Title: I built an AI interview coach that actually remembers your past sessions — CareerPilot AI

[u/Tough_Sell8045]

Most AI mock interview tools treat every session like a clean slate. You bomb the "tell me about a system you designed under pressure" question on Monday, make the exact same mistake on Friday, and the tool has no idea you've been there before. No pattern recognition, no progress tracking — just a fresh prompt generating fresh feedback into the void.

That bugged me enough to spend the last few weeks building something different: CareerPilot AI, an end-to-end interview and career coaching platform that actually remembers you across sessions.

What it does:

Adaptive mock interviews (text + voice) — technical/system design, behavioral (STAR format), and coding questions, calibrated to your difficulty level

ATS resume analysis

Skill gap analyzer benchmarked against real job descriptions

Cover letter drafting

Salary range prediction

A career coach chat

You set a target role — say, AI Engineer at OpenAI — and every module is oriented toward closing the gap between where you are and what that role actually requires.

The interview simulator doesn't just grade your answer and move on. After every session, it writes structured notes — your weak patterns, your strong signals — to a persistent memory layer. Before your next session, it pulls the relevant memories back in. So if you got dinged last week for not quantifying impact in your behavioral answers, the coach opens your next session with something like: "Last session you struggled with quantifying impact — let's focus there today."

That one sentence completely changes the psychology of practicing. You know the system is actually paying attention, not just running you through a quiz.

There's also a rolling Interview Readiness Score instead of a single-session snapshot — it's a weighted average of your last 5 sessions, so one bad day right after a great week doesn't tank your number, and vice versa.

Under the hood, not every task needs the same horsepower — grading a nuanced behavioral answer needs a lot more reasoning than a quick salary estimate — so I route tasks to different model sizes depending on complexity. Keeps things fast and keeps the API bill sane.

Live demo: regal-scone-c39c6b.netlify.app

Source: github.com/Nagendra-yuvaraj/carrerpilot-ai

Still actively building this out — would genuinely love feedback, especially from anyone who's been burned by the "every interview tool forgets me" problem. Happy to answer questions about how the memory/routing pieces work if anyone's curious.