A 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?
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.
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.
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.