惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

G
Google Developers Blog
WordPress大学
WordPress大学
奇客Solidot–传递最新科技情报
奇客Solidot–传递最新科技情报
小众软件
小众软件
人人都是产品经理
人人都是产品经理
美团技术团队
Blog — PlanetScale
Blog — PlanetScale
S
SegmentFault 最新的问题
博客园 - 【当耐特】
V
V2EX
Microsoft Azure Blog
Microsoft Azure Blog
博客园 - 叶小钗
Google DeepMind News
Google DeepMind News
量子位
罗磊的独立博客
月光博客
月光博客
N
Netflix TechBlog - Medium
大猫的无限游戏
大猫的无限游戏
博客园_首页
P
Proofpoint News Feed
Jina AI
Jina AI
云风的 BLOG
云风的 BLOG
博客园 - 司徒正美
腾讯CDC

DEV Community

Authentication Security Deep Dive: From Brute Force to Salted Hashing (With Java Examples) Why AI Systems Don’t Fail — They Drift Spilling beans for how i learn for exam😁"Reinforcement Learning Cheat Sheet" I Replaced Chrome with Safari for AI Browser Automation. Here's What Broke (and What Finally Worked) How Python Borrows Other People's Work The $40 Architecture: Processing 1 Billion API Requests with 99.99% Uptime Vibe Coding: A Workflow Guide (From Zero to SaaS) Most webhook security guides protect the wrong side. The scary part is delivery. Headless CMS for TanStack Start: Build a Blog with Cosmic EU Age Verification App "Hacked in 2 Minutes" — What Actually Happened Comfy Cloud’s delete function does not actually remove files Running AI Models on GPU Cloud Servers: A Beginner Guide Event-driven media intelligence with AWS Step Functions and Bedrock I scored 500 AI prompts across 8 quality dimensions — here's what broke How to Call Google Gemini API from Next.js (Free Tier, No Backend Needed) The Portal Protocol: Reclaiming Human Connection in the Age of AI How to Fix Your Team's Scattered Knowledge Problem With a Self-Hosted Forum Intro to tc Cloud Functors: A Graph-First Mental Model for the Modern Cloud Designing Multi-Tenant Backends With Both Ownership and Team Access I Built a Neumorphic CSS Library with 77+ Components — Here's What I Learned PostgreSQL Performance Optimization: Why Connection Pooling Is Critical at Scale Cómo construí un SaaS multi-rubro para gestionar expensas en Argentina con FastAPI + Vue 3 🚀 I Built an Ethical Hacking Scanner Tool – Open Source Project I Replaced /usage and /context in Claude Code With a Single Statusline A Pythonic Way to Handle Emails (IMAP/SMTP) with Auto-Discovery and AI-Ready Design I Collected 8.9 Million Polymarket Price Points — Here's What I Found About How Markets Really Move EcoTrack AI — Carbon Footprint Tracker & Dashboard Everyone's Using AI. No One Agrees How. 5 self-hosted ebook managers worth trying in 2026 Building Your First AI Agent with LangChain: From Chatbot to Autonomous Assistant
I Built 3 Free AI Tools in 3 Hours - Here Is How
zhiyuan kang · 2026-05-20 · via DEV Community

Last Saturday, I woke up with that familiar itch. You know the one - where you want to build something, but you're not sure what, and you end up scrolling Twitter for an hour instead.

But this time was different. I had this thought: "What if I just pick three annoying tasks people deal with regularly and wrap an AI around them?"

Three hours later, I had three working tools. Here's the messy, honest story of how it went down.

Why I Built Them

Honestly? I was tired of seeing AI tools that charge $20/month for something that takes 3 seconds of API calls. The job market is brutal right now. People are applying to hundreds of positions. Friends were asking me to review their resumes. And every single "code explainer" tool wanted my credit card.

So I thought: screw it. Let me build the free versions I wish existed.

