Dossier
Quality-first agentic job-search SaaS
Pipeline
The problem
Job search is high-effort and low-signal: hundreds of listings, most irrelevant, and tailoring a resume per role eats hours. I wanted a system that finds, scores, and researches roles autonomously — then produces an ATS-ready resume — for cents per run, not dollars.
Approach
8-agent autonomous pipeline
Persona Builder, Job Discovery, Watchlist, Company Intel, Gap Analysis, Market Intel, Resume Agent and Referral Finder — each a bounded agent with typed inputs and outputs, composed into one run.
Cost-first model routing
A pre-LLM rule filter drops ~60% of jobs at zero cost before any model call. Cheap models triage; expensive models only finish the shortlist — keeping a full run near $0.04.
3-pass self-evaluating resumes
Claude Sonnet tailors → Haiku critiques → Sonnet revises, emitting ATS-optimised LaTeX. A self-evaluation loop replaces one-shot generation.
CLI → multi-user SaaS
M2+ wraps the pipeline in Next.js 16 + FastAPI + Clerk with credits, SSE progress streaming and an async worker for concurrent runs.