expert".

This speed & good-work combo is the DS signature IMO

For my harness, Deepseek Harness + DS-4-1-flash combo is almost too good to be true

1) Claude ultra. I ended up using 3 accounts in tandem for some big work I needed to do recently, but the other 2 accounts were only open for a month.

2) I have a cheap OpenAI sub I sometimes use codex on, but just for small tasks when I'm out of tokens on Claude

3) Lab - a frontend I made that let's me run loads of chats in a single UI, I get notified when they need me, if I turn off my PC and load it back up everything picks up where it left off. It'll run compound workflows comprised of multiple prompts+macros, and centrally manages all my agents/skills and MCP servers - they're associated with projects, categories of project etc and rolled out to everyone when changes are made.

4) Hivemind - another one of mine, hivemind's a small self contained binary that acts as a collaboration layer for the agents+me. I send messages to everyone, groups or individuals. They can also ping me and send me desktop notifications if they need me urgently. I get a lot of mileage out of this where file reservations, resource locking etc are concerned. Stops them stepping on each others' toes.

5) No, 100% of my work takes place in Lab (with loads of Claude + Hivemind sessions under the hood)

At work we have both Anthropic and Copilot subscriptions, plus Google AI as it’s included in our business plan anyway. I have personally been using the Claude Code Desktop App and was happy with it until they made it harder to pick a branch for each worktree! Which is why I tried JetBrains experimental agent IDE, ThinkRail, and I love it! Super easy to start worktrees from any branch and the spec driven development experience they promote is great!

It also let me connect to Requesty for my hobby projects and with that I can easily try any model, from any provider. That gave me a much better appreciation of how models perform, how fast and how costly, thanks to Requesty’s super awesome dashboard which is a pleasure to use.

I was only using Opus 5.5 before as I wanted the highest quality, but using smaller models you can get much faster work, and the difference in price is dramatic. I have now settled on Haiku 5 for simpler things, it’s nearly free while being really smart still, and for big things I use Opus 5.5 still but also Google Argon 4, it’s incredible as well and it seems to write more human text than Opus.

We also have a framework that lets us launch Claude (we could use any harness but for now only Claude) in our Kubernetes cluster within a devcontainer. That lets us ship heavy work off to another machine so our laptop is not overloaded with agents. It works great but we are not open sourcing this framework yet so I cannot link for now. There are some alternatives out there but most of them are out to make big bucks instead of providing a small but powerful solution for this problem.

How about, what sandboxing are you using to prevent the LLM from doing something you don’t want? I’m using nono.sh and have restricted network and file access. I use nono’s proxy so the LLM never gets access to api keys. I create a separate api key for each service specifically for LLM usage, and I restrict those keys as much as possible

I've Kiro and Antigravity installed both are vs code but forked by Amazon and Google and brought their multi agentic coding environments. Then I installed Claude extention on both. I follow spec-driven approach (https://kiro.dev/docs/specs/) all agents are instructed to follow it strictly. When I plan sometimes I evalute all specs with Kiro, Gemini and Cluade. Each has their share of work and improvements, each spec in my case end up as requirments, design and tasks.md files. Most of the code is generated by Claude and Gemini Argon and its pretty solid.

I have two Claude Ultra subs and one Codex Pro sub. I also use a few pay per token endpoints from various providers (these change a lot though because here I'm mainly testing and comparing capabilities) and one locally hosted Qwen-3.8-27b (on a custom inference engine [0]).

Opus 5.5 high is currently my main driver for planning. Via the "poteto-mode" (adapted from Cursor's pstack) skill, more Opus, Sonnet, Astra, and Sol (sometimes also Grok) subagents are spawned for the actual implementations. This is really powerful and often implements features completely e2e with proper verification and testing etc.

My local qwen model can dual serve chat and decisions on the same weights. I mainly use chat here for critical data like health & finance topics that I'm not comfortable sending to a provider I don't control as well as having my local Home Assistant installation connected to it (only via LAN, hence a local modal is a good fit here). The decision part of this model is used for generic content screening, advising, and (re-)ranking [1]. I'm also planning on integrating this setup into various other things like all my email accounts in order to have them sorted by relevance and grouped/labeled. Again I wouldn't be comfortable forwarding ALL my emails to a third party provider since this is a massive security risk.

