Ajira365 - AI Career Prep Platform
Ajira365 is the ultimate career-readiness platform designed for students and young professionals. It offers AI-powered mock interviews to help users practice and improve their interview skills. With global leaderboards, users can compete with peers and track their progress, making career preparation engaging and effective.
The Story
- •Early 2024: watched six people I cared about fail interviews at top companies
- •They had the technical skills—they just froze under pressure
- •Realized the problem wasn't knowledge; it was confidence under pressure
- •Tried offering manual interview prep, but 2 hours per person doesn't scale
- •Built an AI interviewer available 24/7 with instant, personalized feedback
- •Collaborated with 8 beta testers during development—their feedback shaped the adaptive difficulty system
- •Started with free models, upgraded to GPT-4 because quality matters for feedback
- •Ajira365 became the tool I wish I had when panicking about my own interviews
Key Features
- 187 completed mock interviews with users rating them 4.2 stars on average—that's genuine satisfaction, not pity ratings
- 42 users coming back every week, and 68% of them do a second interview. That retention means the tool is actually helping
- Average interview takes 24 minutes, and the AI adjusts difficulty on the fly based on performance. No two interviews feel the same
- Users report being 3.5x more confident in real interviews after practicing here. That's the metric that matters most
Challenges & Solutions
The Challenge
Building a realistic interview experience is harder than just throwing questions at an AI. You need to simulate pressure, adapt difficulty in real-time, and give feedback that's specific enough to improve real interview performance. The AI had to understand different roles needed different question types. Behavioral questions for PMs are useless for engineers. The system needed to be smart enough to route users appropriately while maintaining that pressure simulation throughout.
What I Learned
- •Interview simulation can't just ask questions—it needs to replicate actual pressure. That's what separates useful practice from wasted time
- •Retention isn't about features; it's about visible improvement. The 68% return rate happens because users see real gains between sessions
- •Different career paths need different questions. A behavioral interview for a PM looks nothing like a systems design interview for an engineer
- •Confidence is measurable. When users report 3.5x better performance in real interviews, that's market validation
- •Listen to frustrated users—they're goldmines. Onesmus did 20 interviews and messaged: 'I feel like there's no reward, nothing competitive.' Added leaderboards. He started checking daily to see who topped him. Other users followed the same pattern. Then added reward points (share on social → earn points → redeem for 1 month premium). Engagement exploded. Learned: gamification isn't childish when the stakes are real careers
Impact & Growth
- •Showed that AI tutoring scales. One system reaching 42 weekly users what would've taken me 84 hours of manual prep
- •Built feedback that actually helps. Instead of vague 'be more confident,' users get specific gaps to work on
- •Discovered the multiplier effect: users who interview twice close 5x more job offers. Practice compounds
- •Created a playbook for AI-powered education products that I'm now applying to other domains