Yo Dev! Here’s How I Use AI Tools Like Codex CLI and Aider to Speed Up My Coding
Hey there 👋
If you’re anything like me, you’ve probably been drowning in code at some point, thinking,
“Man, I wish I had a junior dev I could just tell what I want done…”
Well — good news — you kinda do now.
Let me show you how I use Codex CLI and Aider (plus a cool mode called --architect
) to make coding way easier, especially if you’re into using AI locally (LM Studio, Ollama, you name it).
🔧 What These Tools Actually Do
Here’s the quick version:
Tool | What it’s for |
---|---|
Codex CLI | You type a prompt in terminal, it analyzes code and gives ideas or code snippets — like “Explain this class” or “Refactor this function” |
Aider | You chat with your code — and it edits your real files based on what you say. Super clean with Git support |
Architect Mode (in Aider) | You describe the app you want to build → it gives you file/folder structure and even fills in basic code to get you started |
🧪 Codex CLI — My Quick Code Sidekick
Install it:
pip install codex-cli
Now try:
codex "Explain what the login function does in auth.py"
or:
codex "Generate a test for the payment() function"
It won’t edit your code — it’s more like asking an AI senior dev:
“Hey, can you help me understand or draft something?”
Perfect for:
- Code reviews
- First drafts
- Brainstorming ideas fast
If you use local models, just point it to LM Studio or Ollama by setting endpoint
in your ~/.codex/config.yaml
.
🤖 Aider — When You Want the Code Actually Changed
Okay this one’s nuts.
Run this in your project folder:
aider main.py
Now chat like this:
“Make all functions in this file async”
“Replace requests with httpx”
“Add error handling to database calls”
It’ll show you a diff. You say yes or no. Done.
And if you’re using Git (you should), it’s super safe and easy to revert anything.
Great for:
- Refactors
- Bug fixing
- Feature updates
🏗️ Aider --architect
— Start a Project from Thin Air
Let’s say you’re building something from scratch.
Run:
aider --architect
Then say something like:
“A FastAPI app with login/signup and todo item CRUD.”
Aider will:
- Propose a file layout
- Fill in skeletons for
main.py
,models.py
, etc. - Ask if you want to edit/approve/add/remove
- Then write the files for you 🎉
This is awesome when you:
- Don’t want to write boilerplate by hand
- Want to try ideas quickly
- Need a jumpstart on a side project
👀 Which One Should You Use?
If you want to... | Use this |
---|---|
Understand or explore code | codex |
Change real files live | aider |
Build a project scaffold fast | aider --architect |
🧠 Local Models? Yup, They Work Too
All of these tools can talk to local models if they support OpenAI’s API format (like LM Studio or Ollama).
Just set this in your config:
llm:
provider: openai
endpoint: http://localhost:1234/v1
api_key: sk-no-need
Try with:
qwen1.5-7b
deepseek-coder
phi-3-mini
codellama-instruct
💡 Real Examples I Use
Task | Prompt | Tool |
---|---|---|
Build new app | “A CLI app that tracks expenses to a CSV file” | aider --architect |
Cleanup | “Refactor this view to use class-based API” | aider |
Review code | “What does the class TokenManager do?” | codex |
Generate test | “Write a pytest for update_item()” | aider |
🔄 Typical Flow I Use
flowchart TD
A["🧠 I get an idea"] --> B["🏗️ aider --architect creates the base"]
B --> C["📂 Project structure + code stubs"]
C --> D["🤖 aider edits & refactors my files"]
D --> E["🧪 codex gives me analysis & extra ideas"]
🎯 Final Thoughts
Honestly, these tools feel like a cheat code for solo devs and small teams.
You get:
- Less boilerplate
- Fewer bugs
- A teammate who never sleeps 😎
If you haven’t tried them yet — go play! You’ll thank yourself later.
🔗 Links to Check Out
- 💬 Codex CLI GitHub
- 🤖 Aider
- 🧠 LM Studio
- 🖥️ OpenWebUI
Get in Touch with us
Related Posts
- Working With AI in Coding the Right Way
- How to Select the Right LLM Model: Instruct, MLX, 8-bit, and Embedding Models
- How to Use Local LLM Models in Daily Work
- How to Use Embedding Models with LLMs for Smarter AI Applications
- Smart Vision System for Continuous Material Defect Detection
- Building a Real-Time Defect Detector with Line-Scan + ML (Reusable Playbook)
- How to Read Source Code: Frappe Framework Sample
- Interface-Oriented Design: The Foundation of Clean Architecture
- Understanding Anti-Drone Systems: Architecture, Hardware, and Software
- RTOS vs Linux in Drone Systems: Modern Design, Security, and Rust for Next-Gen Drones
- Why Does Spring Use So Many Annotations? Java vs. Python Web Development Explained
- From Django to Spring Boot: A Practical, Visual Guide for Web Developers
- How to Build Large, Maintainable Python Systems with Clean Architecture: Concepts & Real-World Examples
- Why Test-Driven Development Makes Better Business Sense
- Continuous Delivery for Django on DigitalOcean with GitHub Actions & Docker
- Build a Local Product Recommendation System with LangChain, Ollama, and Open-Source Embeddings
- 2025 Guide: Comparing the Top Mobile App Frameworks (Flutter, React Native, Expo, Ionic, and More)
- Understanding `np.meshgrid()` in NumPy: Why It’s Needed and What Happens When You Swap It
- How to Use PyMeasure for Automated Instrument Control and Lab Experiments
- Supercharge Your Chatbot: Custom API Integration Services for Your Business