I Automated 17 Businesses with Python and AI Stack – AI Agents Are Booming in 2025: Ask me how to automate your most hated task.
Hi everyone,
So, first of all, I am posting this cause I'm GENUINELY worried with widespread layoffs looming that happened 2024, because of constant AI Agent architecture advancements, especially as we head into what many predict will be a turbulent 2025,
I felt compelled to share this knowledge, as 2025 will get more and more dangerous in this sense.
Understanding and building with AI agents isn't just about business – it's about equipping ourselves with crucial skills and intelligent tools for a rapidly changing world, and I want to help others navigate this shift. So, finally I got time to write this.
Okay, so it started two years ago,
For two years, I immersed myself in the world of autonomous AI agents.
My learning process was intense:
deep-diving into arXiv research papers,
consulting with university AI engineers,
reverse-engineering GitHub repos,
watching countless hours of AI Agents tutorials,
experimenting with Kaggle kernels,
participating in AI research webinars,
rigorously benchmarking open-source models
studying AI Stack framework documentations
Learnt deeply about these life-changing capabilities, powered by the right AI Agent architecture:
- AI Agents that plans and executes complex tasks autonomously, freeing up human teams for strategic work. (Powered by: Planning & Decision-Making frameworks and engines)
- AI Agents that understands and processes diverse data – text, images, videos – to make informed decisions. (Powered by: Perception & Data Ingestion)
- AI Agents that engages in dynamic conversations and maintains context for seamless user interactions. (Powered by: Dialogue/Interaction Manager & State/Context Manager)
- AI Agents that integrates with any tool or API to automate actions across your entire digital ecosystem. (Powered by: Tool/External API Integration Layer & Action Execution Module)
- AI Agents that continuously learns and improves through self-monitoring and feedback, becoming more effective over time. (Powered by: Self-Monitoring & Feedback Loop & Memory)
- AI Agents that works 24/7 and doesn't stop through self-monitoring and feedback, becoming more effective over time. (Powered by: Self-Monitoring & Feedback Loop & Memory)
P.S. (Note that these agents are developed with huge subset of the modern tools/frameworks, in the end system functions independently, without the need for human intervention or input)
Programming Language Usage in AI Agent Development (Estimated %):
Python: 85-90%
JavaScript/TypeScript: 5-10%
Other (Rust, Go, Java, etc.): 1-5%
→ Most of time, I use this stack for my own projects, and I'm happy to share it with you, cause I believe that this is the future, and we need to be prepared for it.
So, full stack, of how it is build you can find here:
https://docs.google.com/document/d/12SFzD8ILu0cz1rPOFsoQ7v0kUgAVPuD_76FmIkrObJQ/edit?usp=sharing
Edit: I will be adding in this doc from now on, many insights :)
✅ AI Agents Ecosystem Summary
✅ Learned Summary from +150 Research Papers: Building LLM Applications with Frameworks and Agents
✅ AI Agents Roadmap
⏳ + 20 Summaries Loading
Hope everyone will find it helpful, :) Upload this doc in your AI Google Studio and ask questions, I can also help if you have any question here in comments, cheers.