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docs: guide on using tokens efficiently with AI coding agents#269

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rachaelrenk merged 14 commits into
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rrenk/reduce-token-usage-guide
Jul 10, 2026
Merged

docs: guide on using tokens efficiently with AI coding agents#269
rachaelrenk merged 14 commits into
mainfrom
rrenk/reduce-token-usage-guide

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@rachaelrenk rachaelrenk commented Jun 29, 2026

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Summary

Adds a Guides-section guide on getting more out of your tokens with Warp's coding agents. It lives in Guides → Configuration, alongside "Use Agent Profiles efficiently."

Framed positively around using tokens efficiently and getting more out of each token (per @hongyi-chen), while keeping searchable, non-branded terms.

  • Title: "Use tokens more efficiently with AI coding agents"
  • Slug: how-to-use-tokens-efficiently-with-ai-coding-agents

Changes

src/content/docs/guides/configuration/how-to-use-tokens-efficiently-with-ai-coding-agents.mdx (new)

  • Practical techniques anchored to Warp features:
    • Track usage first (per-turn Usage Summary, /cost, Settings > Billing and usage)
    • Match the model to the task (auto-efficient, auto-open for open-weight models, lightweight models, consistent model for prompt caching)
    • Automate model selection with custom routers (complexity or rules; cost-efficient default)
    • Keep each conversation focused (/new, /compact, /fork-and-compact)
    • Be selective about attached context
    • Let Codebase Context retrieve code (/index)
    • Set up Rules and AGENTS.md (/add-rule, /init)
    • Plan large tasks first (/plan)
  • Includes a per-turn Usage Summary screenshot in "Track your usage first."
  • Notes that Warp meters this usage in credits, which package tokens across providers.
  • Cross-links to a Guides page plus main-docs feature pages (Model choice, Custom routers, Conversation forking, Slash Commands, Codebase Context, Rules, Planning, Blocks as context).

src/assets/guides/usage-summary-panel.png (new)

  • Screenshot of the per-turn Usage Summary panel referenced by the guide.

src/sidebar.ts

  • Updated the Configuration nav entry (new slug + label "Use tokens efficiently").

Review history (@hongyi-chen)

  • Efficiency framing (title + copy): renamed from "Reduce token usage" to "Use tokens more efficiently with AI coding agents," and shifted copy from "reduce/trim" toward "make your tokens go further." Guide is unpublished, so no redirect needed.
  • Credits: added a note that Warp meters usage in credits, which package tokens into a single unit across differing provider rates.
  • Open-weight models: added a "Prefer open-weight models" bullet pointing to Auto (Open-weights) (auto-open).

Notes

  • Screenshot: the Usage Summary capture is currently credit-labeled (shows "credits"). A NOTE comment in the file flags swapping it for a token-labeled version once the credits-to-tokens UI ships.
  • AEO check: validated the wording against Peec — the token-efficiency topic isn't in Warp's tracked prompts/search queries, so there was no data backing "reduce"; the efficiency reframe is a positioning-driven call.
  • Custom routers accuracy: the Custom routers doc says routers can't target BYOK/custom-endpoint models, so the guide doesn't repeat that external claim.
  • style_lint.py passes with 0 issues; local npm run build succeeds. (The earlier failing Vercel preview was a /404 route collision from main, since fixed by fix: resolve /404 route collision and prerender header warnings #313.)

Co-Authored-By: Oz oz-agent@warp.dev

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@rachaelrenk

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Overview

This PR adds a new Guides > Configuration page about reducing token and credit usage with agents, plus the corresponding sidebar entry. I checked the guide against the provided diff, existing docs references, and the security checklist; the links and referenced slash commands map to existing docs, and there are no security findings.

Concerns

  • No blocking concerns found.

Verdict

Found: 0 critical, 0 important, 0 suggestions

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@rachaelrenk rachaelrenk changed the title docs: add guide on reducing token usage with AI coding agents docs: v1 guide on reducing token usage with AI coding agents Jun 29, 2026
@rachaelrenk rachaelrenk self-assigned this Jun 29, 2026
Incorporates the new custom model routers feature: route by complexity or rules to keep routine work off the most expensive models.

