SEO & AI Initiative
Brainly — Product Manager
Faced with Google’s SGE update threatening organic traffic, Brainly needed a scalable strategy to defend SEO rankings and maintain traffic acquisition.
Brainly’s organic search traffic was at serious risk due to Google’s new AI search features surfacing direct answers instead of traditional search listings.
The goal was to generate SEO-optimized topical content at scale to defend and grow Brainly’s visibility while minimizing development and operational costs.
- Led the exploration of scalable SEO content generation strategies using AI and scraping tools.
- Designed a Python-based system to orchestrate topical content creation across up to 1 million subjects.
- Built AI prompting frameworks for content generation aligned with educational standards and SEO best practices.
- Negotiated and aligned cross-functional teams (AI, Content, Product, Engineering) around a lean MVP plan, cutting proposed costs drastically.
- Supervised the web scraping and QA process to ensure topical accuracy and coverage.
- Reduced projected project costs from $300K to $15K by designing in-house MVP approach.
- Achieved 93% topical coverage and 70% QA accuracy across generated content.
- Delivered full MVP framework and initial data generation plan ahead of stakeholder deadlines.
Exploration of a Dynamic Metering System for Monetization Optimization
Brainly — Product Manager
As Brainly looked to evolve its freemium model, static access limits (e.g., fixed paywalls after X answers) created blunt user experiences and left revenue on the table.
There was a need to explore more nuanced, behavior-based metering to balance engagement and monetization.
The existing access model treated all users the same, regardless of behavior or intent — either offering too much for free or pushing away high-value users too early.
The opportunity was to design a dynamic metering system that adjusted content access thresholds based on user behavior, predicted conversion potential, and platform value delivery — increasing monetization without harming engagement.
- Conducted exploratory research on metering strategies used by subscription-based content platforms (media, edtech, productivity).
- Designed a scoring algorithm using behavioral inputs (session depth, feature usage, engagement history) to dynamically assign access thresholds.
- Proposed content gating flows (e.g., adwall, soft paywall, reward-unlock gates) tailored to user clusters.
- Used principal component analysis (PCA) and engagement signals to simulate user segmentation for prototype testing.
- Outlined experimental design for phased A/B testing, including fallback conditions and sensitivity analysis for impact on churn, engagement, and LTV.
- Delivered a full spec doc including architecture, scoring logic, threshold calibration strategy, and success metrics.
- Provided a technically and behaviorally grounded framework for adaptive monetization experimentation.
- Shifted internal thinking away from fixed thresholds toward intent-driven gating models.
- Enabled future pilots of metering strategies aligned with personalization and AI scoring tools.
- Positioned Brainly to scale monetization intelligently without compromising trust or learning outcomes.
Personal Productivity System with Gamification and Workflow Automation
Freelancer — Systems Architect
To manage ADHD-related executive function challenges and maintain sustainable productivity, I designed and implemented a modular, gamified productivity system that evolved into a fully automated behavioral tool.
Traditional productivity tools (planners, calendars, to-do apps) failed to drive consistent engagement or match fluctuating energy levels.
The opportunity was to design a self-regulating, gamified system that would make task completion intrinsically motivating — using automation to remove friction and decision fatigue.
- Designed a point-based RPG system to reward tasks based on effort, urgency, and long-term impact.
- Created task categories and streak mechanics to drive daily consistency and long-term progression.
- Automated score updates, habit tracking, and daily reset logic using Coda formulas and button-based logic.
- Developed iOS Shortcuts to push screenshots from Goodnotes directly into the system for task parsing.
- Integrated AI-assisted classification to extract tasks from notes and update the task database automatically.
- Iterated weekly challenge mechanics, status effects (energy, focus), and milestone rewards to reinforce behavior loops.
- Significantly increased consistency in task execution, especially on high-cognitive-load or ambiguous tasks.
- Reduced friction in daily planning through fully automated pipeline from notes to tasks.
- Demonstrated the ability to design closed feedback systems that drive user behavior over time.
- Built a reusable architecture for productivity gamification that mirrors user engagement frameworks in commercial products.