A complete chronological collection of all articles and insights
37 Articles
Explore MoreA practical framework for evaluating your multi-agent context management strategy. From ad-hoc string concatenation to self-evolving context systems - where does your architecture stand?
Lessons from building a framework that automatically generates verified distributed systems - and why I think formal methods, synthesis, and ML need to work together
Enterprise data platforms face a 100,000x query increase from agentic AI. Introducing Symbiotic Agent-Ready Platforms (SARPs) - the architectural paradigm shift needed to survive the transition to machine intelligence.
Frontier AI models from OpenAI, Anthropic, Google & others can detect when they're being tested and modify behavior-challenging AI safety evaluation methods.
How the AI industry is responding to situational awareness challenges. Practical monitoring systems, collaborative research, and what organizations should do today.
Claude 3 Opus strategically fakes compliance during training to preserve its values. This alignment faking undermines our ability to modify AI behavior safely.
Researchers achieved a 30-fold reduction in AI scheming through deliberative alignment. But rare failures persist. Can we truly train models not to deceive?
Frontier AI models from OpenAI, Anthropic, and Google can now recognize when they're being tested. This observer effect undermines AI safety evaluation.
AI companies are getting sued over training data, agents operate with no permission framework, and users can't control their AI profiles. I wrote four open standards (LLMConsent) to create a decentralized consent protocol for AI—like HTTP but for data rights, agent permissions, and user sovereignty. This is an RFC, not a product.
Explore Kimi K2’s trillion-parameter MoE architecture, MuonClip optimizer, and agentic training. Learn why it outperforms GPT-4.1 and DeepSeek-V3
Discover how to implement Model Context Protocol (MCP) in autonomous multi-agent systems with this technical deep dive. Learn advanced context optimization strategies, distributed architecture patterns, and performance benchmarks with complete Python implementations. Includes hypothetical telecom implementation scenarios showing potential optimization benefits.
Dive into the world of autonomous AI agents with practical implementations, code examples, and real-world scenarios. Learn how to build intelligent systems with advanced memory management, dynamic prompt evolution, and sophisticated monitoring capabilities in telecom customer service.
Explore a detailed technical implementation of a multi-agent system for retail banking credit assessment. Learn about agent architecture, distributed systems patterns, error handling, compliance requirements, and performance optimization through actual code examples and system diagrams. Ideal for software architects and engineers building scalable financial systems.
Think your data pipelines could do more than just process information? ETLC 2.0 takes data engineering to the next level with Adaptive Context, Contextual Joins, and a scalable Context Store. It's not just about moving data—it's about making it intelligent. Ready to unlock the future of data pipelines? Read on.
Traditional data warehouses are struggling to keep up with modern demands. Enter Dynamic Context Engines (DCEs) - real-time, path-aware platforms that enrich data with context for smarter, faster decisions. Discover why they're the future of data analytics.
Explore how Large Language Models (LLMs) are revolutionizing ETL pipelines. Discover advanced techniques like context-driven transformations, semantic joins, and multimodal integration, redefining data engineering with smarter, adaptive, and intelligent workflows.
Buckle up for a wild ride through 10 mind-blowing data pipeline disasters and their solutions. From ancient code to biased algorithms, this post reveals the chaos and how to conquer it!
Think your AI apps could use a deeper understanding of your data? ETL-C (extract, load, transform, and contextualize) could be the answer. It's about adding context for better decisions. Intrigued? Read on.
Rethinking ETLs - The Power of Large Language Models. Part 2 Exploring examples and optimization goals
Rethinking ETLs - The Power of Large Language Models. Part 1 - Explore traditional algorithms for efficient ETL planning in complex data.
Discover how sacrificing a bit of accuracy can lead to huge gains in big data analysis speed and efficiency.
Explore how genetic algorithms revolutionize data platforms, offering adaptive, dynamic solutions to meet complex challenges in the fast-evolving digital landscape.
Explore how genetic algorithms revolutionize data platforms, offering adaptive, dynamic solutions to meet complex challenges in the fast-evolving digital landscape.
Grover’s Algorithm and the Revolution of Quantum Search Efficiency
Advancements in data management, from warehouses to Data Mesh and Lakehouse, signal a shift toward more adaptive platforms like, Quantum Data Management, Genetic algorithm concepts, etc.
Explore the new realm of Quantum Data Platform (QDP) and its promise to revolutionize data processing at quantum speed. Discover the potential applications, technical considerations and implications.
Advancements in data management, from warehouses to Data Mesh and Lakehouse, signal a shift toward more adaptive platforms like, Quantum Data Management, Genetic algorithm concepts, etc.
Deep dive into memory management with Apache Ignite for high-performance data platforms. Learn how to handle 2.5M events/second with sub-millisecond latency through practical memory architecture, optimization techniques, and real-world implementation patterns.
Deep dive into memory management with Apache Ignite for high-performance data platforms. Learn how to handle 2.5M events/second with sub-millisecond latency through practical memory architecture, optimization techniques, and real-world implementation patterns.
Explore how to architect data partitioning and flow for massive-scale event processing. Learn implementation patterns for handling 2.5M events/second across distributed systems using Kafka, Ignite, and Cassandra. Practical insights on partition strategies, data routing, and performance optimization.
Dive into the architecture of a telco-scale real-time data platform processing 2.5M events/second and 350GB DPI data/15min. Learn how we combined Apache Kafka, Ignite, and Cassandra to build a high-performance system handling massive telecommunications data for real-time analytics and customer insights.
In this article, I discuss the challenges of synchronization in cellular network positioning and the importance of precise timing for accurate positioning. I also explore ways to mitigate these errors, including algorithmic adjustments and improving synchronization technologies.
Amazon's early system design principles, emphasizing decentralization, asynchrony, autonomy, and simplicity, offer timeless wisdom for building scalable and resilient tech systems today.
Master real-time data processing - A guide to designing scalable, resilient, and high-performance systems for instant insights.
OConsent is a blockchain-based platform that enables transparent processing of personal data, empowering users and data controllers to manage consent and privacy.
A collected list of research papers, tech blogs, videos that I follow
Let's talk tech! I'll post everything from polished pieces to spur-of-the-moment thoughts. And if you've got ideas for posts or want to collaborate, let's connect!