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Paste This Into Claude, Never Hit a Token Limit Again

2026-07-29 · 14:00 UTC ·AI News & Strategy Daily | Nate B Jones ·1 min read

Brief

Nate B Jones's video 'Paste This Into Claude, Never Hit a Token Limit Again' (presentation/tutorial) lays out 15 practical rules to reduce AI token usage, demos a Token Saver skill for Claude/Codex, and walks a workflow that combines local pre-call checks, prompt caching, and a 'ringer' intermediary to avoid sending repeated context and extend token budgets.

Why it matters

Nate B Jones (AI News & Strategy Daily) published on 2026-07-29 a ~19-minute video presenting 15 rules to cut reused input and stretch AI token budgets, and demos a 'Token Saver' skill that automates trimming repeated context for Claude and OpenAI Codex.

Key details

  • Actionable workflow items include Rule 1 ('edit your mistakes instead of arguing with them') at 04:40, an explanation of the Token Saver skill at 11:13, prompt caching at 15:35, and using a 'ringer' intermediary at 16:23; he advises local pre-call checks because a local check beats any post-call skill.
  • Core insight: reused input (context sent repeatedly) dominates token cost—so later messages can cost far more than the first—therefore Token Saver, prompt caching, and an intermediary reduce repeated context and meaningfully extend usable token limits.
Source evidence

Running out of AI tokens on ChatGPT, Claude, or OpenAI Codex? Here are the 15 rules I use to cut reused input and get more real work out of the same plan.

Full post w/ Token Saver Skill + Guide:
https://natesnewsletter.substack.com/p/reduce-ai-token-usage?r=1z4sm5&utmcampaign=post&utmmedium=web&showWelcomeOnShare=true

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What's really happening inside your AI token limits?

The common story is that hitting a limit means you asked too much — but the real question is how much of every request you never typed.

In this video, I share the inside scoop on keeping your AI desk clean:

  • Why your tenth message costs far more than your first
  • How reused input quietly dominates every request you send
  • What the Token Saver skill automates inside Codex and Claude Code
  • Where a local check beats any skill running after the call

Better tools are coming, but deciding what a job actually needs to remember stays the work you own.

Chapters:
00:00 you keep running out of claude, codex or chatgpt tokens
04:40 rule one, edit your mistakes instead of arguing with them
11:13 the token saver skill and what it automates for you
15:35 prompt caching and when it actually matters
16:23 ringer as an intermediary before the model provider
18:51 keeping your desk clean and what comes next

Listen to this video as a podcast.

Spotify: https://open.spotify.com/show/0gkFdjd1wptEKJKLu9LbZ4
Apple Podcasts: https://podcasts.apple.com/us/podcast/ai-news-strategy-daily-with-nate-b-jones/id1877109372

Channel: AI News & Strategy Daily | Nate B Jones
Published: 2026-07-29
Video URL: https://www.youtube.com/watch?v=Y8vAQ1FgNbM