---
title: "aNewJob.com | T10 Case Study"
url: "https://t10.net/projects/anewjobcom/"
description: "aNewJob.com — AI Powered Resume Builder ($5 Workflow) We built aNewJob.com , a production grade career platform that turns messy PDFs, DOCX files…"
lastmod: "2026-09-26"
---

# aNewJob.com

### **aNewJob.com — AI-Powered Resume Builder ($5 Workflow)**

We built **aNewJob.com**, a production-grade career platform that turns messy PDFs, DOCX files, screenshots, notes, and LinkedIn exports into polished, ATS-ready resumes, cover letters, and mock interviews — all through a simple **$5 workflow**. It combines a multi-format ingestion pipeline with a lightweight RAG workflow and prompt-driven LLM orchestration to create structured, accurate resumes in minutes.

![aNewJob.com home page](https://t10.net/media/projects/anewjob/home.webp)

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## **Problem**

Most job seekers aren’t bad writers — they’re overwhelmed.

-   Old resumes with inconsistent formatting
-   Missing metrics, unclear bullets, vague responsibilities
-   No structure, timelines, or keyword alignment
-   Expensive resume writers ($200–$600)
-   Existing tools lock people into subscriptions

People don’t need more templates. They need **structure, clarity, and guidance** — delivered fast.

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## **What We Built**

aNewJob.com is a **guided, AI-powered resume workflow**:

1.  **Upload anything**: PDF, DOCX, TXT, screenshots, LinkedIn exports
2.  **AI extracts and structures the data**
3.  **Gap-detection questions** (form or chat mode) fill missing details
4.  **LLMs generate a polished, recruiter-ready resume**
5.  **Users edit in a real-time editor**
6.  **Download as PDF or DOCX**
7.  Optional: **mock interviews** and **cover letters**

All of this is powered by a backend architecture built for **accuracy, speed, and reliability**, not just “magic.”

Screenshots: ![image](https://t10.net/media/blog/ANJ-BlogPost-screen1.webp) ![image](https://t10.net/media/blog/ANJ-BlogPost-screen2.webp) ![image](https://t10.net/media/blog/ANJ-BlogPost-screen3.webp) ![image](https://t10.net/media/blog/ANJ-BlogPost-screen4.webp) ![image](https://t10.net/media/blog/ANJ-BlogPost-screen5.webp)

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## **Under the Hood — Architecture & AI Pipeline**

This project builds on themes from our previous work around **LLM orchestration, RAG, and vectorized structured extraction**. The platform combines:

### **1\. Multi-format ingestion**

We handle PDFs, DOCX, text, and images with OCR. Text is normalized, segmented, and passed to LLMs for structured parsing.

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### **2\. Structured extraction (LLM as parser)**

Instead of scraping text heuristically, we use **LLMs as a deterministic extractor**:

-   GPT-o3-mini converts raw text → structured JSON
-   Experience, dates, skills, education, certifications, projects
-   Normalized schema written to Postgres

This mirrors a RAG pipeline but inverted: instead of embedding → retrieve, this is **unstructured → structured → curated context → generation**.

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### **3\. Gap-Detection Engine**

Given extracted data, a model evaluates what’s missing:

-   Employment dates
-   Missing achievements
-   Skills gaps
-   Weak summaries
-   Roles without responsibilities

This produces a small set (5–10) of targeted questions.

Users can answer them in:

#### **Form Mode** — traditional input fields

#### **Chat Mode** — conversational agent powered by Claude Sonnet 4.5

The chat mode uses a lightweight follow-up loop:

-   LLM checks for missing specifics
-   Generates clarifying questions when needed
-   Normalizes user responses back into structured JSON

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### **4\. Resume Generation (LLM)**

The final resume is generated using:

-   Extracted data
-   User answers
-   Template preferences
-   Tone (professional, impact-focused, academic)

Claude generates structured JSON that’s rendered into:

-   **Modern**
-   **Classic**
-   **Compact**

templates with consistent HTML → PDF and DOCX export.

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### **5\. Real-Time Editor**

A full in-browser editor with:

-   Section-level editing
-   Template switching
-   Auto-save
-   AI rewrite suggestions

Users stay in control — never stuck with a black-box output.

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### **6\. Fast, Production-Ready Layering**

The platform uses reliability layers typically found in enterprise SaaS:

-   SHA-256 hashing to de-duplicate uploads (cuts ~90% of reprocessing)
-   Error handling and retries for LLM calls
-   JSON repair utilities
-   PostgreSQL session store
-   Passwordless email auth
-   Admin panel for live prompt updates

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## **Technical Stack Summary**

**Frontend:** React, Vite, TypeScript, Zustand **Backend:** Node.js, Express, TypeScript **Database:** PostgreSQL **AI Models:**

-   GPT-o3-mini (extraction + questions)
-   Claude Sonnet 4.5 (resume generation + conversation)

**Infrastructure:** systemd, nginx, Puppeteer for PDF, DOCX engine

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## **LLM & RAG Concepts Applied Here**

This project brings together several patterns we focus on at t10.net:

### **RAG without the “R”**

Instead of retrieval, the system generates a **structured, queryable dataset** from user uploads. That structured profile becomes the context window for later generation steps.

### **Deterministic JSON extraction**

LLMs act as **semantic normalizers**, producing machine-consumable schemas instead of long-form prose.

### **Hybrid conversational & form-based UX**

Chat mode uses follow-up logic similar to multi-turn retrieval chat.

### **Prompt lifecycle management**

All prompts are editable live in an admin panel — no redeploy required.

### **Strict guardrails**

Low temperature for extraction, higher for writing. JSON repair functions for malformed outputs. Retry logic for partial failures.

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## **Lessons Learned**

This project reinforced several ideas we’ve seen across multiple AI systems:

-   **Architecture matters more than model choice**
-   **Users want control, not magic**
-   **Reliability is a product feature**
-   **Caching and guardrails are non-negotiable in production**
-   **LLMs perform best when given structured context, not raw text**

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## **Live Demo**

If you’re job hunting — or know someone who is — try the free 30-second checkup: 👉 **[https://anewjob.com/free-resume-checkup](https://anewjob.com/free-resume-checkup)**

Or start the full $5 resume builder here: 👉 [https://anewjob.com](https://anewjob.com)

Have a workflow like this one?

[Book a free AI planning call](https://t10.net/#book)