Verdict

I'm going to be honest with you - and I mean actually honest, not the polished "founder story" version. For the last 6-7 months before I quit, I was working under someone I had zero respect for. Not because they were a bad person - just because I was sitting there watching decisions get made that I knew were wrong, implementing features I didn't believe in, building someone else's product with none of my own judgment applied. Every morning I'd open that Jira board and feel something die a little inside. I hate mediocrity. Not in other people - in myself. The feeling of living like you're already dead. Just going through motions. Smart colleagues. Decent salary. And absolutely zero sense that any of it would matter in 10 years. Over those 6-7 months I got obsessed with SaaS. Not because of the money fantasy. Because of something else: the idea of **building something people trust**. Something that solves a real problem for real people. Something with my name - my actual judgment - behind every decision. I wanted to build for myself, for the problem I'd actually gone through. That felt different than building for someone else's roadmap. So I quit. **What I Built** It's called **PortLume AI** \- and I'll describe it properly, not with a vague tagline. The problem I kept running into, both personally and watching people around me: **interview prep is fundamentally broken**. Everyone prepares generically. YouTube videos. Random LeetCode. A mock interview with a friend who's never even worked at the company you're targeting. You show up to a Google SDE-2 loop having practiced like it's any software job. You get destroyed. You don't even know exactly why. PortLume AI is built around one thesis: **prep that's specific beats prep that's comprehensive**. Here's everything it actually does: **Company-Specific Interview Coach** Not "here are some common interview questions." It scrapes real interview data - Glassdoor, AmbitionBox, Blind, recent Reddit threads - **in parallel**, split by round type (OA, system design, behavioral). It knows the difference between how Google interviews vs how Razorpay interviews vs how a Series B startup interviews. It researches the company, the role, recent news, and generates questions that are actually relevant to *that* interview. Big tech companies (60+ in the list) get deeper, multi-source intelligence. Everyone else gets targeted searches instead of generic filler. **Real AI Mock Interviews - That Actually Pressure You** Not a static Q&A dump. A live conversation. Five interviewer personas: friendly (patience, hints if you're stuck), standard (professional, structured), griller (FAANG-level, challenges every assumption, aggressive follow-ups), vague PM (intentionally ambiguous questions, tests how you handle ambiguity), and speed mode (rapid-fire, breadth over depth). When you answer, it doesn't just score you. It: * Analyzes your **tone** \- fillers you used, hedging language, passive voice, confidence markers * Scores your **answer structure** (STAR, depth, specificity) * Gives you **follow-up questions** the way a real interviewer would * For coding: asks you to walk through your approach, why you used it, how you'd optimize - not just "here's the correct solution" * After 8-10 exchanges, it wraps naturally and gives you a readiness score + grade **Interview Intelligence - Cross-Session Memory** This is the piece I'm most proud of technically. Every time you complete a session, the system aggregates your performance across **all** sessions - not just the latest one. It surfaces: * Your **persistent weak spots** by question type (technical vs behavioral vs system design) * Score trends over time (are you actually improving?) * Tone patterns - are you always hedging? Always too brief? * Company-level breakdown (you do fine in behavioral but collapse in system design at product companies) * A personalized improvement plan, not a generic one **Rejection Debrief - Got Rejected? Here's Exactly Why** You paste in what you remember from the interview. The rejection email if you have it (it gets sanitized before hitting AI - no PII). The stage you reached. And it: * Cross-references your actual practice sessions for that company * Identifies your weak spots from those sessions * Tells you *why you likely failed* \- not generic advice, specific diagnosis * Gives you a recovery plan with a study priority order It links your practice data to your real outcome. That's the thing no generic tool does. It closes the loop. **Adaptive Study Plan Controller** Builds you a week-by-week prep schedule based on your target company and role. But here's the part that's different: **if you fall behind, it reschedules**. It detects which topics you haven't covered and reorders them by impact. Not "you missed Tuesday, figure it out yourself." It actually adapts. SPRINT mode (tight deadline) vs MARATHON mode (6+ weeks) changes the entire structure of what you're given. **STAR Story Bank - Behavioral Prep That Uses Your Actual Experience** Reads your portfolio/resume, pulls your real work experience and projects, and generates 7 personalized STAR stories from them. Not templates. Not "tell me about a time you showed leadership" with a blank box. Each story covers a different competency (Leadership, Technical Problem Solving, Conflict, Ownership, Failure/Learning, etc.), gives you the specific interview question it answers, follow-up tips from real FAANG interviewers, and even an "improve this story" flow for specific companies or roles. It also generates practice questions that will specifically draw *that story* out of you in an interview. **Session Replay + Share** Completed a practice session? You can generate a shareable link for it. Your scores, answer feedback, tone analysis - all shareable publicly or with a mentor. Comments supported. View counts tracked. Your interview answer text is omitted by default for privacy unless you opt in. **Layoff Reboot Plan - For People Who Just Got Cut** This one came from watching friends go through layoffs and immediately start panic-applying. Week 1 of the plan is called "Stabilize - Before You Apply Anything." Because they're not ready. You input your former company, role, how many months of runway you have, target companies. It generates: * A 90-day structured reboot plan (Week 1 = emotional reset + logistics, not applications) * A severance checklist (COBRA timeline, equity/vesting cliff, non-compete clauses) * A LinkedIn reframe for the layoff period ("I'm choosing my next move" not "I got let go") * A script for networking calls when someone asks "what happened?" * Financial urgency calibration based on your actual runway And peer cohort matching - finds other engineers laid off from similar companies/roles, forms groups of up to 5, sets up a 4-week accountability structure. Because doing this alone is how people spiral. **Company Research Assistant** Deep research on the company before your interview. Recent news, what the company actually does, engineering culture, what they've been shipping. So you're never the candidate who walks in not knowing what their product does. **Where I Actually Am** 3 months since launch. 31 users. Zero paid. I made a mistake early - the app was pointed at a cluttered portfolio-style landing page. People landed and had no idea what it did. I've since rebuilt the positioning to be 100% interview prep focused. Cleaner. More honest. I've reached out personally to every single one of my 31 users. A few said they'd pay. Most didn't reply. Classic early-stage problem that I know I need to diagnose properly - is the free tier too generous? Is the value moment unclear? Am I not asking directly enough? **Why I'm Not Going Back** If this doesn't work, I'll pivot. Build something else. Try again. I have a hypothesis backlog and the ability to ship fast. But I am **not** going back to that cubicle. Not because I have something