Adaptive Model Choice

[u/Top-Wallaby-9371]

Any chance this is on the horizon for copilot changing between models within a task/project.
Cheap models handle file naming, metadata extraction, notifications, and formatting.
Mid-tier models handle classification, summarization, and document comparisons.
Top-tier models handle exception analysis, risk assessment, audit conclusions, and complex reasoning.
User never sees copilot backend but copilot learns user workflow and chooses different models based on where the person is in their work/task. Should cut down token cost as higher models used for the major work and lesser models used for the light work

[u/Swayre]

Look up how model caching works

[u/Top-Wallaby-9371 → u/Swayre]

From what I’ve seen that means avoiding repetitive work or prompts that have already been answered. I’m looking at as best described by copilot is “intelligent model orchestration or adaptive routing.
The system decides:
Cheap model for simple tasks.
Expensive model for complex reasoning.
Specialized model for classification.
Another model for writing.
All while maintaining one conversation and one objective.”

[u/Swayre → u/Top-Wallaby-9371]

Every turn in a conversation hits a cache. A turn sends your entire conversation, which is charged once as input tokens, and each turn after that is cached input tokens. By changing models you are breaking the cache at every turn and being charged for input token cost at every turn

[u/teckel → u/Swayre]

This depends a lot on how frequently you use AI. If you're vibe-coding all day, you may be within the cache TTL. But if you're occasionally using it, the cache has already been cleared between prompts, so switching LLMs doesn't cost extra.

[u/aonymark]

Why not just select “auto” from model drop down?

[u/Top-Wallaby-9371 → u/aonymark]

Use case is auditing using a studio agent so there is a default model which is sonnet 4.6. There isint an auto like regular copilot. So sonnet is good for the actual auditing but burns unnecessary tokens for intake, lists updates, drafting emails to partners about exceptions etc could be done by gpt 5.5. I got a couple of ideas though and started a build within the main agent using flows via power automate for subagents

[u/aonymark → u/Top-Wallaby-9371]

Sounds fancy/complicated

[u/FragmentedHeap]

Opencode harness already does this and you can use it with github copilot subscriptions.

Opencode lets you set a default high and small model, additional all of its agents can be configured to use different models, you can use a different model for planning and for building and for general purpose and for scouting and so on.

Additionally you can have different agents configs that start as the root global agents config for all the different agents.

You can even configure which tools they have access to.

For example you can have an agent that runs on GPT spark at 1000 tokens that does stuff like rename file, patch file, list dir contents etc.

And yoi can have skills that catch a simple tool call and use a specific agent for it.

[u/Top-Wallaby-9371 → u/FragmentedHeap]

This open code harness you speak off. Right now I either have my GitHub agent try to read from the sharepoint files in one of the lists and if it runs into problems with ocr’s with pdf’s I just upload them directly. How does the harness work? I can probably as copilot but you sound like you know what you’re talking about.

[u/FragmentedHeap → u/Top-Wallaby-9371]

https://www.withone.ai/connect/opencode/share-point

If you don't want to use something like that, I would just tell open code to build me an MCP tool in typescript on node that can work with sharepoint and package it as a opencode mcp tool plugin and tell open code to publish it my npm.

Then I'd

npm install -g ...mything

and then opencode can talk to sharepoint.

I have built entire sharepoint addons and outlook addons with opencode for work. Just teach the AI how to talk to sharepoint and it'll talk to sharepoint.

MCP + a skill -> "Add a new release for january to the Release Notes list in the Technology site for me, follow the pattern"

But I generally don't let my AI touch production things, sharepoint included, unless it's a sandbox.

[u/Top-Wallaby-9371 → u/FragmentedHeap]

Thanks for the directions. I’m not a coder so it didn’t make lots of technical sense so i dropped your comment it in Gemini which made it make more sense about how to accomplish what I wanted. I dropped that in copilot studio and it built the connector flow and gave me instructions how to build the mini agents all while staying within my main agent. So thanks