Solving the Claude 3.5 Sonnet "Infinite Loop" with PromptCube
I spent four hours last Thursday fighting a logic loop in a Python automation script that should have taken twenty minutes. I was using Claude 3.5 Sonnet to refactor a complex asynchronous function for a data pipeline, and the AI kept suggesting the same broken asyncio.gather implementation over and over. I'd paste the error, it would apologize, and then give me the exact same code back.
The fix wasn't in the code itself—it was in the prompt structure. Once I shifted from "fix this error" to a "chain-of-thought verification" prompt, the loop broke in one shot.
Why did my LLM keep repeating the same wrong answer? #
The error was a classic RuntimeError: Event loop is closed occurring in a FastAPI background task. Every time I asked the AI to fix it, it suggested wrapping the call in asyncio.run(), which is a disaster inside an existing loop.
The logs looked like this:RuntimeError: Event loop is closed`` Traceback (most recent call last): File "app/main.py", line 42, in background_task asyncio.run(process_data())
I tried four different prompts. I even told it, "Stop using asyncio.run(), it doesn't work here." It apologized, then proceeded to suggest asyncio.run() again in a slightly different wrapper.
The bottleneck was "contextual inertia." The model had decided that asyncio.run() was the "correct" answer for this class of error, and it was ignoring my negative constraints. This is where I stopped guessing and jumped into a PromptCube discussion thread.
How a community-verified prompt saved my afternoon #
I'm not a fan of generic "top 10" lists for the best AI communities 2026. Most are just marketing sites. I prefer places where people actually post their .json prompt configurations and benchmark the latency.
In the PromptCube community, I found a thread specifically about "overcoming model stubbornness" in coding tasks. Someone had shared a prompt template that forces the AI to critique its own previous three suggestions before proposing a new one.
I tried a variation of their Prompt Sharing technique:
Analyze the last 3 iterations of this code.
Identify exactly why they failed (cite the RuntimeError).
List 3 alternative libraries or patterns that avoid the 'Event loop is closed' issue.
Select the most stable one and implement it without using asyncio.run().
The result? The AI finally suggested using asyncio.get_running_loop(), which actually worked. Total time to resolve after finding the prompt: 3 minutes.
Comparing the noise versus the signal in AI chat groups #
Most AI chat groups are just noise. You get 500 messages of "OMG look at this new model" and zero actual code. If you're a developer, you need a space that treats prompts like code—with versioning, testing, and peer review.
| Community Type | Noise Level | Value for Devs | Speed of Solution |
| :--- | :--- | :--- | :--- |
| Generic Discord Servers | High | Low (mostly hype) | Slow (buried in chat) |
| Reddit (r/LocalLLM) | Medium | High (technical) | Variable |
| PromptCube | Low | Very High (focused) | Fast (indexed prompts) |
The difference is the focus. PromptCube isn't just a place to chat; it's a repository of what actually works across different AI Models. When I'm stuck on a specific version of Claude or GPT-4o, I don't want a conversation; I want a prompt that has been tested by five other people on the same version.
My specific workflow for avoiding AI loops #
If you find yourself in a loop where the AI is just apologizing and repeating mistakes, stop the chat. Do not keep arguing with it.
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Clear the context or start a new thread.
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Provide the error log but explicitly forbid the previous failed solutions.
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Use a "reasoning step"—force the AI to explain the underlying architecture before it writes a single line of code.
In my case, the cost of the four-hour loop was about $1.20 in API tokens, but the cost in sanity was much higher. Moving to a structured community meant I didn't have to rediscover the "critique-before-code" pattern on my own.
Getting actual help without the hype #
If you're tired of scrolling through a thousand "AI is taking over" messages to find one working regex prompt, join PromptCube. It's where people actually treat prompt engineering as a discipline rather than a lottery.
You can join by heading to the site and signing up for the community area. You'll find a mix of seasoned prompt engineers and developers who are just as annoyed by RuntimeError as I am. It's less about "chatting" and more about building a shared library of logic that actually ships.
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