35,000 AI calls last week. 23 million tokens. Zero human in the loop. Here's what that actually

35,000 AI calls last week. 23 million tokens. Zero human in the loop. Here's what that actually35,000 AI calls last week. 23 million tokens. Zero human in the loop. Here's what that actually

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Kelvin Desman

pro

• May 20

35,000 AI calls last week. 23 million tokens. Zero human in the loop.

Here's what that actually looks like inside lokerdollar.com.

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What those pipelines do:

Job ingestion + enrichment (15 sources) → job boards, Reddit, Hacker News — each with its own AI pipeline to normalize, classify, and enrich

Job summaries → every job rewritten with local salary context, timezone fit, and red/green flags for the candidate

Content generation → draft → critique → polish chain for every blog post

Email automation → AI writes the subject line AND the opening hook for every transactional email individually

User-facing career AI → resume parsing, scoring, tailoring, regeneration → cover letter writing

Self-monitoring → the routing logic itself is AI — a "select" task that decides which provider handles each call

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The part most "AI startup" posts miss:

91% of these tokens never touch a user.

They run quietly — ingesting, normalizing, enriching, translating, scoring, deduping.

User-facing AI (resume tools, cover letters) is barely 1% of the actual workload.

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The moat isn't the chatbot.

The moat is the 30 invisible pipelines behind it — doing boring work consistently, on free providers, 24 hours a day, with no human in the loop.

Most "AI startups" hit a wall because they built a feature. The ones that survive build a pipeline.

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This is the kind of stack I help other solo founders and small teams set up. If you're stuck paying frontier prices for routine work, the routing layer pays for itself within a week.

Drop a comment — happy to share the pattern.

#BuildInPublic #AI #SoloFounder #IndieHacker #Engineering