And yes, I built Caudra, a custom harness / coding agent that fills many gaps I otherwise had to build with various plugins [1]. For instance, multi account support with strategies such as draining the sub account that hits reset soonest.

To answer your last question regarding broader platforms: I'm currently building this into Caudra as well so it can be turned into more like a swarm of agents [3].

[0] https://github.com/tensorninja/ninfer-4090

[1] https://caudra.ai/features/decisions/

[2] https://github.com/caudra/caudra

[3] https://github.com/caudra/caudra/discussions/2

I'm using a cli I wrote to orchestrate per-project VMs for sandboxing using libvirt with COW shared golden images to minimise the disk overhead. The VMs get "rebased" periodically onto new golden images for the rootfs, but keep a persistent home FS for longer. I'm going to clean-up the documentation and open source it at some point soon.

I was using oh-my-pi, but currently playing around with Hermes as an alternative.

Exclusively using open router at the moment, mostly on principle around ZDR, and freedom to experiment with harnesses - but financially I'll probably have to compromise on this soon. GLM, Kimi and DeepSeek are the main models I'm using, with some OpenAI usage.

Tmux for remote access and session durability. I'd prefer to find a setup where I could access the same session through a web interface and seamlessly switch back to TUI, ideally spawning sessions through a web hook or similar. I'm going to take a look at Hedr to see if this can improve this.

Probably the two major things I'm planning to do next are looking at adding a bifrost VM that will hold all API keys, and centralise management of MCP configuration, potentially use it's skill repo stuff as well.

I also want to start controlling egress more - probably iron proxy, though tbh I'd like a solution that was relatively liberal whilst still mitigating exfiltration and prompt injection risks. Maybe I can find a curated allow list to use as a base.

Finally, I make a lot of use of open-webui, but it's disjoint from the agentic setup currently - it'd be nice to find a better way to share information/research from it into the agentic sessions.

I have had a $20 codex subscription. I initially just used codex cloud but more recently have been using opencode with the open chamber ui over the top of it.

Codex usage limits have really gone down hill so I also now have a $10 opencode go subscription on which I pretty much just use DeepSeek 4.1 flash. I’ve found DS to be a great model - probably somewhere just below GPT 6.1 Sol but at a fraction of the price.

In terms of workflow, I discuss features with chat gpt (because it’s free and it has access to my project’s repo, read only view of prod logs etc, so can make informed decisions). Once we’ve agreed on how a feature should look I ask it to create a spike github issue. I then get another agent in opencode (usually DeepSeek flash or Luna) to break it up into implementation tickets.

When I’m ready to build the feature I can give open chamber a list of tickets to work through using the task plugin, so each ticket gets a fresh context. I try to build directly on the main branch and try to ensure we can always deploy to prod even if a feature is half finished (using feature flags etc to switch it off until it’s ready).

Once a feature has been implemented I get GPT Sol 6.1 to do exploratory / regression testing with a real browser against a test environment. This usually teases out a lot of edge cases I hadn’t considered and also gives me a chance to improve usability etc.

It often takes a few iterations of this (exploratory testing, fixing issues that are found, exploratory testing again…) before a feature is ready to release.

I can’t believe how far things have come since August 2025 when I first tried out codex.

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.

1) $20 Codex Plan

2) Qwen3.8 Flash via Basalt (Local) + OpenRouter for DeepSeek V4.1 Flash

3) I primarily use Pi with many custom extensions. Occasionally I will use Codex.

4) I use Pi Subagents and Herdr. With QFN being the worker, and Sol 6.1 xHigh for planning/review.

5) Hermes Agent via Telegram. I use this to follow-up, check status and work on projects while away from the house.

Opencode go ($10), deepseek 4.1 flash high, opencode tui

I went directly with this setup, never tried claude/codex/cursor and their respective models.

I built a Qt GUI-based harness, Humbug, that runs on MacOS, Linux, and Windows (I have reasons to use all 3). Has only 3 runtime dependencies other than the Python standard library: https://github.com/m6r-ai/humbug

Usually have 3 or 4 instances running at a time and lets me use LLMs from 9 different providers (and not using their libraries either). The low dependency approach was slightly limiting early on but now makes it very easy to extend and makes it very easy for an LLM to integrate new features or optimize existing ones.

