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Latest from AI Architecture Hub

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AI Architecture Hub

Apr 29, 2026 · Artificial Intelligence

How Subagents Keep Claude Code Context Clean

Long Claude Code sessions quickly become cluttered with every grep, find, and ls command lingering in the context, but using subagents—independent assistants that run tasks in separate windows and return only final results—keeps the context tidy; this article explains what subagents are, how to create them, built‑in options, and context‑forking techniques.

Claude CodeContext Managementai-assistants

0 likes · 8 min read

How Subagents Keep Claude Code Context Clean

AI Architecture Hub

Apr 28, 2026 · Product Management

Designing Products for AI Agents: Lessons from Salesforce Headless 360

The article examines how AI agents are becoming primary callers of software, outlines the shift from human‑centric UI design to agent‑readable actions, and details Salesforce Headless 360's multi‑mode invocation, semantic layer, lifecycle governance, scenario adaptation, and a five‑step roadmap for building agent‑friendly products.

AI AgentHeadless ArchitectureLifecycle Governance

0 likes · 15 min read

Designing Products for AI Agents: Lessons from Salesforce Headless 360

AI Architecture Hub

Apr 27, 2026 · Artificial Intelligence

Sub-Agent vs Agent Team: Choosing the Right Architecture for Complex AI Tasks

The article analyzes why many AI projects misuse multi‑agent setups, explains the fundamental differences between Sub‑Agent (isolated parallel executors) and Agent Team (collaborative teams with shared state), and provides concrete guidelines, code examples, and design principles to select the appropriate architecture for a given task.

AI AgentsAgent TeamMulti-Agent Architecture

0 likes · 10 min read

Sub-Agent vs Agent Team: Choosing the Right Architecture for Complex AI Tasks

AI Architecture Hub

Apr 26, 2026 · Artificial Intelligence

How Hermes Skills Enable Agent Self‑Evolution: Experience Engineering as the Next‑Gen Key

The article analyzes how Hermes Agent structures memory, session retrieval, and process assets into three clear layers, integrates Skills into the runtime, compares this approach with Claude Skills, Codex, and OpenClaw, and outlines security, versioning, and deployment safeguards for reliable self‑evolving agents.

AI AgentExperience EngineeringHermes Agent

0 likes · 10 min read

How Hermes Skills Enable Agent Self‑Evolution: Experience Engineering as the Next‑Gen Key

AI Architecture Hub

Apr 25, 2026 · Artificial Intelligence

When AI Agents Handle 80% of the Work, What Value Remains for Humans?

The article introduces the Compound Engineering framework and the "AI Sandwich" metaphor, arguing that humans should focus on defining problems and polishing final outputs while AI agents execute the middle tasks, and discusses how this division reshapes software engineering roles and the path toward AGI.

AGIAI AgentsAI sandwich

0 likes · 16 min read

When AI Agents Handle 80% of the Work, What Value Remains for Humans?

AI Architecture Hub

Apr 24, 2026 · Artificial Intelligence

How Claude Code Achieves a 92% Prompt Caching Hit Rate with Three Unbreakable Engineering Rules

Claude Code’s prompt‑caching delivers a 92% hit rate, slashing a 50‑round agent session cost from $6 to $1.15 by separating stable prefixes from dynamic tails, using a three‑layer cache architecture, exact token‑sequence matching, and three strict engineering rules that keep the cache hot and reliable.

Agent EngineeringCache Hit RateClaude Code

0 likes · 13 min read

How Claude Code Achieves a 92% Prompt Caching Hit Rate with Three Unbreakable Engineering Rules

AI Architecture Hub

Apr 23, 2026 · Artificial Intelligence

Why Prompt Caching Is Critical: Lessons from Building Claude Code

Prompt caching, a prefix‑matching technique that reuses prior LLM interactions, proved essential for Claude Code’s low latency and cost, and the article details counter‑intuitive practices such as arranging static prompts first, updating info via messages, avoiding mid‑session model or tool changes, and ensuring cache‑safe context forks.

AI engineeringClaude CodeLLM Agents

0 likes · 10 min read

Why Prompt Caching Is Critical: Lessons from Building Claude Code

AI Architecture Hub

Apr 22, 2026 · Artificial Intelligence

Build a Minimal AI Agent Loop in 30 Minutes and Turn It into a Stable Production System

This article walks through constructing a tiny, runnable AI agent loop that reads a user task, lets the model choose the next step, calls a tool, feeds the observation back, and repeats, then explains how to add harness, memory, permission, and validation layers to make the agent reliable in real‑world engineering environments.

AI AgentAgent LoopHarness

0 likes · 30 min read

Build a Minimal AI Agent Loop in 30 Minutes and Turn It into a Stable Production System

AI Architecture Hub

Apr 21, 2026 · Artificial Intelligence

Why Harness Architecture Turns LLMs into Production‑Ready Agents

This article explains why the Harness architecture—linking prompts, context, and runtime support—is the decisive factor that turns large language models from demo prototypes into reliable production agents, detailing its core capabilities, structural components, execution loop, design trade‑offs, and industry trends.

AI OperationsContext ManagementLLM Engineering

0 likes · 35 min read

Why Harness Architecture Turns LLMs into Production‑Ready Agents

AI Architecture Hub

Apr 20, 2026 · Artificial Intelligence

OpenClaw vs Hermes: Which AI Agent Framework Wins for Your Use Case?

This guide dissects the architectural focus, skill system, memory design, security strategy, deployment workflow, and migration path of OpenClaw and Hermes, helping developers decide which general‑purpose AI agent platform best matches their multi‑channel, self‑evolving, or governance‑heavy requirements.

AI AgentsFramework ComparisonHermes

0 likes · 19 min read

OpenClaw vs Hermes: Which AI Agent Framework Wins for Your Use Case?