Bridging the Gaps in Today’s AI Workflows
As developers, many of us jumped into large language models (LLMs) with excitement — from writing utilities in Python to automating documentation and even testing logic in our code. Tools like GPT-4, Claude, and Gemini have fundamentally changed the way we work. But as powerful as they are individually, using them together? That’s where the cracks begin to show.
The Problem Isn’t the Models It’s the Workflow
Each model has unique strengths:
GPT-4 is brilliant at structured reasoning and code generation.
Claude excels in summarization, context retention, and humanlike tone.
Gemini brings native access to search, tools, and multi-modal understanding.
Yet, juggling them feels like browser tab overload. You’re copying prompts from one interface to another, retyping instructions, or comparing results manually in Notion, Docs, or a text editor. There’s no memory, no continuity, and no central place to work across models.
The Developer Friction Is Real
For technical users, the problems compound:
No persistent prompt history across tools
Manual output comparison
Token waste due to repeating context
Limited multi-agent experimentation
Time lost to UI switching and copy/paste chaos
Even worse, if you're trying to optimize results across models, train team members, or benchmark outputs the interface becomes the bottleneck
We Don’t Need Another Model — We Need a Better Interface
Let’s be honest: the models aren’t the limiting factor anymore the interface is.
What builders truly need:
A unified, distraction-free workspace
Support for multiple LLMs in one view
A place to save prompts, compare outputs, and take notes
Token usage awareness for API keys
A setup that works with your own API access — not paywalled tools or shadow usage
A Vision from the Frustration: 9xChat
This is exactly what led us to build 9xChat — a floating, multi-agent AI workspace that brings all your favorite models into one focused environment.
With 9xChat:
You bring your own API keys
No login, no lock-in just open, create, and compare
It works offline too (via desktop install)
You can track prompt history, take notes, and manage usage with clarity
We made it for ourselves developers, writers, solo founders tired of bouncing between ChatGPT, Claude, and Gemini just to get things done.
We believe the future of LLMs isn’t just smarter models also it’s smarter workflows.
Top comments (2)
Just show me the prompt you used to generate this article. The thing you wanted to say is there, not here.
that you mention it, sharing the actual prompt flow and some raw thoughts behind how we explored this might make for a good follow-up post. Appreciate you keeping it real.