If you switch from claude to codex(or really any other frontier lab) after a spending a little bit of time with how claude writes, you will immediately smell claude's writing from a mile away.
This is pretty basic stuff, just build a bunch of tools with any openAI compatible api and you'll get good. I think stuff like this is kinda overcomplicating simple problems. "Framework free", bruh its just jsonRPC for the most part.
This was probably made to show off for an interview or something, hence why they're throwing throwing around the term "FDE" so much. Its meant to impress a very specific type of person (gullible managers).
Actually yeah, that's kind of the original intent — not trying to go deep on any topic, just trying to get someone unfamiliar to a starting point fast. Once you've got that base, you're free to go deep on your own.
Why does applied AI intentionally exclude a framework/harness around AI? The job is to harness the power of AI, and a harness is a critical part of that.
Glad to hear they are prioritizing evaluation right from the start. Usually people just throw together a rag pipeline on the knee and then judge the metrics by eye, skimming three responses in the terminal
One thing that evals are super important from the get go are where the harness+model inference is part of the product, e.g. if you are doing voice ai, building out a test harness to test the system is a non trivial first step.
I think for voice-ai every one builds their own harness, and thats why there isn't a common one out there. Also if you are a serious company that has a llm in your production loop, you would have to build an in house thing because its so critical to your product. Its like performance-engineering, most performance engineer work is done in house and it varies wildly. Another reason is that because voice quality is a vibe measure(intonition, pitch, human variation), its impossible to make the whole thing deterministic.
I use pi and built a harness for just an llm that calls a bunch of tools. That got me 50% of the way and it would be fast. Then build it for STT and TTS, this will be slower but it will get you far. There are a bunch of tools out there for building basic harnesses.
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[ 0.22 ms ] story [ 29.9 ms ] threadUpon review, it appears that fumbling my way through the dark with Claude and Google led to the same place, in nearly all cases.
However, this is all written by Claude — it has too many em-dashes to not be, does it not? So, maybe that's why we ended up in the same places.
Does anyone know of any related resources to in this vein?
This was probably made to show off for an interview or something, hence why they're throwing throwing around the term "FDE" so much. Its meant to impress a very specific type of person (gullible managers).
I use pi and built a harness for just an llm that calls a bunch of tools. That got me 50% of the way and it would be fast. Then build it for STT and TTS, this will be slower but it will get you far. There are a bunch of tools out there for building basic harnesses.