Regarding what #1 said about "Honestly, if you only have $200 left, you" should stick to tools, I think memory is the real MVP! I am totally obsessed with Mem0 Managed Memory API Cloud lately. It is fantastic at extracting facts so your agent doesnt repeat mistakes. This stops those loops and saves your budget! TL;DR: Use a memory layer to stop context rot and save tokens.

^ This. Also, Ive spent a massive amount of time in these trenches and while the debate between tools and memory is valid, there is a third piece of the puzzle. Back in the day, I built an automated outreach bot for a client... My plan was to give it a massive reflection prompt so it could self-correct. Ended up with a $400 bill and a bot that apologized for its mistakes 50 times in a row without actually fixing them. Total nightmare. Since youre doing lead gen for a marketing agency, you really need to look at orchestration. Tools like LangChain LangGraph State Management Library are a lifesaver because they let you map out the agents path as a state machine. The reason your agent is looping or forgetting is usually because it has too much freedom to drift. By using something like CrewAI v0.28 Multi-Agent Framework, you can break the lead gen process into tiny, manageable steps. One agent finds the lead, one validates the email, and another writes the draft. It saves a ton of money on your API budget because the prompts stay short and specific. Memory and tools are great, but without a solid structure to keep the agent on the rails, youre just throwing tokens into a black hole. Stick to a structured framework and youll hit that Friday deadline no problem.

> ^ This. Also, Ive spent a massive amount of time in these trenches and while the debate between tools and memory is valid I agree with Jasonzew that those reflection loops are basically just money pits. They burn your budget way too fast when you're on a tight deadline. Since you only have a few days left, I would suggest focusing on structured output schema validation instead of complex reasoning loops. Make sure to force your model to return strict JSON for every action. If the output doesnt match your schema exactly, just catch the error immediately and retry once or twice before failing over to a hard-coded fallback path. It adds a bit of stability without the massive token cost of having an agent contemplate its own existence. Be careful with how many retry attempts you allow though, or you might still eat through those last 200 dollars real quick.

Building on the earlier suggestion, I actually think focusing on the agent's actual logic flow is safer than relying on external memory layers or complex loops when you are on a budget. Honestly, if you are stuck in loops, it is usually because the prompt structure is too loose. You might have better luck switching to Anthropic Claude 3.5 Sonnet for your agent brain. I have found it follows instructions way more reliably than older models, which actually saves you money on retries because you dont have to run the cycle five times to get a clean result. Also, consider using LangSmith Platform to trace exactly where it is failing. It makes it super obvious if your tool calling or prompt is the issue. Forget the fancy self-reflection stuff for now. Just get your structured output working with a model that actually listens, like Sonnet, and you will save way more of that $200 than you would by bolting on extra layers.

Honestly, if you only have $200 left, you gotta prioritize function calling. I had high hopes for self-reflection loops but they are not as good as expected and just burn through tokens. Most of the time they just hallucinate more or get stuck in those annoying loops you mentioned. It is frustrating because everyone talks them up, but for a solo agency, you just need the thing to actually work. I suggest sticking with OpenAI GPT-4o API for the tool use since it handles CRM calls better than most. For the memory issue, unfortunately, those long context windows get pricey fast, so just use Pinecone Serverless Index to store your leads and history. It is way more stable than trying to shove everything into the prompt. Dont worry too much about it being perfect by Friday, just get the CRM integration solid first... thats the real backbone. If you get stuck on the API calls later this week, just shout.