haradaAI Case Study
There are projects we build out of curiosity, and there are those we build because something in us refuses to stay still. haradaAI belonged to the latter. It began as an idea I saw on the Half Baked newsletter (go check it out it's great): a system that could bridge conversation and intention, not with theatrical ambition but with the precision of a tool that knew its place in the world.
Yet I will admit, when I started, I did not fully understand the magnitude of what I was trying to create.
Context
haradaAI was born from an observation: people often know what they want to say, but not how to say it in the shape the world demands. Whether it was writing emails, structuring assignments, explaining concepts, or carrying a piece of thought from one person to another, there was a gap between intention and articulation.
And being the person that I am, I wanted to close it.
So I set out to build a web-based AI assistant that didn’t pretend to be a personality, nor a sage, nor a spectacle, but a digital extension of the user’s own mind.
Approach
I began by shaping the interface as plainly as a clean sheet of paper. No theatrics. Nothing excessive. The user would enter their prompt, choose the mode they needed (explain, simplify, generate, or refine) and watch as the system responded with the restraint and discipline of a tool that actually knew its boundaries.
The architecture followed the same philosophy.
A frontend written in semantic HTML and responsive CSS, paired with fast, asynchronous JavaScript to handle streaming responses from the LLM backend. I designed the request pipeline so nothing felt sluggish. The result was an 8x8 grid.
But the true weight of haradaAI was in its ability to adapt. Not flamboyantly, not boastfully, but subtly.
It could learn the user’s preference for tone, detail, and format within each session. Everything temporary (but not if you set it to public, because then anyone can see it in the Inspiration Gallery).
Challenges
The first challenge was how to let the user move from idea to expression and to limit the friction.
The second was restraint. Preventing the system from overstepping, from adding opinion or flourish where none was needed.
And the third was reliability. A model may hallucinate, but a tool may not. So I designed guardrails: concise prompts, output checks, and a fallback system that ensured the assistant always returned something practical even when the user prompted something lackluster and vague.
But I came across the most difficult part later in development. I realized that simplicity is not the absence of complexity, but its containment. I discarded feature after feature. Stuff like history logs, persistent profiles, theme variations. And all because they weighed the system down with a kind of greed.
Outcome
haradaAI is what I envisioned it to be. Students used it to stay on top of assignments, professionals used it to refine their goal-setting skills, and friends used it to be able turn half-formed thoughts into something of substance.
In building it, I learned something that stays with me even now. When you strip a system down to its essentials, what remains is the intent. And coding, like most things in life, becomes clearer when you stop trying to impress others and start trying to understand.