I cut my AI coding costs and doomscrolling in 7 days (small habits, big difference)

Published: (March 13, 2026 at 04:41 AM EDT)
2 min read
Source: Dev.to

Source: Dev.to

The Problem

  • My AI coding costs were random and stressful.
  • As a solo Mac builder, both cost unpredictability and distraction hit hard.

What Worked in 7 Days

1. Make Cost Visible

I built TokenBar – a tiny Mac app that shows live token usage and spend while I code.
TokenBar – tokenbar.site

Big difference:

  • Catch runaway sessions faster.
  • Tighten prompts earlier.
  • Stop “one more retry” loops sooner.

2. Block Distracting Feeds

My worst cost spikes happened after social‑feed breaks, so I blocked feeds during deep‑work blocks.

I created Monk Mode, a Mac app that blocks distracting feeds at the feed level.
Monk Mode – mac.monk-mode.lifestyle

Result: Cleaner, shorter coding sessions.

The Daily Loop

PhaseAction
Before session• Pick one task
• Define a “done” condition
During session• Monitor token burn live (TokenBar)
• No feed apps (Monk Mode)
After session• Log what caused the biggest spend
• Fix that in the next prompt pattern

Outcomes

  • Fewer zombie coding sessions.
  • More predictable daily spend.
  • Less context thrash.
  • More shipped work.

No magic model switch—just visibility and environment control.

Takeaways

  • If your AI bill feels random, don’t try to optimize everything at once.
  • Make spend visible while you work.
  • Remove feed triggers during build blocks.

That combo changed more for me than any prompt template ever did.


If you’re also building with Claude, Cursor, or Codex and want the exact daily checklist I use to keep both cost and attention under control, let me know.

0 views
Back to Blog

Related posts

Read more »

Travigo

Travel as fast as you speak with Gemini! Where live agents meet immersive storytelling & 3D navigation. This project was created for entering the Gemini Live Ag...

Micro games

Hey Gamers! 👾 As part of the Rapid Games Prototyping module, we are tasked with reviewing a peer's game. The challenge is to analyse a prototype built in just...