🌟 Quality vs. Efficacy: Learning with AI

🦜 Enter AI

AI: tireless, structured, auto-magic, reactive, tool-dependent. Most of all, it's no more reasonable than a parrot that has mastered human speech! This little parrot might have you fooled; it’s amazing how effectively AI can mimic human interaction.

🤔 Fun fact: Did you know that despite its eloquent nature, AI can sometimes present risks in contexts like therapy and mental health? Check out this article for insights!

But what about my personal journey with AI? When ChatGPT came onto the scene while I was learning to code, I worried it would hinder my growth rather than help it. Spoiler alert: it kind of did.

💬 The Parrot Effect

I never had a mentor throughout my learning journey and was hesitant to network. I thought I could use an LLM as a surrogate mentor. However, it soon became clear that AI couldn't replace the invaluable insight a human mentor provides.

🚀 Depth vs. Scale

End-to-End Learning Challenges

Among the tech dilemmas I faced, it became apparent that advancements lead to more complex problems. With AI, understanding the challenge is more critical than superficial knowledge. Just because a computer can scale doesn’t mean it solves our problems effectively.

Let’s reflect:

"While computers scaled exponentially (thanks, Moore's Law!), the depth of their impact has expanded astronomically with AI."

To illustrate how differential scale can impact outcomes, consider this:

• 1,000,000 seconds = ~11 days (Factor of 10)
• 1,000,000,000 seconds = ~31 years (Factor of 1000)

Seems simple, right? But the depth of the difference is what counts!

🍋 Life's Lemons

🌳 To Grow a Lemon Tree

In tech, the lemons represent the SaaS world we became accustomed to, while LLMs, Agents, and MCP servers are stepping into the spotlight. AI acts as a cognitive load-balancer, taking over the mundane tasks and allowing us to focus on the creative aspects of our work.

Even with straightforward tasks that could be accomplished in mere lines of code, if there's an app or agent for it now, AI will jump in and support us. Still, I often find myself questioning whether I'm learning effectively.

So, I thought: Could I engineer Claude to assist as a mentor? What if I made it my personal AI? While some may argue that the challenge lies in how well you prompt AI, the deeper question remains—what can we realistically learn from it?

In future posts, I'll share what I learned and what I think could have been better. Stay tuned! 🚀