In this day and age, it’s nearly a necessity to use AI as part of your workflow. There’s a plethora of AI tooling to help you with Python development.

There isn’t a right or wrong answer as to which tooling to use, but it’s more of a question of what tooling works best for you; it’s a trade-off decision.

We see this very frequently in software development. For instance, an organization may prefer using AWS SQS over Kafka. Kafka is powerful, but there’s limiting factors that would make SQS a better choice: cost and staffing technical overhead to name a few.

Similarly, some people prefer using Midjourney for image generation whereas I’d prefer Nano Banana. In fact, depending upon the use case, I’d preference ChatGPT, such as generating thumbnails for the Python Snacks website.

The AI tools I’m using for my Python development workflow

These are the tools I’m using in 2026 as of now; I fully anticipate adding 1-2 more this year as the field evolves.

Tool / Model

Use Case

Cost/Month

ChatGPT / 5.1

General querying, trade-off discussions

$20/mo

Claude / Sonnet 4.5

Building, stubbing code, writing docs, trade-off discussions

$20

Gemini / Nano Banana

Ad-hoc image generation specific attention to detail

Free

Gemini / Gemini 3

Deep research on specific topics

Free

Searching through project documentation asking specific questions

Free

MVP/prototyping ideas that require a web interface

$25/month until credit limit is reached

Secondary deep research in parallel with Gemini 3

Free

Each month, I’m paying at a minimum $65 for these. This may seem like a steep subscription price, but these are tools I use daily, if not weekly.

A major driver of my application development is Claude Code. I find it very beneficial to have the interface right in my terminal interface while I’m developing.

Claude Code Screenshot

I can ask it questions, tell it to write code, and help me with figuring things out. It’s a very clear winner for me when it comes to development. I’ve had it write tests, generate documentation, and help me identify bugs. More importantly, it can explain why behind its output.

I’ve never had to navigate out of VS Code once and swap between tabs, which expedites my development workflow more than you’d think.

I mentioned earlier there’s trade-offs with tooling. What if I wanted to spin up a full website as part of an MVP or a prototype of an idea I have?

I could use Claude, but I’d have to worry about token consumption - it has a bias towards over-engineering projects. It also requires me to build the database locally and build the integration of 3rd party sources.

I chose Replit as my tool to take this kind of task. It takes a prompt and creates a website in a matter of minutes. You can iterate on the website, telling it to fix bugs, add new functionality, and more:

Replit screenshot

Replit also solves some of the problems I faced with Claude: over-engineering, creating a database, and integrating 3rd party API’s. Replit already has this out of the box when you create a new project. Now, I don’t have to worry if my tokens are being used to build the database connection (more tokens = $$$).

Tools I don’t use

There are some tools that I don’t use, not because they’re bad, but because they don’t necessarily fit into my workflow:

  • Copilot: This tool helps developers write code faster, very similar to Claude. I don’t use it because I view it as a duplicate to Claude and I don’t necessarily see the need to have 2 of the same tool

  • Code Rabbit: This tool accelerates the code review process. I don’t use this because I haven’t had a moment to try it out.

  • Cursor: An AI-powered IDE, similar to VS Code but with AI capabilities. I use VS Code primarily because just like Code Rabbit, I haven’t tried it out.

If you use any of these tools or use a tool that’s not mentioned here, reply to this email and share your experience with them!

Happy coding!

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