The three that came to mind:

  • Cover Letter Generator - Because no one enjoys writing "I am writing to express my strong interest..."
  • Resume Analyzer - The quick feedback you'd get from a friend who's a hiring manager
  • Code Explainer - For those late nights staring at a function that makes zero sense

The Tech Stack (It's Boring, And That's The Point)

Nothing fancy here:

  • Next.js 14 (App Router) - Because I'm lazy and it handles both frontend and API routes
  • DeepSeek API - $0.14 per million tokens. Yes, you read that right. Cheaper than my morning coffee.
  • Tailwind CSS - For making things not look like 1998
  • Vercel - Deploy and forget

The whole thing is literally: form submits → API route calls DeepSeek → returns response → renders on screen. That's it.

DeepSeek was the real MVP here. I'd been using OpenAI but kept hitting rate limits on the free tier. DeepSeek's pricing made it a no-brainer for a project I wanted to keep free forever.

How Each Tool Actually Works

Cover Letter Generator

This was the simplest. A form with: job description, company name, your skills. The prompt is basically:

"Write a professional cover letter for [company]. The job requires [description]. The applicant is skilled in [skills]. Keep it under 350 words, sound human, not like a template."

The trick? I added "sound human" to the prompt. Without it, the letters were robotic and full of "leveraging synergies" nonsense.

Resume Analyzer

This one needed more thought. I built a prompt that evaluates:

  • Keyword matching with the job description
  • Action verbs (nobody wants to read "was responsible for")
  • Quantifiable achievements
  • Overall structure

The response comes back as bullet points with a score. No magic. Just a well-structured prompt and a model that follows instructions.

Code Explainer

The simplest of all. Paste code, get explanation. But I added a dropdown for "beginner" vs "advanced" mode. Beginner mode explains like you're 12. Advanced mode assumes you know what a closure is.

What I Learned (The Real Stuff)

1. Prompt engineering > model choice
I spent way too long comparing models. The truth? A good prompt on a cheap model beats a bad prompt on GPT-4. Every time.

2. Rate limiting is your friend
DeepSeek is fast, but I still added artificial delays and queuing. Nothing worse than a tool that breaks because 10 people used it simultaneously.

3. People don't read instructions
I put "paste your resume here" in big letters. Someone still tried to upload a PDF. So I added a note saying "copy-paste only, I know it sucks." That helped.

4. Free tools attract real feedback
Within 2 hours of sharing on Reddit, I got 47 responses. Some bug reports. Some feature requests. One guy said the cover letter "made me sound like a human instead of a LinkedIn bot." That made my day.

The Embarrassing Part

The first version of the code explainer had a bug where it would sometimes return the explanation in Chinese. Turns out DeepSeek's base model defaults to Chinese if the prompt is ambiguous. I fixed it by explicitly saying "respond in English" at the end of every prompt.

Also, I accidentally left a console.log with my API key in the first deploy. Caught it after 11 minutes. No one stole it, thankfully. Don't be me.

Why This Matters (To Me)

I'm not trying to build a startup here. I don't want your email. I don't want to sell you premium. I just wanted three tools that work, that are free, and that I'd actually use myself.

The code explainer has already saved me twice this week trying to understand legacy code. The resume analyzer caught that I was using "helped with" instead of "implemented" on my own resume. That's worth more than any SaaS subscription.

Try Them (For Free, Obviously)

If you want to check them out:

ai-cover-letter-gamma-ruby.vercel.app

The cover letter generator is the most polished. The resume analyzer needs you to paste text (sorry, no PDF parsing yet). The code explainer works best for Python and JavaScript, but handles most languages okay.

If they break (and they might - I'm one person), give it a minute and try again. Or DM me on Twitter. I'll probably fix it within a day.


One last thing: If you build something similar, don't overthink it. Three hours, three tools, one API key. The barrier to building useful AI stuff is lower than ever. Go make something janky that helps one person. That's enough.