New Currency
Forget cloud bills — in 2026 the line item engineers actually argue about is tokens. Every move a coding agent makes (reading a file, running a test, replying "Sure, happy to help!") has a price tag attached.
Buzz around
The dev community has been buzzing about a few repos lately, all tackling the same problem: do the same work, spend fewer tokens. What's interesting is that each one attacks it from a totally different angle — like three different ways to cut a grocery bill: buy less, waste less, and stop paying for the gift wrap.
How to spend less?
rtk — github.com/rtk-ai/rtk
The "stop paying for noise" layer. It sits between your agent (Claude Code, Copilot, Cursor, etc.) and your terminal, and compresses the output of everyday dev commands — git status, test runs, docker ps, build logs — before any of it reaches the model's context. Most CLI output is boilerplate the model never needed in the first place; the project claims 60-90% savings on routine commands as a result.caveman — github.com/JuliusBrussee/caveman
Flips the problem around: instead of compressing what goes in, it compresses what comes out. It's a skill that makes your agent answer in short, fragment-heavy sentences instead of polite paragraphs — same technical content, way fewer words. It reports roughly 65% fewer output tokens with accuracy intact, and has a side feature that compresses memory/context files (like CLAUDE.md) so every new session starts smaller too.superpowers — github.com/obra/superpowers
Doesn't compress anything directly — it goes after the most expensive token sink of all: waste. Disorganized agent sessions burn tokens re-explaining context, wandering down the wrong implementation path, and redoing work nobody planned properly. Superpowers is a structured workflow (brainstorm → plan → test-first build → isolated subagent execution → review) that keeps the agent on-task and hands work off to fresh subagents so the main conversation doesn't balloon. Less backtracking, fewer tokens paid for twice.
Wrapping up
Put together: one shrinks what comes in, one shrinks what goes out, and one stops you from paying for the same work twice. Three different layers of the exact same economy.
Funny thing — a year ago we were all measuring AI cost in "API calls." Now we're tuning prose style for token efficiency. The grind never stops, it just changes units.
What else you have used?
My Other Blogs:
- Personal Agentic AI Assistant - Architecture
- Openclaw Personal AI Assistant Complete Series
- “Skills” in Claude Aren’t About Prompts — They’re About Context Design
- Practical Tips When Working with AI Coding Assistants
- Trying MCP for the First Time — What Stood Out
- Subagents: The Building Block of Agentic AI
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