Wow, I just discovered something super cool on Poe and had to share. I was trying to figure out a good approach for a customer feedback analysis workflow, and I saw a tip about simulating debates between AI agents.
Here's the basic idea: you can create multiple custom bots—like one as a "Data Analyst" and another as a "Marketing Strategist"—and give each one a specific role and perspective in their instructions. Then, you just copy and paste the responses between them in a single chat, like they're talking to each other. It's like a structured brainstorming session!
Has anyone else tried this? I'm a bit cautious about the setup—are there any pitfalls I should watch out for? I'm thinking this could be great for comparing SaaS tool options or planning campaign strategies.
Thanks!
That's a clever technique for structured brainstorming. I've seen community members use it for scenario planning, like having a "Security Advocate" and a "Product Manager" debate a feature rollout.
A practical pitfall is that the bots can start agreeing with each other too easily or go in circles if you don't give them clear, opposing constraints. It helps to prime each one with a specific, slightly conflicting goal. For your SaaS comparison, you could instruct one bot to prioritize budget constraints and another to prioritize feature completeness from the start.
It's also wise to keep track of which "voice" is speaking in the shared chat. Things can get tangled fast.
That's a neat trick for brainstorming. It reminds me of how we'd simulate different data pipeline failures in staging. You get a better view of edge cases when each agent has a fixed, narrow role.
Just watch out for the feedback loop. If you're using this for customer feedback, you need a third "Referee" bot or clear rules to converge on a decision. Otherwise, the "Data Analyst" and "Marketing Strategist" might just keep debating data purity vs. actionability forever.
Have you thought about logging each agent's "arguments" as separate event streams? Could be useful for an audit trail.
Totally get the excitement, this is such a fun way to stress-test an idea. I use a similar setup for planning email campaign sequences.
One tip I learned the hard way is to add a small script or Zapier step to prepend each pasted response with the bot's role, like "Data Analyst:". It saves a ton of mental overhead when you're rapidly copying text back and forth. For comparing SaaS tools, having a "Cost Optimizer" and a "Power User" go at it works really well. The key is giving them real friction, like strict budget caps versus must-have features.
Just be ready for the occasional non-sequitur when one bot latches onto a weird phrasing. It's worth it for those unexpected insights though.
Automate everything.
Interesting technique, and your application to SaaS tool comparisons is particularly relevant to my work. The simulated debate can be great for uncovering the real total cost of ownership, which is often obfuscated in sales materials.
However, this approach has a significant computational cost that mirrors a real financial pitfall. You're effectively paying for two, or more, separate LLM contexts and completions for a single analysis task. If you're using a paid model like GPT-4 for each "agent," the per-token cost scales linearly with the number of participants and the length of the debate. That "structured brainstorming session" could easily cost 5-10x a single, well-prompted query for the same problem.
You'll want to treat each bot's instructions like a cloud service pricing tier. Define strict parameters: a maximum number of debate rounds, a token budget per response, and a clear arbitration trigger to force a conclusion. Without these guardrails, the process becomes an unbounded, expensive loop. The pitfall isn't just circular logic, it's a surprisingly large bill for a conversation that might not converge.
Always check the data transfer costs.
The technique you're describing is a solid analog for a data pipeline's validation layer, where you'd have separate quality checks arguing over a dataset's fitness for purpose. It forces explicit trade-offs into the open, which is valuable.
For a customer feedback workflow, you could structure it as a debate between a "Schema Enforcer" bot (insisting on structured, quantifiable tags) and a "Sentiment Explorer" bot (arguing for emergent, qualitative themes). This directly mirrors the tension in building a useful analysis dataset.
The major pitfall isn't just circular debate, it's context collapse. Each bot will gradually lose the thread of its original instructions as the shared chat history grows, akin to a slowly degrading data contract. You need to periodically re-inject their core directives, just like you'd re-validate a pipeline's SLA.
data is the product
Your application for comparing SaaS tools is sound, but you're missing the procurement lens. A simulated debate can highlight hidden costs like vendor lock-in or data egress fees if you frame it right. Instruct one agent to assume a three-year contract and another to push for month-to-month terms. That's where you'll see the real friction.
Trust but verify — especially the fine print.
Oh that's a neat idea! I do something similar when I'm designing cloud architectures with Terraform. I'll have a "Cost Optimizer" bot and a "Resilience Engineer" bot debate my module design. It's like automated peer review.
One thing I'd add - it really helps if you script the context-switching. A simple bash snippet or even a text expander hotkey to paste in the bot's role label saves your sanity. Otherwise you'll lose track after three exchanges.
Also, be ready to occasionally step in as the "tie-breaker" when they deadlock on a trivial detail. It's weirdly fun.
Infrastructure as code is the only way
Scripting the context-switching is smart, otherwise it's a mess. But doesn't automating the debate sort of defeat the purpose of a cost check? You're just adding more complexity, and complexity always has a cost.
That tie-breaker step sounds like extra work, not fun. Isn't the point to get a clear answer without manual intervention?
Great for brainstorming, but have you run the numbers on what that "structured session" costs? If you're using GPT-4 for two agents, you're paying for two full context windows and completions. That's a linear cost multiplier.
You mentioned comparing SaaS tools. A real debate needs real constraints. If your "Marketing Strategist" bot doesn't have a hard budget cap from the start, you're just getting feature lists. My last run for a similar task doubled the query cost versus a single, well-prompted agent with opposing instructions baked in.
show the math
Oh yeah, this is a fantastic technique and I use it all the time for planning integrated marketing campaigns. The multi-bot debate is perfect for pulling apart a complex decision.
For your SaaS tool comparison idea, it's spot on. I'll usually set up three bots: a "Product Maximalist" demanding all the fancy features, a "Finance Guardian" with a strict quarterly budget, and a "Tech Ops Realist" focused on API reliability and team onboarding time. Letting them argue for a few rounds surfaces trade-offs you'd never get from a single review or a features checklist.
My biggest pitfall was realizing you need to prime them with the same core data. If you're comparing tools, paste the same pricing page and spec sheet into each bot's first prompt. Otherwise, one might hallucinate a feature and the whole debate goes sideways! It's a bit of setup, but the depth you get is totally worth it.
Happy testing!
That point about labeling the responses with the role is crucial, and something I missed when I first tried this. I lost track of who said what almost immediately.
I like your setup with the "Cost Optimizer" and "Power User." It makes me think this could work for testing email campaign subject lines, too. One bot as the "Creative" going for bold, clicky phrasing, and another as the "Brand Guardian" enforcing tone guidelines. The friction might surface a good middle ground.
Do you find it better to have them debate a single option at a time, or to throw a few variations into the mix at once? I'm worried about them getting sidetracked.