The latest articles on DEV Community by Ahmed H (@ahmed_h). https://dev.to/ahmed_h https://media2.dev.to/dynamic/image/width=90,height=90,fit=cover,gravity=auto,format=auto/https:%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Fuser%2Fprofile_image%2F3905977%2F9b0e92aa-4535-40df-8725-a5abe9df10ad.png https://dev.to/ahmed_h en Ahmed H Thu, 30 Apr 2026 11:13:15 +0000 https://dev.to/ahmed_h/i-built-a-prompt-compressor-that-cuts-token-usage-and-help-prevents-prompt-decay-in-long-sessions-jf3 https://dev.to/ahmed_h/i-built-a-prompt-compressor-that-cuts-token-usage-and-help-prevents-prompt-decay-in-long-sessions-jf3 <p>If you use Claude (or any LLM) for long sessions you've probably hit this at some point. You're deep into a coding project or research session, halfway through finishing what you started, and you notice the AI starting to take shortcuts, answers that are clearly rushed, constraints you set early being ignored, and you end up sending more messages just to correct it, which eats into your limits for no reason.</p> <p>This is Prompt Decay. It's not a Claude bug, it's just what happens when your original instructions get buried under everything that came after them.</p> <p>I started looking for ways to slow it down, and that's when I noticed something about my own prompts, they were messy, unclear, full of stuff the AI had to work around just to find what I actually wanted. My prompts were fine as is, but they could be more compact, use fewer tokens, and get the same output quality, so I built a tool to do just that.</p> <p>Squaizer compresses your prompts down to the actual signal, strips the filler, keeps your constraints and role definitions intact. The token reduction is significant and the demo shows you the before/after count directly. Fewer input tokens means your context window lasts longer, which matters most in exactly the sessions where Prompt Decay hits hardest. On the API it's also just cheaper.</p> <p>One thing I found while building it that genuinely surprised me: Claude mirrors the density and structure of what you send it. Tighter input, tighter responses. It's just how attention works, but it means the compression compounds. You're not just saving tokens, you're getting cleaner output back too.</p> <p>Desktop app has a fast squeeze hotkey. Select your text anywhere, press it, compressed prompt replaces it instantly in place.</p> <p>Free 1000 user beta at <a href="http://squaizer.com/" rel="noopener noreferrer">squaizer.com</a>. live demo on the homepage, no account needed.</p> <p>Happy to get into how it handles edge cases or complex prompts if anyone's curious.</p> <p>Curious if any power users or API users here actually feel this problem enough to use a tool like this. Or have you found other ways to deal with it?</p> ai promptengineering programming productivity