Legacy-First Design: Designing Software That Survives Time
Most software systems are designed with one implicit assumption:someone will always be there to main...
Modern software architecture is remarkably good at solving today’s problems. It is far less effective at surviving tomorrow.
DREAM: Scalable Episodic Memory Architecture A user-centric memory protocol designed to overcome the context window limits of LLMs. It introduces Episodic Units (EUs) and an Adaptive Retention Mechanism (ARM) that dynamically adjusts memory longevity based on user engagement. The architecture utilizes sharded orchestration and dual-output processing to ensure low latency, cost efficiency, and privacy-first data management.
MQ-AGI: Modular Quantum-Orchestrated AI A neuro-symbolic architecture designed to transcend monolithic LLMs. It integrates Domain Expert Networks (DENs) with a Global Integrator (GIN) to enable deep "System 2" reasoning. The system features a Quantum-Inspired Core that uses Hamiltonian optimization for efficient expert routing and incorporates the DREAM protocol for persistent, adaptive episodic memory.
Most software systems are designed with one implicit assumption:someone will always be there to main...
Most software systems don’t fail because of bugs. They fail because of invisible dependency.Con...
The Hidden Problem Nobody Talks About: Memory That Never ForgetsMost AI systems today suffer from th...
Neal Ford, Mark Richards, Pramod Sadalage, Zhamak Dehghani
Software Architecture: The Hard Parts focuses on the complex decision-making required for distributed systems, emphasizing that there are no universal 'best practices,' only trade-offs. The authors provide a practical framework for analyzing difficult architectural decisions such as service granularity, data ownership, and workflow orchestration helping architects navigate the critical balance between static coupling and dynamic forces in modern microservices architectures.
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Mark Richards, Neal Ford
Fundamentals of Software Architecture serves as a comprehensive guide for aspiring and practicing architects, defining the role not just by technical depth, but by breadth and trade-off analysis. The authors introduce the 'First Law of Software Architecture' everything is a trade-off and provide a structured approach to identifying architectural characteristics (the '-ilities'), architectural patterns, and component modularity. It bridges the gap between coding and high-level structure, offering a framework to make objective decisions in an industry often driven by subjectivity.
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Andrew Harmel-Law
Facilitating Software Architecture redefines the modern architect not as a top-down decision maker, but as a collaborative facilitator who empowers teams to own their architectural choices. Recognizing that complex systems move too fast for a single "ivory tower" architect, Andrew Harmel-Law introduces the Architectural Advice Process (AAP) a framework for decentralizing decision-making while maintaining alignment. It is essentially a guide on how to stop doing all the architecture yourself and start coaching your teams to build it effectively.
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Len Bass, Paul Clements, Rick Kazman
Software Architecture in Practice establishes the definitive framework for linking technical decisions to business goals. Written by researchers from the SEI (Software Engineering Institute), it argues that architecture is primarily driven by Quality Attributes (like performance, security, and modifiability) rather than just functional requirements. The book provides rigorous, proven methodologies such as the ATAM (Architecture Tradeoff Analysis Method) for evaluating whether an architecture can actually support the necessary business drivers before a single line of code is written.
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