9 tiny systems I use to stop AI token bleed and doomscroll drift as a solo Mac dev
Source: Dev.to
Last month I hit two different leaks in my workflow:
- My AI spend kept creeping up from “just one more run.”
- My focus kept getting wrecked by infinite feeds.
I kept treating them as separate problems, but both were attention leaks—small defaults compounding over time. Below are the nine tiny systems that helped me stabilize both.
The 9 tiny systems
1. Set a hard daily spend cap
Pick a concrete limit (e.g., “$8 max today”) and stick to it. Without a cap I always rationalize one extra call, one extra retry, or one extra context blast. A cap forces you to decide between refining the prompt or brute‑forcing more tokens.
2. Real‑time token/cost meter – TokenBar
I keep a live token/cost meter visible in the menu bar so I can see spikes while I’m working.
- Tool: TokenBar – $5 one‑time purchase.
Seeing the burn rate makes me tighten prompts automatically.
3. Use a brief output format with a stop rule
My “brief” includes:
- Done: exact output shape
- Constraints: what not to do
- Stop rule: when to halt instead of looping
This dropped my “almost right, rerun again” loop dramatically.
4. Tiered retry rule
- First miss: tighten instruction
- Second miss: reduce scope
- Third miss: stop and redesign
Without this hierarchy it’s easy to keep paying for emotionally‑driven retries.
5. Feed‑level focus protection – Monk Mode
Not all social apps, just the parts that trigger scroll spirals.
- Tool: Monk Mode – $15 one‑time purchase.
When a feed opens, my brain takes the bait; Monk Mode blocks those surfaces.
6. “Ship blocks” – timed focus sessions
Run 45–90 minute blocks with:
- Feed surfaces blocked
- Notifications minimized
- One repo, one outcome
Pairing restriction with a clear output target (PR, feature chunk, doc update) yields high‑impact work.
7. Keep a fresh context file
When tools crash, reset, or rate‑limit, I no longer rebuild context manually. I maintain a single file with:
- Current objective
- Architecture notes
- Known constraints
- Open questions
Recovery becomes much cheaper.
8. Log expensive failures in a note
Record:
- What prompted the detour
- What signal I ignored
- What I’ll do differently next run
Most cost improvements came from avoiding repeated mistakes, not tweaking model settings.
9. Treat doom‑scrolling time as billable
If I lose 40 minutes to doom‑scrolling, I count it like an actual bill. That framing changed everything.
Quick start for solo AI developers
If you’re building solo with AI all day, try just two changes this week:
- Implement a hard daily spend cap – stick to it for 7 days.
- Add a live token/cost meter (e.g., TokenBar).
You should see both your numbers and sanity improve noticeably.