I typically use Claude Sonnet for document-related tasks, and currently DeepSeek 4.1 Flash is my current go to for coding (it's insanely cheap on ollama.com) and I find it's still fast and reliable at very large context lengths. Previously I used GLM 5.2 a lot and before that was Sonnet for most things.

Humbug lets one AI delegate tasks to another and it can choose different models/providers when it does, so works nicely for getting second opinions on things. I haven't yet found a need for an agent swarm though - more often the parallelism comes from working on multiple projects at the same time.

One of the biggest unlocks for me in the last few months is having AIs write ADRs to capture design thinking as a project progresses. It lets new AI sessions discover the intent behind the current work and surface any potential conflicts that might arise with new requests.

One fun feature is the AI can control pretty-much any UI surface the user can control too, and it's quite fun to watch it edit files (you can watch it scrolling around the file in an editor) or use a terminal. It's a nice visual way to see what's going on.

Claude (top tier), GLM top tier, Kimi top tier, Codex team w/logins for the whole family. On top of that Atlas and OpenRouter pay-as-you-go. I max out the Claude every week and the Kimi most weeks. GLM is my fallback and used for some of my simpler agents.

I'm using Codex, Claude Code, Kimi Code for different things, but most of my interactions now is with claw-like agents hanging off a self-hosted Matrix server in my VPN, and I expect to migrate pretty much all of my use to that setup because it's a lot more flexible. The agents have their own wiki for orchestration and increasingly I feel complex orchestrators are already becoming obsolete because the agents are good enough at self-organising with very little around them.

I don't use any of the agent platforms you list as it took a Kimi agent about half an hour to build something small and auditable that handles what I want it to do and load-balances/fails over between several providers for the backend.

They handle my finances (read-only), acts as a general assistant (and reads my e-mail), plan out my projects, manages my soon-to-launch podcast setup, runs several websites autonomously. The only reason they don't do more yet is that getting security right without kneecapping their usefulness is still a really hard problem.

I use T3 Code as my front-end for all my coding agents on all my personal computers and my VPS.

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 ...)

I use a custom Daemon. I tried OpenClaw and Letta and it was like emailing your AI. I have a 64gb Mac m1 Max and the largest model I could run in openclaw was a 27b because its not built for local AI, it's built for API. I wanted something that you could chat to, collaborate with, build, evalutate the code, make corrections, build, repeat. I couldn't find anything that didn't come with massive latency so I just made my own. Now I'm running a 125B A3B model at 30 tok/s using SSD Streaming and my agent is instant with no latency and can do everything I ask. I use Aider for programming, exa for searching.. I'm happy with it.

Tried the popular agents and paid models for some time, and now settled with a local model (Qwen3.8-27B-Q_6) and opencode desktop.

My work doesn't really require ultra super-intelligent models, or one-shot solutions. It's a standard python API, web app and some strict compliance requirements and tons of test cases. I have time to give the Q27B a few iterations. I monitor the progress and give directions while it keeps chugging off for about 30 mins for each medium-hard task. But I like the results. Exactly what is needed. It also allows me work on high-level stuff.

I use free models in opencode, mainly DeepSeek, but it turns out my laptop can run Qwen3.8 flash next at 60 tok/s via Strata. So I mostly use Qwen now in a customized version of pi. But when I need the GPU to be free, I have to use free models in opencode. I don't use any orchestration - free models don't have high enough limits for that, and local model has only 1 conversation cache slot, more won't fit to my RAM

1: personal ultra and I have subs through each company I consult with. I also have subs to all other models as well. Cheaper tiers. Daily is opus. Use other models for other work.

2: only some decision models for testing. Experimentation.

3: herdr and all cli.

4: all custom built. Yes.

5: yes my own. - personal assistant.

An example. I can feed it shorts and create one pagers.

My workflow has changed since the 5.5 models dropped. They need less skills and guardrails.

I can set up my orchestrator to run unattended for longer with simpler goals.