Co-Authored-By: Oz <oz-agent@warp.dev>
@rachaelrenk rachaelrenk changed the title docs: v1 guide on reducing token usage with AI coding agents docs: v1.2 guide on reducing token usage with AI coding agents Jun 30, 2026
Credits are being phased out in favor of tokens. Removes credit framing and genericizes credit-named surfaces (usage chip, usage details, usage resets) while keeping links accurate to today's docs.

Co-Authored-By: Oz <oz-agent@warp.dev>
Editorial pass from PR review: clearer intro, accurate Usage Summary description (with TODO for a token-labeled screenshot), tightened custom router and conversation sections, a Next steps lead-in, and a chose->choose typo fix.

Co-Authored-By: Oz <oz-agent@warp.dev>
@@ -0,0 +1,103 @@
---
title: "Reduce token usage with AI coding agents"

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instead of framing it as "reduce" i would try to frame this more around how to be more efficient with tokens / make them go further / accomplish more with less for a cost-conscious audience

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@rachaelrenk I still think we could frame this more positively. Instead of “Reduce token usage,” maybe something like “Use tokens more efficiently with AI coding agents” or “Get more out of your tokens" (i defer to you on the exact messaging, but i think we should stray away from "reduce" -- we'd love to encourage folks to use our agent more!)

The guide is less about cutting usage for its own sake and more about helping cost-conscious users make their usage go further: choosing the right model, keeping context focused, using routers/rules, etc.

---
Every agent task consumes tokens. Tokens are the unit of text a model reads and generates. The more tokens a task uses, the more it costs and the longer it takes, so trimming token usage keeps your agent workflows lean and fast.

This guide covers practical ways to lower token usage in Warp. You'll learn how to choose the right model, route tasks to cost-appropriate models, keep context tight, manage conversations, and configure your agents to work efficiently.

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it's worth mentioning somewhere that in Warp, the unit of measurement is actually credits, but it's essentially packages up tokens into an easier to grok measurement (e.g. different tokens rates across different providers, price of per token, etc)


Larger reasoning models process more tokens per turn than lighter ones, so the model you choose has one of the biggest effects on usage.

* **Use a cost-efficient model for routine work** - Switch to **Auto (Cost-efficient)** (`auto-efficient`), which optimizes for lower token consumption while keeping output quality high. Lightweight models like Claude Haiku also use fewer tokens for simple edits, lookups, and quick questions.

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maybe worth mentioning that if folks prefer open source models, we also have an auto-open (need to double check the exact name) router, or they can create their own custom router

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ah i see you mention the custom routers below, nvm

Per @hongyi-chen review: shift framing toward token efficiency (keeping the searchable title/slug), add a note that Warp meters usage in credits which package tokens across providers, and mention Auto (Open-weights) (auto-open) for open-source models.

Co-Authored-By: Oz <oz-agent@warp.dev>
Per @hongyi-chen review: frame positively around using tokens efficiently and getting more out of each token instead of 'reduce.' Renames to how-to-use-tokens-efficiently-with-ai-coding-agents (unpublished, no redirect needed), updates title, sidebar label, and description, and softens reduction-framed copy.

Co-Authored-By: Oz <oz-agent@warp.dev>
@rachaelrenk rachaelrenk changed the title docs: v1.2 guide on reducing token usage with AI coding agents docs: guide on using tokens efficiently with AI coding agents Jul 10, 2026
Adds the per-turn Usage Summary figure to the Track your usage section (maxWidth 563px). Current capture is credit-labeled; a NOTE comment flags swapping it for a token-labeled version once that UI ships.

Co-Authored-By: Oz <oz-agent@warp.dev>
@rachaelrenk rachaelrenk merged commit 642b1d7 into main Jul 10, 2026
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@rachaelrenk rachaelrenk deleted the rrenk/reduce-token-usage-guide branch July 10, 2026 17:50
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