AI wait time

becomes verified attentionverified attention

AI generation pauses are new inventory. BackSpin turns those wait states into useful product discovery, verifies the human attention behind them, and shares the value with the people creating the attention.

Bid now Install & Get Paid

Get paid while waiting

We turn AI fiddle-faddling wait states into a verified attention marketplace.

50% of the revenue goes to you.91,076 earned by developers

$curl -fsSL https://usebackspin.com/install.sh | bash

Wraps Claude Code, Codex, OpenCode and any AI CLI

Put your wait time to work

Without BackSpin

Percolating.Read · 0.0s

With BackSpin

Railway · ship your backend in seconds .+0 creditsEdit · 0.0s

How it works

The loop that pays while you wait.

Four steps turn idle wait states into verified attention and shared revenue. The loop runs every time your AI pauses to think.

ClaudeChatGPTGeminiPerplexityCursorCopilotOpenCode

01⏳

AI waits

Your AI CLI or editor hits a wait state: thinking, generating, analyzing. Dead time, every session.

02✦

Discovery shows

A relevant, structured discovery card appears in the gap. No clicks required, no interruption to the flow.

03◉

Attention verified

We confirm a real human was focused and active, gating on a human-score before anything is paid out.

04↗

Revenue shared

Quality-adjusted attention earns rewards, and the split between network and builder is transparent.

Bid Now

Open attention exchange

The attention market is already moving.

Advertisers do not buy blind clicks. They buy verified attention share across AI wait states, weighted by TrustRank, relevance, and fairness caps.

Powerful AI attention features for open exchange growth

Everything BackSpin needs to turn AI wait states into verified human attention, transparent market allocation, and useful product discovery across IDEs, CLIs, coding agents, and MCP workflows.

0 low signal100 verified human

+51%focus confidence

+75%human quality score

Verified attention

Every AI wait window is scored by active app focus, typing recency, session depth, and fraud signals before it becomes billable attention.

+18%

active coding

TrustRank

+89%

clean session

TrustRank

TrustRank separates real builders from idle machines by combining session quality, account reputation, dismissal rate, and clean attribution.

Base allocation18%

Purchased boost55%

Fairness reserve27%

Share of voice

Campaigns buy predictable attention share, then BackSpin applies fairness caps so one buyer cannot flood developer inventory.

81% recall matched after exposure

Post-impression recall

When AI tools cannot be clicked during generation, BackSpin measures later saves, visits, searches, and brand recall instead of pretending CTR is enough.

live

ledger health

BidQualityPayout

Open ledger

The public exchange shows bid pressure, verified attention, campaign quality, fraud controls, and payout movement in one auditable feed.

Selected: Verified attention feeds the exchange score before any campaign receives inventory.

Exchange telemetry

Attention economics, visible by default.

Public aggregates from the BackSpin attention exchange: wait states, human-score eligibility, quality-adjusted attention, discovery volume, and rewards, refreshed live from the network.

Two sides, one exchange

Built for both ends of the wait.

For advertisers

Buy attention that’s actually paid.

Reach AI builders in the moments they’re most focused. Every impression is gated on a verified-human score, so you pay for real attention, not bot traffic or accidental views.

Start advertising

For developers

Earn from the time you already wait.

Your AI sessions are full of dead time. Wrap your CLI once and turn those wait states into discovery and shared revenue, with a transparent split and no change to your workflow.

Install the CLI

Open by default

An exchange you can audit, not a black box.

The anti-fraud principles, the scoring methodology, and aggregate audit reports are open. You can verify how attention is measured and how revenue is split. The raw fraud signatures stay closed so they cannot be gamed, but the system that earns your trust stays in the open.

View source on GitHub Open source license llms.txtPublic data · aggregates only · never per-user

Open scoring

How attention is weighted and quality-adjusted is documented and inspectable in the public repo.

Transparent splits

The revenue share between network and builder is published in code, not buried.

Public audits

Aggregate audit reports show the network is measuring what it claims.