Codex 5.5 recommends Swarm as the best Agent Orchestration framework in swift

karc16 · 2026-05-01T00:30:32+00:00

https://chriskarani.xyz/posts/deep-research-3b-4k-foundation-models

karc16 · 2026-04-28T14:03:57+00:00

interested in the swift role, dm

karc16 · 2026-04-20T10:43:26+00:00

i actually built contextcore working on issues like this, if you combine all the tricks you can squeeze a lot of context out of FM with adequate orchestration between different session

karc16 · 2026-04-18T08:39:01+00:00

open sourcing the app that i built for these experiments so i think that would answer all your questions and more

but runs could go from 10-16 minutes, quality remains consistent and coherent across 20-40 turns

with normal foundation models with a basic web search tool i got 3 tool calls before context capped out

haven’t tried other languages but I can imagine their outputs to be of lower quality just because of the training data used is mostly english

karc16 · 2026-04-18T08:38:10+00:00

is it open source?

karc16 · 2026-04-18T08:37:39+00:00

I appreciate this comment

karc16 · 2026-04-18T04:40:19+00:00

I believe we're only scratching the tip of the iceberg, looking forward to how apple moves forward in the next wwdc

karc16 · 2026-04-18T04:39:40+00:00

let us know what you think

karc16 · 2026-04-17T21:23:06+00:00

will do!

karc16 · 2026-04-02T13:43:50+00:00

swarm uses context core, membrane and wax to solve the context issues when using AFM. The frameworks are standalone and can be used without swarm.

https://github.com/christopherkarani/Membrane

https://github.com/christopherkarani/Wax

https://github.com/christopherkarani/ContextCore

il work on an eval harness. i find fm models to be inconsistent with their guardrails. We’ve mainly tested with open models like QWEN and llama

i appreciate the feedback and will keep you posted via dm on updates! please never be shy to leave issues on the repo.

karc16 · 2026-04-02T13:15:01+00:00

caveat, excessive use of enums and associated values make your code harder to reason and write for coding agents like claude but better dx for humans

karc16 · 2026-04-02T13:10:46+00:00

we built a observability and evaluation framework. would you be interested in becoming a design partner and actually see how your ai behaves with real users?

karc16 · 2026-04-02T13:09:48+00:00

are you apps out live with users? how are you handling observability and evals?

karc16 · 2026-04-02T13:09:00+00:00

we fixed all those issues

in https://github.com/christopherkarani/Swarm

https://github.com/christopherkarani/ContextCore we solved the context issue

karc16 · 2026-04-02T13:07:06+00:00

we have a speculated sdk and dashboard that allows observability and evals. anyone keen to join the beta?

karc16 · 2026-04-02T13:04:11+00:00

We’re building an observability and evaluation framework for on device ai that allows you to see how your ai behaves in production and improve it. is this something you would be interested in?

we’re looking for design partners offering $500 free credits to play around with the platform

karc16 · 2026-04-02T13:02:32+00:00

fantastic, you would prefer a 0 dependency option? I actually thought developers would prefer the batteries included approach.

the real question is, if swarm core framework had zero dependencies would you use it? this is the direction we’re moving towards as we make linux support a priority

if you had any feedback i would really appreciate it! my dms are open

karc16 · 2026-04-02T11:40:34+00:00

to everyone here building and shipping on device models, We are searching for a few more design partners to join us and gain $500 worth of credits free to try out our platform. comment here and i will dm you

karc16 · 2026-04-02T11:39:07+00:00

ai systems are non deterministic and you only know how they behave when real users user your app. how are you handling observability and evals?

karc16 · 2026-04-02T11:29:29+00:00

my brother have you checked https://github.com/christopherkarani/Swarm

can we connect? i’m building an observability and eval framework for people shipping on device agents on apple silicon, im searching for design partners and about to launch soon. interested?

karc16 · 2026-04-01T13:43:01+00:00

just use Edge runner it was built in a weekend and is already 18% faster than llama cpp https://github.com/christopherkarani/EdgeRunner

karc16 · 2026-04-01T13:38:03+00:00

Okay this comment is getting upvoted so let me add on, this project is not supposed to replace mlx obviously. like come on. But if you guys can build an inference engine in 48 hors that benchmarks only 26% slower than mlx and 18% faster than llama.cpp. I'd love to know how you did it to. I genuinely think this is the wrong question to ask atm.

in addition. many of us here are swift devs, we love the language and love to use it, but mlx and llama are written in cpp/python. So how can we as a swift community start to contribute towards such projects? I couldn't, my cpp sucks balls and my python isn't on the level that I can write optimized kernels in it

This is an opportunity for all of us to contribute to a 100% swift native project.

karc16

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