✨ Rabbit hole of AI analysis and solutions ✨

Over the last ten days, I found myself deep in the trenches of research and analysis, exploring the right technology fit for one of our application use cases. Like many in the tech space, I started my work with a lot of curiosity, a strong use case in hand, and a hopeful mindset that I’d be able to narrow things down with some help from AI to speed things up. But reality had a different plan. From the get-go, it was clear that choosing the right tech stack wasn’t going to be straightforward. There were edge cases. There were trade-offs. There were limitations that only surfaced once you tried running a real-world PoC. I ran into blockers. And naturally, like many of us do today, I turned to AI for help to get into some conclusion with less efforts.

ChatGPT. Copilot. Gemini. I tried them all !!!

As always ! Initially, it seemed promising — throwing ideas, generating code, offering insights. But soon enough, the same pattern: the same suggestions kept coming up, recycled in different words. I was trapped in an echo chamber of AI-generated answers. The responses were technically correct but lacked the contextual intelligence I needed. None of them could truly grasp the nuances of my use case.

🌀 It was like being caught in a loop. A polite, intelligent, well-formatted loop — but a loop nonetheless. 🌀

And that’s where the frustration set in. When you're doing deep research — especially on something that demands logical evaluation and strategic trade-offs — AI can become a rabbit hole. What begins as assistance quickly turns into a loop of over-analysis. Thousands of ideas, opinions, and statements, all sounding valid but none taking you closer to a solution. You start to lose sight of the problem you're solving. You start second-guessing yourself. And most importantly, you forget to think.

At some point, I had to call it. I closed the tabs, shut off the prompts, and just sat down with a notepad.I started writing all the important observations gathers from official documents and my POC. I gave myself the space to think like a human again. Because research isn’t just about gathering information and reading the sentenses — it’s about interpreting it, applying logic, recognizing patterns, and making judgment calls. These are deeply human tasks.

🌀 AI can assist. But it can't replace thinking. It needs that human brain power to evaluate things logically. 🌀

And so, I pivoted. I went back to first principles, revisited the core requirements, and approached the problem with fresh eyes — my own. In the end, that was the breakthrough moment. Well ! To be honest there was mostly not applicable moments, but I was able to come to a conclusion, unlike the AI.

🌀 AI is a Tool, Not a Brain 🌀

AI is powerful. It's evolving. But it's not infallible — especially in areas that require deep context, judgment, or lateral thinking. It’s a tool, not a brain.

So here’s the real question:

How far should you go with AI assistance, and where do you draw the line and start thinking for yourself?

🌀 Let that question sink in the next time you hit “Regenerate Response.” 🌀