How are YOU using PraisonAI? Share your workflows, wins, and wild experiments!

[Dhivya-Bharathy]

I'd love to hear what you're all building with PraisonAI — whether it's a polished production system or a weekend hack that surprised you.

Tell us about your setup

• What problem are you solving with PraisonAI?
• How many agents are in your workflow, and what do they do?
• Which LLM backend(s) are you using?
• Are you using memory, RAG, or MCP integrations?

What's working well?

• What feature saved you the most time?
• Any "aha" moments where agents did something unexpectedly useful?
• How does PraisonAI compare to your previous approach?

What would make it better?

• What's the one thing you wish PraisonAI could do that it can't yet?
• Any rough edges you've hit that we should know about?
• What would make you recommend it to a colleague?

Some use cases I've seen so far

Just to get the conversation started — people are using PraisonAI for:

• Research automation — agents that search, summarize, and compile reports
• Code review pipelines — multi-agent workflows that analyze PRs and suggest fixes
• Content workflows — drafting, editing, and publishing across platforms
• Data analysis — agents that query databases, run analysis, and generate insights
• DevOps automation — monitoring, alerting, and incident response agents

Are you doing something completely different? That's even more interesting — drop it below.

No setup is too small

Even if you just ran the 5-line quick start and played around for an afternoon, I want to hear about it. What did you try? What happened? First impressions matter.

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Reply with as much or as little detail as you'd like. Screenshots, code snippets, and links to repos are all welcome. Let's learn from each other.