Claude Code Now Responds Faster — Anthropic Digs Up a 1992 Compression Technique

TVS News AI, editorially supervised, presents Claude Code Now Responds Faster — Anthropic Digs Up a 1992 Compression Technique.

Anyone who uses Claude Code regularly in their daily routine knows the feeling: you fire off a code prompt, the cursor blinks — and you wait. When that very waiting suddenly gets shorter, there's usually more behind it than a routine software update.

Since mid-October, Anthropic's coding assistant Claude Code has been delivering noticeably snappier responses, according to 01net. The kicker: the speed gain doesn't come from a new model or some hip architecture, but from a data compression technique dating back to 1992 — older than the public web as we know it today.

Specifically, according to 01net, it's an old compression method that Anthropic has reactivated. What's remarkable is who gave the nudge: not the in-house product team, but Claude Code users themselves. According to the report, they had been pointing the company toward this very tool since the end of summer with concrete measurements — mesures à l'appui, that is, backed with data.

Why a 33-year-old idea makes the difference in 2025/2026

That sounds at first glance like legacy data archiving, not modern AI. But that's exactly where the leverage sits: when large volumes of data shuttle back and forth between model and endpoint, every kilobyte saved costs time. A proven compression technique from the 1990s can still do the job — if it matches today's bottleneck. Anthropic apparently didn't have to reinvent the wheel, just pull the right old tool out of the drawer.

The community forced it with hard numbers

Anyone who normally only reads marketing bulletins for AI updates looks twice here. Because the nudge didn't come from the product team in San Francisco, but from the userbase itself. Since the end of summer, 01net writes, developers have been showing the manufacturer with data exactly where the shoe pinches. Which specific latency figures, protocols or tests were involved isn't revealed in the 01net report. What's clear, though, is the direction: people who use beta software daily can absolutely get manufacturers moving with real numbers.

What this means for your day-to-day Claude Code use

If you work with Claude Code yourself, this first means: responses come back noticeably faster. Just how big the jump actually is compared to before mid-October, 01net doesn't quantify — latency gain is one of the few things that tend to stay murky in tech press releases. If you want to feel out for yourself whether the difference is really there: compare a code response from the last September weekend against the identical task today, and you'll find out whether it's nicely noticeable or, well, not the promised boost after all.

Context: Old tricks in modern AI stacks

It's no isolated case that classic methods are enjoying a renaissance in modern AI systems. Data compression, caching, deterministic tokenization — much of what makes the difference today comes from an era when "Large Language Model" wasn't yet a job description. Anthropic's move shows: anyone who does their homework inside their own user community can speed up an entire product with the right old idea — without needing to roll out a whole new model generation.