01
Pinecone vs Weaviate vs Qdrant: How to Choose the Right Vector Database
Compare Pinecone, Weaviate, and Qdrant for your AI project. Learn the real performance differences, pricing, and which vector database fits your specific use case.
Sebastian Mondragon
CEO & Founder
AI System ArchitectureLarge Language ModelsRAG SystemsAI Agent DevelopmentEnterprise AI Strategy
Sebastian Mondragon
CEO & Founder
AI systems architect and founder of Particula Tech, building production-ready AI solutions for enterprises worldwide.
AI System ArchitectureLarge Language ModelsRAG SystemsAI Agent DevelopmentEnterprise AI Strategy
About
Sebastian Mondragon is the founder and CEO of Particula Tech, an AI consulting and development company that has delivered over 600 AI solutions to 450+ clients worldwide since 2023.
With deep expertise in building production-ready AI systems, Sebastian specializes in architecting solutions that handle real-world scale and complexity. His approach combines rigorous engineering discipline with practical business understanding, focusing on AI implementations that actually ship to production rather than remaining proof-of-concepts.
Before founding Particula Tech, Sebastian worked extensively on enterprise software systems, developing a strong foundation in building reliable, scalable applications. This background shapes his philosophy that AI systems need the same engineering rigor as any other production software: proper architecture, comprehensive testing, monitoring, and maintenance plans.
Sebastian writes regularly about AI development best practices, from technical deep-dives on RAG systems and AI agents to strategic guidance on when and how businesses should adopt AI. His writing reflects hands-on experience solving real problems for clients across manufacturing, professional services, healthcare, and retail industries.
Articles by Sebastian (66)
02
How to Structure Prompts for Consistent JSON Outputs from AI Models
Learn practical techniques to get reliable, parseable JSON responses from LLMs. Covers schema definition, prompt patterns, validation strategies, and error handling for production AI integrations.
03
How to Make AI Agents Remember Context Across Conversations
AI models are stateless by design. Learn practical memory architectures—from context window management to vector databases—that let agents maintain conversation history and user preferences.
04
How to Chunk Documents for RAG Without Losing Context
Context loss during document chunking kills RAG accuracy. Learn the semantic chunking strategies and overlap techniques that preserve meaning while optimizing retrieval performance.
05
Long-Running AI Tasks in UIs: Patterns That Keep Users Engaged
Learn practical UI patterns for handling AI operations that take 30 seconds to 5 minutes. Discover progress indicators, background processing, and feedback strategies that prevent user abandonment.
06
AI Team Structure: Which Roles Your Company Actually Needs
Building an AI team isn't about hiring every role on job boards. Learn which specific positions deliver value at each company stage and how to avoid the costly mistake of overhiring.