BUILDING MY OWN AI BLOG TOOL TO OPTIMIZE TOKEN USAGE
A look at leveraging specialized AI models to streamline content creation and overcome token limits.
The Motivation Behind the Build
I’ve been spending a lot of time studying and practicing AI-assisted coding. While I enjoyed using Claude Pro, I kept running into token limits. It broke my flow and made longer sessions frustrating.
Instead of trying to push past those limits, I shifted my approach. I decided to build a simple Python web tool that handles formatting and blog generation for me, and more importantly, lets me optimize token usage by leveraging each model for what it does best.
Building the Tool: Process & Pains
Building the tool in Visual Studio Code only took a few minutes, and about an hour of debugging to get it into a usable state. It’s not perfect, but version 1.0 is functional and already saving me time.
Another challenge was Blogger. It doesn’t play nicely with certain HTML and scripts, so I had to tweak the output to make it compatible. Slightly annoying, but it’s free, so no real complaints.
A Smarter AI Workflow
The biggest improvement came from how I now divide the workload:
- →Claude Code — for software development and building tools
- →Gemini API (free tier) — for general-purpose (running the Python app via API)
- →ChatGPT — for formatting and refining raw blog content
This setup feels more efficient. Each model plays to its strengths, and I’m no longer wasting tokens forcing one tool to do everything.
What's Next
Next steps are clear. I want to enable an AI agent that I can point directly to my Blogger site so it can handle publishing more autonomously. I also plan to improve the Python web tool UI to make it cleaner and more efficient to use day-to-day.
There’s still more to build, but even at version 1.0, this already feels like a meaningful upgrade to my workflow.

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