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The article analyzes 'katamari architecture' as a metaphor for haphazard AI-assisted software development, examining how LLM agents lead to feature bloat without proper composition, drawing parallels to the 'Big Ball of Mud' concept.
This paper presents design principles and the 'AGIMUD' software for enabling socio-affective interactions between humans and multiple AI agents in simulated dynamic worlds, leveraging generative AI and distributed processing.
A comprehensive guide to core system design building blocks, including client-server architecture, scaling, and databases, to help with system design problems and interview preparation.
This article is an engineering note that re-examines the design of coding agents from first principles, questions the impact of KV cache on current architectures, and proposes new methods for context management and decision-making.
The article expands Gary Bernhardt's 'Functional Core, Imperative Shell' architecture to 'Deterministic Core, Non-Deterministic Shell,' highlighting determinism over pure functionalism for better testability and broader applicability in software systems.
Joel Spolsky warns against over-abstraction in software design, using examples like Napster to highlight how excessive focus on architecture can neglect user needs. He critiques the hype around tech trends that prioritize abstract concepts over practical features.
This article discusses handling provider outages in AI agent systems by implementing failover, model fallback, circuit breakers, and idempotent retries to prevent pipeline stoppages and duplicate actions.
The article explores setting boundaries for AI agents in production, advocating for modular design with versioned contracts to manage coordination costs and failure isolation.
TALA, Terrastruct's AutoLayout Algorithm, is now open-source under the MPL-2.0 license and bundled with D2 v0.9.0, providing a novel approach for aesthetic software architecture diagrams.
Issue 306 of the deararchitects newsletter curates recent tech reads including the 'Agentic Enterprise' book, context engineering for production-grade AI, Spotify Engineering's Claude Code token optimization, and Netflix's ArchUnit scaling with Nebula ArchRules.
Dalek introduces a constructive agent machine that enables self-maintenance, self-evolution, self-reproduction, and self-organization on any substrate, using actors, messages, and channels with a von Neumann core for hereditary construction.
A discussion questioning the common interpretation of premature optimization in software development, referencing insights from performance expert Casey Muratori.
This article presents architectural metapatterns that generalize software architecture patterns into wider classes for local and distributed systems, illustrated with intuitive diagrams and outdated presentations.
The article explains why a CLI with 67 commands, despite being agent-friendly, fails for AI agents due to abstraction issues, and proposes a new three-layer intent model to simplify agent interaction and optimize cost management.
This article discusses the 4E framework for architectural work, focusing on the 'Evaluate' and 'Examine' steps to identify trade-offs and understand the problem holistically.
The article argues that multi-agent systems are often overused in AI applications, suggesting that a single agent with good tools, strict state, and clear stop conditions can be more efficient, easier to debug, and cost-effective for many workflows.
This article explores the limitations of Pubsub systems, focusing on challenges in distributed computing environments.
This blog post discusses the essence of architectural work, focusing on key activities and introducing the 4E framework as a minimal tool for organizing design processes while emphasizing context-dependent decision-making.
The article describes the architecture of KeplerCrew, an AI coding agent that automates output scoring before PR submission, highlighting challenges in plan sequencing, cost predictability, and air-gapped deployment.
A developer discusses the challenge of maintaining engineering discipline and architectural integrity when using AI coding agents that generate code faster than it can be comprehended, seeking best practices to avoid creating low-quality software.