Blog
Thoughts, insights, and experiences from my journey in AI, product management, and technology. Here I share what I'm learning, exploring, and thinking about in the rapidly evolving world of artificial intelligence.
📝 Recent Posts
The Art and Science of AI Product Management
Date: 2024-01-15 | Category: AI Product Management
Building AI products is different from traditional software development. It requires a unique blend of technical understanding, user empathy, and strategic thinking. In this post, I share my framework for successful AI product management...
Key takeaways:
- Understanding the AI product lifecycle from data collection to deployment
- Managing user expectations and building trust in AI systems
- Measuring success beyond traditional metrics
[Read more →]
From Prototype to Production: Scaling AI Systems
Date: 2024-01-08 | Category: Engineering & Architecture
Taking an AI model from notebook to production involves more than just deployment. It requires careful consideration of scalability, monitoring, and maintenance. Here's what I learned from scaling multiple AI systems to serve millions of users...
Technical deep dive:
- Model serving architectures and patterns
- Monitoring for model drift and performance degradation
- Cost optimization strategies for production AI
[Read more →]
The Human Side of AI: Building Trust in Intelligent Systems
Date: 2023-12-20 | Category: AI Ethics & Design
Trust is the foundation of successful AI products. Without it, even the most sophisticated algorithms will fail to gain user adoption. This post explores practical strategies for building and maintaining trust in AI systems...
Design principles covered:
- Transparency and explainability in AI interfaces
- Error handling and graceful degradation
- User feedback loops and continuous improvement
[Read more →]
🎯 Series & Collections
AI PM Fundamentals
A comprehensive series covering everything you need to know about AI product management:
- [Introduction to AI PM] - What makes AI product management unique
- [Data Strategy for AI Products] - Building and leveraging your data moat
- [Model Selection & Evaluation] - Choosing the right AI approach
- [Deployment & Monitoring] - Taking AI to production safely
- [Ethics & Responsibility] - Building AI that users can trust
Technical Tutorials
Hands-on guides for implementing AI features:
- Building RAG Systems with LangChain - Complete walkthrough from data ingestion to deployment
- Fine-tuning LLMs for Domain-Specific Tasks - Practical guide to custom model training
- Implementing Real-time AI Features - Low-latency inference patterns and optimizations
📊 Industry Analysis
2024 AI Trends: What Product Managers Need to Know
Published: January 2024
As we enter 2024, several key trends are shaping the AI landscape. Product managers need to understand these shifts to make informed decisions about their AI strategies...
Trends covered:
- Multimodal AI goes mainstream
- Edge AI and privacy-preserving ML
- AI agents and autonomous systems
- Regulatory developments and their impact
The Economics of AI: Understanding Costs and ROI
Published: December 2023**
Many organizations struggle with the financial aspects of AI implementation. This analysis breaks down the true costs of AI systems and how to measure their business value...
Key insights:
- Total cost of ownership for AI systems
- Measuring ROI beyond traditional metrics
- Strategies for cost-effective AI deployment
🛠️ Case Studies
Success Story: Improving Search with Semantic Understanding
How we transformed traditional keyword search into an intelligent, context-aware system that increased user satisfaction by 60%...
Challenges addressed:
- Vocabulary mismatch and synonym handling
- Personalization and user intent understanding
- Balancing relevance with discovery
Lessons Learned: When AI Projects Fail
Not every AI initiative succeeds. This honest look at failed projects provides valuable insights into what goes wrong and how to avoid common pitfalls...
Failure patterns analyzed:
- Data quality and availability issues
- Technical feasibility underestimation
- User adoption and trust problems
🎙️ Podcasts & Interviews
Future of AI Products (TechTalks Podcast)
Guest appearance discussing the evolution of AI in consumer products and what the future holds for AI-powered experiences.
[Listen Episode]
Building Trust in AI (Product Management Today)
Interview on practical strategies for developing AI products that users trust and love to use.
[Read Transcript]
📚 Book Reviews & Recommendations
Essential Reading for AI Product Managers
"Designing Machine Learning Systems" by Chip Huyen My take: The definitive guide to building production ML systems. Essential reading for anyone serious about AI product management.
"The AI Unicorn" by Malavika Suresh My take: Great insights into building and scaling AI startups. Real-world examples and practical frameworks.
"Power and Prediction" by Ajay Agrawal, Joshua Gans, and Avi Goldfarb My take: Economic perspective on AI's impact on business and decision-making.
📧 Subscribe to Updates
Want to stay updated with my latest posts on AI and product management? Subscribe to my newsletter for:
- Weekly insights on AI trends and developments
- Early access to new tutorials and case studies
- Exclusive content not available on the blog
- Community discussions and networking opportunities
[Subscribe Now]
🏷️ Topics I Cover
- AI Product Management - Strategy, roadmap, and execution
- Machine Learning Engineering - Technical implementation best practices
- User Experience Design - Building human-centered AI systems
- Industry Analysis - Trends, market dynamics, and future predictions
- Ethics & Responsibility - Building AI that benefits society
- Career Development - Growing in the AI and tech industry
💬 Let's Discuss
Have questions about any of the topics I've written about? Want to share your own experiences? I'd love to hear from you in the comments or connect on social media.
Subscribe to stay updated on new posts and join the conversation about the future of AI and product management.