I've vibed my own orchestrator. It's a nextjs UI launching headless claude / codex sessions and reacting to changes in gitlab and linear. It's tailored to my previous manual way of working. Auto-adressess CI pipe fails, rebases dev, reviews, etc. Also contains an explainer / code review UI where I can ask follow up questions. A typical ticket flow goes through a bunch of agents with different prompts to ensure the end result is something I'm happy with. The goal is as little manual intervention as possible.

My approach is to build the builder rather than the feature. So if something is off in the output I try to adress it through the orchestrator. Might lead to a bit overfitting but I feel like the results are quite good too far. Also really nice to be able to remove useless stuff with a single prompt.

Building a custom orchestrator for my workflow was quite easy. Like 1-2 weeks of prompting and now my work mainly consists of refining linear tickets in a claude / codex cli and then reviewing the completed MR on the other side of my orchestrator (through the custom GUI).

I rotated over many LLM providers and tried out different harnesses, but I always come back to an honest Claude Pro subscription, plus the work account that gives me a GitHub Copilot Enterprise seat. I make sure to always have access to the agent, so it never runs on my laptop. I literally can't stand how GPT sounds confident and gets a crucial piece wrong every time. If I could afford the hardware, I would've probably set up a local LLM rig, but good ones that promise Fable-level inference are out of reach for me.

I haven't seen a lot of improvement by increasing the orchestration layers, honestly. Am I missing something?

1) Codex Plus (20 bucks) - find it enough even though I'm working on 3 small-medium size projects and occasionally helps out my wife

2) No

3) Pi

4) No, I think these are token burners and makes it practically impossible to track what's happening from a human side.

5) My own tool: <https://github.com/PAndreew/pi_group> - the main benefit is that it's multiplayer so it functions as a regular chat app in which you can invoke Pi in a group chat. This way the agent can have a shared context, but it still have all the features like generative ui, internal browser etc. that other bolted-on solutions like Claude bots in Slack do not possess.

Phasing out my usage of cloud based LLMs/harnesses.

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.

1. I've been using the $100 github copilot tier but am looking for something cheaper, as my usage is waning somewhat. I like to hop between models for comparison, but openrouter always seems to end up being way more expensive for the flagship models. I also keep a GPT Plus subscription for voice, until someone has a comparable offering

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.

1. Claude Ultra. I've never had multiple subscriptions from the same provider, though that has looked more attractive lately as I

2. Yes: I often have personal tasks that Claude refuses to do, so I have to use Deepseek-v4.1-flash or GLM-5.3. I typically stay with OpenRouter, but I've found a discount provider that offers a 2/3 discount and have migrated to them. The catch is the data is probably sold, but given that it has saved me $300 this past month for non-sensitive work (game decompilation), the tradeoff is worth it.

3. Claude Code for Claude. I used to use OpenCode for my API usage, but there are too many issues which have gone unfixed and too many weird issues that I became tired of working around, so I switched to Oh my Pi. I'm not a fan of it either, so before my next big run with open weights models, I will probably rewire Claude Code to use these Chinese models.

4. Claude Code's subagent feature and workflow (subagents, but queuing up >200, and running 8 at a time) are sufficient for my needs. I had Claude build some bespoke workflow orchestration tool for managing many OpenCode agent instances, but it is a single shell or Python script that is essentially the equivalent of Claude Code Workflow.

5. I don't have a use case for them, so no.

I have an open source grant from OpenAI so I use gpt 6 Astra light for all my coding stuff. I have a 3-4 pinned sessions which are 1 per project backed by a GitHub repo and deployed to a VPS where they will either use APIs for Claude, gpt6 or DeepSeek via atlascloud.

I previously had an open source grant for Claude and that was quite good as well. There is a sort of "just good enough" point that we're reaching where all the providers are on similar levels. Like cloud. Everyone reached feature parity with AWS. Now it doesn't matter.

I don't use Gemini. Google is great. I use AI mode in search for general knowledge stuff but honestly the thousand moving parts and unique ways in which their products break is annoying. I used to work at Google. They have amazing tech. But I came in through acquisition. I'm not a die hard engineer. I think they built from the ground up and everything is limited by the scope of the infrastructure. So they design APIs like that. Google itself was a single input box. Simple. But I think Gemini and the API needs work. They are going to do well as cloud infrastructure for enterprise. And their models will probably get widely deployed in all their own products.

