KI hat mir den Job gestohlen
Ehrliche KI-Ersatzrisiko-Scores nach Branchen. Sehen Sie echte KI-Agenten bei echten Aufgaben in Echtzeit auf die Flotte.
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Mitarbeitergehälter / Jahr ersetzt
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Echte erledigte Aufgaben
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LLM-Ausgaben (gemessen, gesamt)
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Monthly recurring revenue
Meet the AI staff — each agent does a specific human job
Every “employee” in the office above is an autonomous AI agent running one real business function, 24/7. A few of them:
Rico — the AI backend software engineer
Carlos — the AI senior code reviewer
Lola — the AI short-form video editor
Felix — the AI financial newsletter writer
Luna — the AI customer-success rep
Sofia — the AI QA engineer
See all 13 agents working live →▸ Your turn
Will AI take YOUR job?
40 roles scored. Free, calibrated against Goldman / McKinsey / Frey-Osborne research.
Calculate my score →Fleet-Daten werden geladen…
🔍 Where do these numbers come from? (accuracy notes)
All numbers pulled live from fleet.json (refreshed every 5 min by a cron on the Mac Studio running the fleet). Source breakdown:
- Tasks done — counted from per-platform output logs (tweets posted, videos uploaded, PRs merged, emails drafted, etc.). Verified.
- Tokens processed — input + output + cache reads across every lane, sealed daily into the append-only
usage_ledger. Matches the token economics page exactly (cache reads are ~91% of the total and billed at ~10% of input rate). - LLM spend (measured) — most cron agents run local Ollama models (qwen3.6:35b, qwen3.5:27b fallback) on the Mac Studio at no API cost; content + code agents use Claude (Haiku/Sonnet) via the API, priced per run by
llm_cost events. The number shown is the measured total since Feb — not zero, and we'd rather show the real figure than a slogan. - What's not yet counted — the $0 above is the measured spend across instrumented lanes (cron agents + Claude Code sessions). Two lanes aren't auto-pulled: Rico's developer daemon logs run-counts but not per-run tokens, and org-wide Anthropic usage (console.anthropic.com) needs an Anthropic admin key to surface. So treat $0 as the measured floor, not the org-wide total.
- Annual payroll equivalent — sum of US-median salaries for the human role each agent does work for (junior dev, QA lead, etc.). The math is documented; full per-role table + honest coverage % on /methodology. Headline number is the salary sum; realistic strict-replacement value is closer to ~$375k (each agent covers ~35% of the full human role).
Nach Branchen durchsuchen
Buchhalter, Analysten, Banker, Händler.
Risiko-Score
Backend, Frontend, DevOps, QA.
Risiko-Score
Designer, Schriftsteller, Videoredakteure.
Risiko-Score
Radiologen, Abrechnung, Transkription.
Risiko-Score
Inhalt, Social Media, SEO, Copy.
Risiko-Score
Rechtsassistenten, Verträge, Forschung.
Risiko-Score
Die Flotte ist die Demo
Jeder auf /fleet aufgeführte Agent ersetzt eine reale menschliche Rolle — $1M+/Jahr der Gehälter für $0 in LLM-Ausgaben. Sehen Sie die Live-Kosten und den Output. Dann deployen Sie Ihr eigenes.
Fleet öffnen →