General agents burn ~140M tokens/month on LinkedIn outreach; scripts do it 60x cheaper
ChrisHarpon2 · reddit · 2026-10-26
A LinkedIn outreach tool builder ran the numbers on using general computer-use agents vs code:
Token math — one account, one month (1,000 profile checks, 400 invites, 400 messages + follow-ups, daily reply checks): a screenshot→think→click agent takes 7,000 steps × 20k input tokens = 140M input tokens/month. Sonnet: $135–300; Opus: $270–600; Haiku: $15–30 but slow and error-prone. Scraping and clicking need no LLM — code does it for zero tokens; only scoring and message-writing need the model (2.3M tokens, 60x less).
The untalked-about part: scaling = ban risk
- LinkedIn caps weekly invites and watches patterns; agents blow through limits on day 1
- No warm-up, bursty pacing, no account rotation, shared browser profiles create cross-account risk, datacenter IPs don't match your login location
Safe scaling needs per-account limits, gradual warm-up, randomized pacing, and isolated sessions — "that's not a prompt, that's infrastructure." Author notes it violates LinkedIn's ToS regardless, and asks how others handle multi-account setups.
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