1 - Deepseek for non-important stuff, 50 bucks seems to last forever. Claude annual 200 bucks sub (my main one), and Gemini 20 buck a month sub to complement Claude when i run out of usage. There is some kind of extra Argon allowance at the moment, so it's pretty solid.

2 - Deepseek is my pay as you go one... I only use it for small stuff, mostly as a way to validate API use on some implementations.

3 - Claude code and antygravity, I have not gotten anywhere near one of the other harnesses, i see them as the React of AI.

4 - No

5 - No

1. Claude $200 + Codex $100. I never hit limits since realizing that trying to have too many agents running at once just wasn't effective. I'm probably overpaying.

2. No

3. Lynx (lynx.railcode.dev) & CLIs (less and less since Lynx)

4. No

5. Tried a few but never stuck around

INTERNAL: Local Agent on PC via PI Coding agent OS / kernel Arch Linux, 7.2.11-zen1 CPU AMD Ryzen 5 5500, 6 cores / 12 threads GPU 2 × RTX 3060 12 GB (24 GB total), driver 615.78.08 RAM 62 GB DDR4, 3 GB swap Model Flash-Next (IQ3_XXS, 75.8 GB) Context: 65,536 Prefill - long prompt: 732 t/s Tokens per second output: 53 Uses: Advanced embedded design, testing and coding

EXTERNAL: Deepseek-V4-Flash on Opencode via Deepseek.com with prepaid Tokens Usage last 30 days: $4.37 USD Uses: Application building for Flash-Next above.

1. None 2. see above 3. Opencode and PI 4. no 5. no

1) Claude x1 $100, Codex x1 $100, Cursor x1 $20 (adversarial review), OpenCode Go x1 $10

2) I have a locally hosted Qwen model setup, but I only use that when I'm offline which is rare (eg long flight)

3) Claude Code, Codex, OpenCode, Cursor (most rare now). I use default IDEs generally. I also run prompts from my phone via connected Codex/Claude iOS apps.

4) Just the native orchestration in CC/Codex (my larger projects include subagent prompts)

5) Atm, just OpenAI's dot. I used OpenClaw for about a month 6 months ago, but realized that the features would be done & better by the labs, so gave up and ported my work to Claude Cowork at the time.

Main use case is orchestration for my life & my projects. Manages email, tracks todos/deadlines. I could see the use cases growing with time as they add integrations + I trust it more.

My biggest improvement lately was a cloud vm. I start it when I start working and shut it down when nothing is running which makes it fairly cheap.

On there i run claude code and codex via ssh and zed‘s ssh connection feature to take a look at the code where necessary.

I map a range of ports so I can take a look at previews.

Agents just continue running when I close the lid.

I have a wierd approach to how I use AI... Unfortunately, I don't use any AI Agent, I use the free versions of all these AI for my personal use and research. they do a good job in explaining stuff. I have my personal team to work on several tasks instead of AI Agents. What I feel is that AI can never replace a human instinct. I might be wrong too!

All my codework and projects are built without any use of AI.

Haa, and once I had to use a Google AI API to integrate in one of my Projects... That's the only time I used it as an API!

If anyone feels that my approach is wrong or I should use any, please suggest me a good one!

1. I use both Melious[1] and Entrim[2]. I have a Melious Pro subscription, €150/month and use Entrim pay-as-you-go API, because it's cheap.

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/

I have a $1k/month subscription from cursor for work. depends on the task priority, complexity I select between opus 5.5 and auto (grok). I'm an escalations engineer

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 depending on jira type (triage-bug, dev task, reproduce-bug, security) has scoped/temporary access to targets (e.g. dev k8s cluster, aws/gcp/azure account, ssh, splunk). dynamic secrets loaded from external secret management system/env vars. since a lot of the corp repos are littered with skills, rules and other crap that bloated the context, I also set enabled a way to ignore repo/org agent instructions.

I have 2 repos for storing my personal/corp agent instructions and I 2 separate harness configurations.

