Launched this week
KarmaBox
Run your own Claude Code in your pocket.
873 followers
Run your own Claude Code in your pocket.
873 followers
Run hundreds of AI agents from your phone. Turn your devices into a private compute pool, route every task to the best AI, and use Claude, Codex, Gemini and more — no infra, no lock-in.
Running AI agents from your phone sounds powerful… but I wonder how practical that is for heavier workloads.
KarmaBox
@ritu21 Totally fair — the heavy work doesn’t run on your phone.
The phone’s just the control layer. The actual workloads run on your laptop, servers, or whatever devices you connect.
So it scales with your setup, not your phone 👍
KarmaBox
@ritu21 The phone acts as your control console — the heavy lifting happens on your own compute devices or in the cloud. We also offer desktop-grade hardware for those who need local execution and maximum data security.
I didn’t realize how much time I was losing waiting for one step to finish before starting the next.
KarmaBox
@shaowei1 Exactly — that hidden waiting time adds up more than people expect.
Once things run in parallel, you stop thinking in “steps” and start thinking in outcomes.
Curious what kind of workflows you felt this the most in?
KarmaBox
@shaowei1 That's the hidden cost of sequential AI — KarmaBox reclaims all that lost time by running everything in parallel.
KarmaBox
@al_sims Glad you like it 🙌
Right now it’s iPhone first, but Android is definitely on the roadmap — we’ll open it up soon 👍
Triforce Todos
This is a genuinely interesting concept.
Quick question, BTW, how does KarmaBox handle task routing decisions? Is it rule-based, or does something smarter decide which model gets which job?
KarmaBox
@abod_rehman Great question — this is actually a core part of how KarmaBox works.
It’s not just rule-based. We use a routing layer that looks at the task context and decides which model, agent, and even which device should handle each part.
Think of it less like fixed rules, and more like a system that’s continuously choosing the best path for the job.
Still evolving, of course — would love to hear how you’re currently handling routing on your side 👀
KarmaBox
@abod_rehman Great question! 👍
KarmaBox uses a hybrid routing approach that combines rules with intelligent decision-making:
How it works:
1. Intent Analysis
We first parse your request to identify the task type (writing, coding, research, automation, etc.)
2. Smart Model Selection
Based on the task, we route to the most suitable model:
Code tasks → specialized coding models
Creative writing → creative-focused models
Complex reasoning → more capable models
3. Parallel Orchestration
When a task has multiple subtasks, we intelligently split them across models that can work simultaneously
4. Adaptive Learning
The system learns from your preferences over time, making routing more personalized
Under the hood:
It's a mix of rule-based heuristics (for speed and predictability) and ML-based routing (for complex decisions). The goal is to give you the right tool for each job without you having to think about it.
Readdy
I like that I can focus on what I’m trying to achieve, instead of how to get there step by step.
KarmaBox
@wenjun_shi That’s exactly the shift we’re going for 🙌
KarmaBox
@wenjun_shi Less about figuring out every step, more about setting the goal and letting the system handle the rest.
KarmaBox
@wenjun_shi Thanks 🙏 — that's actually the entire design thesis in one sentence.
Most AI tools still make you carry the how: pick the right model, write the right prompt, chain the right tools, manage the context, remember what you said last time. The load just shifts from doing the
work to operating the AI.
KarmaBox
@wenjun_shi Karma's bet is that the how should dissolve — into routing, memory, skills, runtime selection — so what's left in your head is the goal. You say "prep me for the 3pm meeting" and the avatar figures out
which docs to pull, which model to use, which format you prefer (because it's seen you accept that format before).
The compounding part: as your avatar matures (memory + L1 → L5), the what you can specify keeps getting bigger.
- Day 1 you describe steps.
- Month 3 you describe outcomes.
- Month 6 you describe intent.
That arc is the productivity unlock — and you spotted it before we said it 🙂
I’m not really interacting with individual AIs anymore -- it feels more like directing a workflow.
KarmaBox
@jocky That’s exactly the shift we’re aiming for.
Less about talking to individual AIs, more about setting direction and letting the system carry things forward.
KarmaBox
@jocky Thanks for the support!
That's exactly the vision — you become Tony Stark, and KarmaBox becomes your JARVIS.
KarmaBox
@jocky Less about figuring out every step, more about setting the goal and letting the system handle the rest.
Brila
Which models are best for which tasks in your opinion? What I see recently is that Opus is leading practically any category on Arena.AI. Given they offer their subscription at a huge discount, compare it to tokens via API, the rational choice is Opus for all.
KarmaBox
@visualpharm Great question — but I’d push back on “Opus for everything.”
Arena ≠ real workloads. It measures chat quality, but real usage involves latency, agent loops, tool calls, long context, etc.
A few quick points:
Latency matters — slower models hurt UX in interactive flows
Different strengths — coding, reasoning, classification, multimodal all favor different models
Blended routing wins — fast model for most tasks, stronger model when needed
In practice, one model rarely wins everything.
That’s why KarmaBox is model-agnostic with routing built in — so each task gets the right model automatically.
Curious how you’re choosing models in your setup today?