AI Coding Tool Breakdown: AI Copilots vs AI Coding Assistants vs AI Software Engineers

AI Coding Tools need to be SORTED: AI Copilots vs AI Coding Assistants vs AI Software Engineers
🌟 In this video, we break down the three essential categories of AI tools that every AI engineer needs to know: AI Copilots, AI coding assistants, and AI software engineers. Learn the differences, capabilities, and why these tools are revolutionizing the way we code.
🛠️ We discuss the power of 'tier 1' AI Copilots like GitHub Copilot and Supermaven, and see how they boost productivity with intelligent autocomplete features. Move up to 'tier 2' AI coding assistants like Cursor, Aider, and Continue, which take coding assistance to a whole new level with advanced capabilities. Finally, we briefly discuss the future with 'tier 3' AI software engineers like Devon and Copilot Workspace, and understand their potential to transform the coding landscape.
🔥 Watch as we demonstrate practical examples and high-level features of these tools, from basic autocompletes to advanced coding prompts. See how tools like Cursor's Copilot++ can streamline your workflow, making you a more efficient and effective coder.
💡 Whether you're a seasoned AI engineer or just starting with AI coding, this video is packed with insights and actionable tips to help you stay ahead of the curve. Don't miss out on the future of coding-embrace these tools and supercharge your productivity!
👍 If you found this video helpful, make sure to hit the like button and subscribe for more content on AI coding, AI engineering, and the latest advancements in generative AI tools. Stay tuned for more exciting updates and tutorials to elevate your coding.
🔥 Previous AI CODING video
• ALL ROADS LEAD to AI C...
🔗 Resources
- github copilot github.com/features/copilot
- aider aider.chat/
- cursor cursor.sh/
- bun bun.sh/
- opendevin github.com/OpenDevin/OpenDevin
- continue www.continue.dev/
📖 Chapters
00:00 AI Copilots, Coding Assistants, and Software Engineers
00:35 Understanding AI Tool Capabilities
01:15 AI Coding Tools
03:35 Key Features of AI Copilots
05:00 Key Features of AI Coding Assistants
12:08 AI Software Engineers are NOT there yet
13:00 Recommendations for AI Coding Tools
#aicoding #agentic #llm

[@konstantinrebrov675]

I'm not a senior developer. I am just starting in my programming career. Everyone else on my team is a Master or PHD, and I am a Bachelor. I don't know as much as my team mates, I'm not as experiences as they are. But using these autocoding tools I can perform at the same level, or at least come close to that. I will not be a burden for my team, but a productive member, just as everyone else. And this helps me shrink the experience gap between myself and my team members who have been coding since I was in middle school.

[@RickySupriyadi]

this content is a content made by top tier generalist analyzer (sorry if I came up with my own term) I have seen several video this channel made and it is really so good. this kind visualization help me with dyslexia, it is common for dyslexic like me having a bit of trouble doing visualization imagination for such structured informations. Thank you. I really hope you continue doing this style.

[@TechnologySquaredLLC]

Same issues can be found within our company. A large percentage of software engineers are known to suffer from dyslexia. We alter our ide tools and products with this in mind quite often. Keep coding.

[@RickySupriyadi]

@@TechnologySquaredLLC thank you for your kind words.

[@techfren]

Let's goo! Love this subject ❤🔥🤝 keep the good videos coming

[@veslavaia]

Really very good explanation! Thanks

[@DanielWeikert]

A major problem might be that currently a lot of companies will not allow to use them internally. You got different experiences?

[@indydevdan]

I see a mixed bag, some allowing others not. It won't matter soon, it will be like adopting remove work vs not. Those that adopt it get more talent and get more done. Those using AI Coding Assistants get more talent and get more done. Same Same.

[@Squick99]

Thanks for posting these! As soon as I heard of the idea of these coding assistants and the more advanced AI Software Engineers like Copilot Workspace I knew things would change. I've always wondered how much the OpenAI bill ends up being for running these. I do a lot with LLMs in a very different context, where my inputs can be ~3k tokens and the output just a single token; so my costs are easy to predict. But with things like Aider sending entire files, and receiving often a hundred lines back, what's been your experience with real-world API costs? Of course the productivity gains dwarf that cost, but are you seeing $10/day, or 10x that?

[@AXYZE]

Which would be better now, Cursor or Continue?

[@jmirodg7094]

Do you have suggestions for open-sources versions ad except Aider all your suggestions are closed source code

[@mrd6869]

My question is why are these tools not mature yet?
Is it how they are trained or they cant reason fully?
Also what if you applied machine learning & RAG to something like this and gave
it access to a huge code repository...could it self improve?
If they can run autonomous military drones and self driving cars semi accurately...why not general code engineering?

[@yellowboat8773]

Not mature? Bruh, this space is moving at light speed, only last year we started using LLM day to day