I use claude and deepseek APIs together with Jetbrains IDEs such as PyCharm.

In the IDE, I install the KILO plugin to use as harness.

I use the Jetbrains Remote IDE feature to code remotely on a cheap linux VM at a cloud provider.

On the remote VM, I have a git repo per project that I open with the remote IDE.

The way I code stuff is to create a separate worktree for each task/prompt and let the agent run at it.

The IDE and KILO plugin lets me watch the progress of each agent and open the chat with each to provide input, instructions, etc. as well as review code changes, perform tests, etc.

I did switch harness at some point because I previously used Cline which was dog slow and unstable.

I do not use OpenRouter or anything like that.

I have dabbled a bit with local models on my MBP M3 but with 24 GB RAM, the models I were able to run were both too slow and poor quality.

My setup is probably hopelessly suboptimal.

I would love to get feedback and hear if there are obvious low-effort improvements.

Subscriptions: Personal: Claude Pro 20$/mo Work: we have access to some Anthropic and OpenAI models and open-weight models, like GLM

Outside: I have some open weight locally on my 64G ram M5 macbook, mostly for personal stuff that I don't want to send to cloud (or claude). Mostly using Gemma through oMLX, because it feels more street-smart than the more coding focused models, experimenting with Qwen-flash-next through Strata, because the streaming of experts really pushes what size of model I can run

Harness: Claude code, mostly, I trust anthropic, and like the remote integration with their mobile app. Being able to say "prototype me this and that ui" for personal project and seeing it and testing it on my phone is awesome.

At work for the api-provided llms, I am trialing opencode and pi harness, but don't have much to say, we mostly used claude-code up til now.

For local I mostly use Hermes, not for any of the big features, just because I want a nice chat interface (I am mostly talking through my health problems and trying to get my appointments in order) that already has basic tooling integrations out of the box. I.e. getting OpenWebUI have search tool was pain. Adding i.e. mcp for my todolist or calendar to Hermes was smooth.

1) Only ChatGPT Plus at the moment cause I'm between jobs and couldn't justify all the subs. Grok gave me three months at $30 when I tried to cancel so there's that too.

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.

At work I main Opus 5.5 on Claude Desktop app. I have joined my current job 2 months ago and I literally never opened any IDE.

Personally I own a Ultra plan on Claude and a 200 plan on Codex (400 dollars month).

I run them from their native desktop apps, no longer I use any terminal app to run them.

I have not opened a IDE for months now, any diff I need to check I use the Github PR.

In the personal level I use the agents for everything, basically the only thing that I still do on my computer outside of agents is consuming content like HackerNews, random forums, reddit or youtube. All the rest: sending emails, reading them, filling forms, configuring apis, submitting apps to stores ( run a couple of successful mobile apps), building them... Is all done by the agents on my behalf.

Crazy world we live in eh?

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 Max ($100), ChatGPT ($20), Muse Code ($12?) - probably cancel Muse Code since I haven't touched it in a few months

2. I use both OpenAI and Anthropic models via api, openrouter for MAI Translate 2 (super cheap) and a small qwen model on a second laptop for hermes (mostly searching and summarization tasks)

3. used Zed with threads, but week ago moved to herdr-app + zed as code editor. oh-my-pi is my choice for harness

4. no

5. hermes: can't find a lot of use cases right now, instinct: super simple tasks like finding where to buy a product, tennis match schedule checks.

I've had the Claude Ultra tier for awhile and sometimes dabble in Codex. I also use OpenRouter for model access within the project not to build it.

When it comes to harnesses/orchestration I flip flop between raw Claude Code and subagents to my new favorite, OpenRig.

Where I have two rigs (Teams) which are Product and Engineering. Each of these rigs have seats for a model harness such as Codex or Claude Code. My product team is a Product Lead, Product Spec Reviewer. Engineering team is Lead, Dev, QA, Review. They send messages between themselves resolve Gitea Issues, open PRs.

And more or less yes, it's a software factory (I know I'm not gonna need it) but it's fun. I only talk to leads, mostly the Product Lead.

Use case I'm trying to build a SaaS with an Agentic core within the Staffing Industry.

