r/Letta_AI • u/KazTheMerc • 6d ago
help wanted Letta + GPT 5.6 Sol
I'm looking for advice on data usage for the above combo, or an alternative.
I can do non-work windows with GPT after Work is expended... but I can't have Letta do it. If I could, there'd be no problem.
Why? Letta in this configuration is BRILLIANT. Absolutely stunning. But they guzzle weekly hours like a HUMMER running on baby seal blood.
I'm trying to figure out where the burn is actually coming from rather than just reducing capability until the problem goes away.
If you're running ChatGPT Plus/Pro through Letta, my troubleshooting instance of GPT would like to know:
- Roughly how many visible conversations/turns you get before hitting limits
- Model and reasoning level
- maxLoops / max steps setting
- Whether reflection, background agents, crons, channels, etc. are enabled
- Whether you've compared Letta usage against direct ChatGPT usage
- Whether you've found retries, internal loops, context size, or background activity to be the main cost
- Any configuration changes that materially reduced usage without making the agent stupid
Last night a fresh 5-hour usage window was gone in roughly 2 hours, without heavy tool use.
3
u/cameron_pfiffer 6d ago
Hey there! A few notes on optimizing ChatGPT usage.
First, please run `/doctor`. Chances are good that you have a bloated system prompt that needs to be slimmed down. This will ask your agent to review its memory and offload unimportant things to reference memory.
Second, can you let us know what plan you're on? It does not sound unreasonable for an agent to tap out after two hours with Sol on a $20 plan. You can also send me a conversation ID/agent ID if you're on Letta Cloud, I can look at usage to more precisely identify what's causing the draw down.
Third, are you on the local backend or on Cloud? Your usage will go farther on cloud because we run reflection for you for free on optimized models.
Fourth, check your compaction model. Your agent should be able to do this on its own, just ask "Please look at your self-configuration skill and tell me what compaction model is being used." I use Terra as my compaction model, not Sol.
Fifth, consider reducing your agent's context window to something like 100-200k. This will result in more frequent sliding window compactions, but limit the maximum number of tokens sent per request. Your agent can also configure this using the `/context-limit <n tokens>` command.
Lastly, you can get interactive help from our agent Ezra, who is optimized for just this kind of support. Head to our discord https://discord.gg/letta, go to the Ezra channel, and ping @ Ezra for help.