Why AI agents are making developers switch to vertical slice architecture

·1 views

A software developer has shared how working with multiple AI agents simultaneously led them to abandon traditional layered architecture in favor of vertical slice organization. In layered architecture, different agents implementing separate features like Shipping and Billing would all modify the same shared folders — controllers, services, and repositories — causing overlap and messy code reviews. Vertical slices reorganize code around features rather than technical layers, giving each agent clear ownership of a self-contained directory including its implementation and tests. This boundary means an agent can complete a feature, update its tests, and leave the rest of the codebase untouched. The developer notes that vertical slices were originally designed to improve code cohesion, but agentic development has simply reinforced their value by exposing the same coordination problems humans face.

Read the full story at DEV Community

This is an AI-generated summary. ShortSingh links to the original source for the complete article.

Discussion (0)

Deflock Casa Grande

Article URL: https://deflockcg.com/ Comments URL: https://news.ycombinator.com/item?id=49088148 Points: 5 # Comments: 0

0 comments Read more at Hacker News

ProgrammingDEV Community ·

How AI Agents Remember and Forget: The Engineering Behind Agent Memory

AI agents rely on memory systems to maintain context across interactions, as a stateless model without memory cannot pursue goals or avoid repeating mistakes. Unlike a model's context window — which acts as temporary working memory and resets with each request — real agent memory is stored externally and loaded selectively when needed. Researchers and developers typically categorize agent memory into four types: short-term working memory, long-term episodic memory, semantic memory, and procedural memory. A common production technique involves retaining recent conversation turns verbatim while summarizing older ones, keeping prompts concise without losing context. For cross-session recall, agents use vector embeddings stored in databases, enabling retrieval by semantic meaning rather than exact keywords, though this approach has limitations around recency and authority of information.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

Loop Engineering: The Framework Making AI Agents More Reliable

Developer Rijul, creator of the open-source AI code reviewer git-lrc, argues that AI agents are fundamentally built on structured feedback loops rather than sophisticated magic. Unlike traditional chatbots that rely on back-and-forth prompting, agents are designed to autonomously execute tasks by repeating cycles of action, review, and correction. A emerging concept called Loop Engineering focuses on designing these cycles deliberately, going beyond prompt engineering to include actions, feedback mechanisms, memory, and stopping conditions. For an agent to work reliably, it must know not only what to do but also how to verify results and recognize when a task is complete. Without well-defined stop conditions and feedback signals, agents risk running indefinitely without ever confirming success.

0 comments Read more at DEV Community

ProgrammingDEV Community ·

Unity developer breaks down the hidden complexity of parking puzzle game mechanics

A developer published a detailed technical breakdown on DEV Community examining the systems design behind a parking and matching puzzle game built in Unity. The article covers four core engineering challenges: valid-move detection, path resolution, match-clear logic, and scalable level authoring. The author explains how maintaining a 2D grid of cell occupancy, separate from visual transforms, keeps movement logic clean and collision-free. A deduplication system using a per-frame HashSet prevents double-triggering when multiple clear conditions fire simultaneously. The breakdown is tied to a published Unity game template called Park Match and is aimed at developers building or extending similar casual mobile puzzle games.

0 comments Read more at DEV Community