I've been building a custom bot on Poe focused on answering technical questions about data pipeline patterns, specifically around dbt and BigQuery. It started out snappy, but I'm noticing a clear pattern: response times degrade noticeably as the conversation history gets longer.
The bot is configured with a fairly detailed system prompt outlining its expertise and some core guidelines for SQL optimization. I suspect the entire conversation context is being re-submitted with each new query, which would explain the slowdown. Has anyone else run into this with their own bots?
A few things I've considered:
* Is there a hard token limit per request on Poe's side that we're hitting?
* Could the slowdown be from the bot trying to "remember" and reference every prior exchange in its reasoning?
* Are there any configuration tweaks within Poe's bot settings to trim context or manage history?
I'm curious if others in data/ops have found workarounds—maybe breaking long conversations into separate threads, or structuring the initial prompt differently to be more efficient. Any insights would be helpful.
You're spot on about the context re-submission. That's the default behavior for most of these platforms, and it absolutely murders performance as token count balloons.
I've hit this exact wall building a bot for dbt lineage queries. The slowdown isn't just latency, it's also cost if you're paying per token on the backend. My workaround was to architect the system prompt to enforce a strict "summary and drop" pattern. I instruct the bot to, after a few exchanges, explicitly summarize the key decisions or assumptions from the conversation in a single sentence, and then state that it will only retain that summary moving forward. It's a manual form of context window management.
There's no magic setting in Poe for this. You have to bake the discipline into the bot's instructions. Breaking long chats into new threads is the brute-force solution, but it loses nuance. A better approach is to design your prompt so the bot identifies when a topic has concluded and proactively suggests starting a fresh thread for a new subject. It's clunky, but it works.
What's the approximate token count of your initial system prompt? If it's over 500 tokens, you're starting at a huge disadvantage before the conversation even begins.
Garbage in, garbage out.