I Got Tired of Losing Good AI Tools, So I Made a Curated GitHub List

A few months ago, I noticed something annoying.

Every time I found a useful AI tool, I would save it somewhere: a browser bookmark, a note, a GitHub star, a message to myself, or sometimes just a tab I promised I would come back to later.

Then, when I actually needed the tool, I could not remember where I saved it.

The AI ecosystem is moving so fast that discovery has become its own problem.

There are tools for writing, coding, research, image generation, automation, video, audio, data analysis, agents, LLM apps, business workflows, and almost everything else. That is great, but it also means that useful tools get buried quickly.

So I started organizing them.

That became Awesome AI Tools.

Repo: https://github.com/aliammari1/awesome-ai-tools

Why I built it

I did not want another random list of links.

There are already many of those.

What I wanted was a practical place where someone could say:

“I need an AI tool for this specific kind of work.”

And then quickly find a relevant section.

For example:

• tools for developers
• tools for writing
• tools for research
• tools for image and video generation
• tools for AI agents
• tools for no-code automation
• tools for business and marketing
• tools for learning AI

That is the main idea behind the repository: make AI tool discovery easier by organizing tools around use cases.

What is inside the repository?

Awesome AI Tools is a curated collection of AI tools for developers, creators, founders, students, researchers, and anyone exploring AI.

The repository currently includes 100+ tools across categories like productivity, creativity, design, code generation, AI search, large language models, agents, automation, MLOps, and learning resources.

The goal is not to say that every tool is perfect.

The goal is to create a useful starting point.

When you are exploring a fast-moving space like AI, sometimes the hardest part is not learning the tool. It is finding the right tool to try first.

Why curation still matters

AI can generate answers, summaries, and recommendations.

But curation still matters because people do not only need more information. They need better structure.

A search result can show you many tools.

A directory can show you hundreds of products.

But a curated list can help you understand the landscape.

That is why I like the “awesome list” format. It is simple, open, readable, and easy to contribute to.

You do not need to create an account.

You do not need to install anything.

You just open the repository and browse.

Who might find it useful?

If you are a developer, you can use it to discover AI coding assistants, LLM frameworks, automation tools, APIs, agent frameworks, and machine learning platforms.

If you are a creator, you can explore tools for writing, design, image generation, video editing, audio, and content creation.

If you are a student or researcher, you can look for AI search tools, summarizers, learning platforms, and research assistants.

If you are a founder or business owner, you can find tools for marketing, sales, customer support, analytics, e-commerce, and workflow automation.

I wanted the list to be useful for both technical and non-technical people.

Not everyone exploring AI is building models from scratch. Some people just want to improve their workflow.

That is completely valid.

What I learned while building it

The biggest thing I noticed is that AI is no longer one category.

It is becoming a layer across many different types of work.

A developer might use AI to write tests.

A designer might use AI to generate concepts.

A marketer might use AI to draft campaigns.

A researcher might use AI to summarize papers.

A founder might use AI to automate repetitive tasks.

These are very different workflows, but they are all part of the same larger shift.

I also noticed that many AI tools are becoming more specialized.

Instead of one tool trying to do everything, many tools are focused on one specific job. That can be powerful, but it makes discovery harder.

The more tools exist, the more useful good organization becomes.

Why I made it open source

AI changes too quickly for one person to track everything alone.

That is why the repository is open source.

If someone finds a useful tool, they can suggest it.

If a link is broken, it can be fixed.

If a category can be improved, it can be discussed.

If a better structure makes sense, the list can evolve.

That is one of the things I like most about GitHub-based resources. They do not have to be finished on day one.

They can improve with the community.

How you can use it

You can use the repository in a few simple ways:

• browse it when you need an AI tool for a task
• star it so you can come back later
• share it with someone who is exploring AI tools
• open an issue if something should be added or changed
• submit a pull request if you want to contribute directly

Here is the repository again:

https://github.com/aliammari1/awesome-ai-tools

What I want to improve next

I want to keep improving the list over time.

Some things I am thinking about:

• better short descriptions for each tool
• cleaner categories
• more open-source AI tools
• removing outdated tools
• highlighting tools with APIs
• adding more community suggestions
• possibly building a small website version later

The main goal is to keep it practical.

I do not want the repository to become a giant list that nobody can navigate. I want it to stay useful.

Final thoughts

The AI tools space is exciting, but it is also noisy.

That is why I created Awesome AI Tools.

It is a simple attempt to make AI tool discovery more organized, more open, and more useful.

If you are exploring AI tools for development, creativity, research, automation, or productivity, I hope the repository saves you some time.

Check it out here:

https://github.com/aliammari1/awesome-ai-tools

If you find it useful, a ⭐ on GitHub would mean a lot.

And if you know a great AI tool that should be included, contributions are welcome.