When Your LLM Becomes Your Twin (and Starts Judging Your Code) 🤖👀
<p><a href="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2Fpnrt7i94qvfd99vvxju3.webp" class="article-body-image-wrapper"><img src="https://media2.dev.to/dynamic/image/width=800%2Cheight=%2Cfit=scale-down%2Cgravity=auto%2Cformat=auto/https%3A%2F%2Fdev-to-uploads.s3.amazonaws.com%2Fuploads%2Farticles%2Fpnrt7i94qvfd99vvxju3.webp" alt=" " width="800" height="773"></a></p> <p>I built an LLM Twin one weekend, convinced that following a clean FTI setup would be smooth, elegant, and maybe even impressive enough to make me look like I knew what I was doing.</p> <p>First came data, which I promised would be clean but quickly turned into logs, broken CSVs, and random files I kep
I built an LLM Twin one weekend, convinced that following a clean FTI setup would be smooth, elegant, and maybe even impressive enough to make me look like I knew what I was doing.
First came data, which I promised would be clean but quickly turned into logs, broken CSVs, and random files I kept anyway because deleting them felt like admitting defeat.
Then I moved to features, skipped the heavy setup, used a vector DB, and confidently called it a “logical feature store,” hoping the name alone would carry the architecture.
Training was where things got serious, because the GPU started working harder than I ever had, and I just watched it like that was part of the plan.
Finally, I deployed it, thinking everything was ready, until the first user asked, “Why is this slow?” and suddenly all my clean design ideas became very quiet.
So I asked my LLM Twin, hoping for something helpful.
It answered:
“Because you built it that way.”
That’s when I realized I didn’t build an AI assistant.
I built a senior engineer who knows all my shortcuts… and refuses to be nice about them.
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