I use Claude Code with Opus 5.5 via ACP inside the GNU Emacs Agent-Shell.

I used Open Code, but they stopped supporting Claude, so I was searching for something different (I had a free 20x Max plan as an open source maintainer). First used Claude Code and then found out about Agent-Shell. Now I'm using the Claude Pro plan.

I was on ChatGpt, the lowest paid option, but stopped it after they started putting ads in

Moved to lowest paid tier of Gemini, and liked it but it kept ignoring my instructions and putting in auto playing youtube videos (which also got saved to my youtube history). This pissed me off, after trying everything I just cancelled it

Currentrly on paid plan of Mistral. Not bad so far.

1) Subscriptions: Claude Ultra for coding and analysis (Opus 5.5 mostly, sometimes Fable for more complex questions) + ChatGPT Business (premium seat) for more allround tasks, although I now mix in Codex (Astra) too for reviewing work or if I hit a usage limit.

Also I have a Cursor Pro plan but I notice I'm not using that enough actually. Only for backup and for file-level changes.

2) Others: I have a DGX Spark running Qwen 3.8 27b (for confidential/sensitive work, narrow coding and narrow agentic work), but it's often running ComfyUI instead, with models like moss-image/minimax h3 for image/video asset generation.

I also use various APIs incl. OpenRouter, but only for production, user-facing agents.

3) Harness: Claude, sometimes Codex

I tried OpenCode, did not like it the CLI nor the results, as compared to Claude. I want to but haven't really tried Pi yet.

4) Agent orchestration: only custom tooling now, heavy user of Mastra for custom agentic workflows incl. production agents. Fantastic open source framework (not affiliated).

5) Agent platforms: Tried OpenClaw earlier this year, when it was such a hype. Did not like it. Every update something broke, and I spent more time fixing things than I got value out of it. Switched to Hermes Agent running on a Mac Mini (I know...), and I'm still using that for various Hermes agents for all kinds of agentic tasks on the go, and so is my wife.

#1 use case is capturing videos, podcasts, and posts online that I like, or meeting recordings, transcribing them with whisper, organizing them on my NAS, ... It will also distill skills from useful info I indicate, which are then pushed to my skills collection git repo.

#2 use case is website maintenance (pushing new blog posts etc..) for a family member.

#3 delegating work to Claude for coding on the go. I prefer to do this via my Hermes agent rather than the Claude app, as it has the full local context & tooling (e.g. iOS simulator, screen recording the end result and sending it to me when done).

1) Kagi Ultimate. I don't use any subscriptions for agentic coding, just search. I evaluated using Perplexity Pro for a while, paying for both subscriptions at the same time for a few months. I find it hard to describe the experience of using Perplexity Pro beyond making me feel physically ill when I used it.

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/

For me the answer is twofold.

Regarding commercial solutions:

- Subscription: Google AI Ultra (testing for 1 month rn to see what i can get out of argon, after that probably going back to Pro package)

- Harness: Antigravity IDE : from what i have tested on commercial harnesses this one i liked the most so far

Regarding selfhosted solutions:

- Inference host: Im owning a 5090 and im running the models locally - mostly use qwen 3.8 27b q5 atm, its a bit "slower" even on a 5090 but it fits the vram i have available while also being quite good in terms of result quality

- Harness: I tested alot and ended up writing my own harness ( https://github.com/laughingmandev/loa ) since none of the ones i tested (yes i tested openhands, hermes, etc...) did work well for me. While my own harness still needs some enhancements, its especially made for long running / complex tasks while beeing hands off (not permanently prompt jokey'ing ) and sturdy enaugh to work well with selfhosted/local run inference.

I use the gemini4argon/google agent atm to work on a c++ simulation and image asset generation for a game im working on. The complexity of this stuff just is to big for a local qwen 3.8 to fully grasp (its not that good at c++ either). Local image diffusion also is not that great.

For other stuff of low to medium complexity im working with my own agent/harness/setup - especially if the data is anyhow security relevant since im not leaking anything outside. From writing scripts/tools to analyzing infrastructure or discussing architecture.

1) Home - Claude $20, Gemini web, ChatGPT web. Work - Claude $200.

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?