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points by bluegatty 1 day ago | 0 comments

Both of those orchestrations will work for sure.

Smart agent to orchestrate cheaper agents for labour.

Dumber agents to be very explicit about asking smarter agents for requests that require deep information.

This is a thing - the SOTA models really light up the more information you can provide them, and humans are too lazy / incapable of doing that in every prompt.

Entirely depends on what you are trying to do.

Edit: you can also use a smart agent to ask another smart agent, obviously, which is good for personal workflows.

[–] fireant 21 hours ago

Doesn't that muddle intent of the original prompt? If the smarter model didn't understand your intent correctly, the dumber one sure won't and it rephrasing and expanding the prompt will just amplify it's misunderstanding, no?

[–] pletnes 17 hours ago

It could make sense to use a cheap model to decide if you need to run a long, high effort or otherwise costly effort. Then you can take many decisions at low cost, but think hard when it’s time to make an important decision.

[–] bluegatty 19 hours ago

You wouldnt normally use a dumb model as a personal agent to get a smarter model to do work, but you may make use of that mechanism in some kind of automation process.

But there are definitely cases.

GPT Pro is an absolutely spectacular model, that almost cannot be used without 'prompt help'. Or rather, it can only be effectively leveraged by very intricate prompting, which requires the help of another agent.

I typically use Claude Code to write prompts for GPT Pro , and cut and paste the prompt in, and let GPT Pro work for 20 minutes, then take the response back to Claude Code and work with Opus to consider the results.

Opus is 'dumber' (nominally) then GPT Pro.

[–] agentdev001 14 hours ago

What is GPT Pro?

[–] bluegatty 11 hours ago

GPT Pro is the pro setting on OAI's consume chat model. It is only available online or API.

It's branded as a separate model, but really it's like an 'ultrathinking' mode of OAI's model.

The details are not public but it's parallel test time compute and multi search, aka the model reasons along different vectors and compares answers.

If 'feels like' a smarter model, even though I'm pretty sure it's a synthetic variation of Astra.

It is by far the 'smartest model' if you were to benchmark it, and many of OAIs released were based on this.

There are few or no benchmark scores on it because it's not suitable for harness testing or coding, it's almost designed to be 'one shot' or 'few shot'.

It takes 8-25 to answer, and if you give it a sufficiently sophisticated prompt, it will think for 1 hour.

It requires OAI's 'pro' account aka the $200/month one.

It's the best open secret in AI, I can't recommend it enough.

[–] agentdev001 10 hours ago

Oh wow, as someone who prides themselves on my depth of knowledge on the OpenAI docs, im ashamed I didn't know about this! I figured that Pro was a deprecated feature post 5.6 family release. Didn't realize Mode:Pro was something you could do with 6 and 6.1, thanks!

[–] seemaze 1 day ago

>you can also use a smart agent to ask another smart agent

What's the best method to have a 'smart' agent just.. ask itslef?

[–] dimava 21 hours ago

Generally, you want a different smart agent as they have different strong sides (e.g. call Sol for a review from Opus)

You may use https://github.com/pingdotgg/t3code as a wrapper above claide/codex/pi/... harnesses, or a proxy below (forgot which one, as agent what theo uses for balancing multiple claude subs)

[–] brabel 18 hours ago

I highly doubt that claim, has it been tested rigorously? I understand mixing different models to save money and time by using cheaper and faster models for certain tasks. But different models just to increase accuracy seems implausible.

[–] bluegatty 11 hours ago

Mixing models almost assuredly does increase accuracy in many cases - I do it all day every day and I can only say from experience though not true objective benchmarks.

I use codex/claude code all day every day and built an MCP that allow them to use each other as sub-agents.

I will not allow claude code to touch my code with any design changes without codex auditing it, and visa versa.

I believe this is the case merely because they are different models that will provide varied perspectives, and smart enough to identify issues on each other's work.

I'm not sure if there's research to back this up but I think it's fairly obvious, and also FYI diminishing marginal return - I'm not sure if a '3rd perspective' would be worth it in most cases.

[–] neal_jones 9 hours ago

Something I’ve added is a step where the agent asks itself how confident it is in the solution/implementation - if it isn’t “High” it then has to ask a smarter agent to review.

Not sure it’s the best approach but it has improved results.

[–] bluegatty 1 day ago

Just ask. The agents already know how. To boost it, have it read the exact docs that OAI/Anthropic provide.

Asking Claude to make prompts is like a Math teacher stuck working at a cafe about Math problem, the just light up.

They are very good at at it.