tobblegobble

I've done more reading about that too and I think I understand it more and how to implement it properly. I'll have a play with it, thanks for sharing.

I just checked out your Go plan and noticed the GLM 5.3 Flash credits are pretty low compared to the other flash models. Is there any plans to change that?

I wrote the prompt to get the agent to write the plugins for me lol

DSH has been fantastic, the customisation is great, like I mentioned before. What has got me to stick with it though is the way it presents information like diffs, subagents, tool calls, thinking and sessions. It's nothing revolutionary but everything is where I want it to be and provides just enough information

I run with DSH, I've found it crazy customisable with the Cordis framework and I feel like I understand how the components in it work. So I'm actually able to articulate to the agent what I want. I Tried pi and OMP but I couldn't get exactly what I wanted.

As for the session maintenance, I have it configured to trigger a compaction when it ends a 'debate' with >25% of context used but before the compaction it puts what it thinks are key points into an MD file. The approach has worked so far in terms of stopping the agent from getting silly with too much context and retaining information. These flash agents get too flakey for my liking past 25%

I'm just going to paste my comment from another post since it is applicable here too, maybe even more so.

I've had really great results with cheap flash agents using a system that has a parent agent that spawns 2 sub agents. They remain active throughout the whole session and don't lose context.

The 2 sub agents get the exact same prompt and tools as each other and they independently answer but before responding back up to the parent they exchange their findings which must be backed up by a citation and then debate their findings and citations repeatedly until they can agree on correctness of all points. They are also heavily encouraged to never assume and always verify with the prompt and tools and guards where they can be realistically enforced.

It churns through tokens but tokens are crazy cheap with some of the plans out there. Could Opus one shot most of those same queries in like 1/4 time? Yep, but that's not the point for me.

DeepSeek Flash for parent then DeepSeek Flash and GLM 5.3 flash as the debating subagents gives best overall results in my experience.

I played with that idea too but found I got better results with them debating each other. Not sure why but I assume the session context for each of them helps a bit.

For context I do equal parts sysadmin/devops and having them write software

I've had really great results with cheap flash agents using a system that has a parent agent that spawns 2 sub agents. They remain active throughout the whole session and don't lose context.

The 2 sub agents get the exact same prompt and tools as each other and they independently answer but before responding back up to the parent they exchange their findings which must be backed up by a citation and then debate their findings and citations repeatedly until they can agree on correctness of all points. They are also heavily encouraged to never assume and always verify with the prompt and tools and guards where they can be realistically enforced.

It churns through tokens but tokens are crazy cheap with some of the plans out there. Could Opus one shot most of those same queries in like 1/4? Yep, but that's not the point for me.

DeepSeek Flash for parent then DeepSeek Flash and GLM 5.3 flash as the debating subagents gives best overall results in my experience.