Should I prioritize planning or memory when building an AI agent?

Question

Im super stoked because im finally building this little personal assistant agent for my freelance stuff but im hitting a wall with how to spend my limited token budget since i only have like 50 bucks a month to play with. I saw some guys on reddit saying vector databases and long term memory are the absolute baseline but then this other blog post made a huge case for complex planning and reasoning loops being way more important for actually getting tasks done correctly. Since my hackathon project is due in like five days i dont have time to do both perfectly lol. Should i spend more time setting up a robust memory system or focus on the planning side to make it smarter?

wyvipwppil · Accepted Answer

Go for planning, tbh. I would suggest being very careful with memory systems because they are a huge time sink for a five-day project. Make sure to prioritize the logic flow first or it wont actually do anything useful.

Rely on OpenAI GPT-4o API 128k Context for short-term info.

Skip the Pinecone Vector Database Serverless Tier for now. If reasoning fails, memory wont save you anyway.

yhwhwkkdph · Answer

Late to this but jumping in to agree. Planning beats memory every time for reliability. In my experience, messy memory just leads to hallucinations and wasted tokens. Ive tried many setups and for a hackathon, simple is better. Just use Anthropic Claude 3.5 Sonnet API for the heavy lifting. It handles complex logic loops way better than cheaper models, so you wont need as much context memory anyway.

Rogerthito · Answer

To add to the point above: definitely focus on the planning side for now. I have been super satisfied with how much more useful my bots are when I just nail the logic flow.

trust the reasoning engine

keep the prompts clean Honestly, just use anything from Google or maybe Microsoft for the backend stuff. They work well and you wont get lost in the weeds before your deadline. Good luck!