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AI Step-by-Step

Sharing AI knowledge, practical implementation records, and more.

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Latest from AI Step-by-Step

39 recent articles
AI Step-by-Step
AI Step-by-Step
Apr 19, 2026 · Operations

Seamless Cross‑Domain Connections in Hermes Agent via Gateway Boundary Separation

Hermes introduces a layered Gateway architecture that cleanly separates entry points—CLI, messaging platforms, and HTTP—from the core AIAgent, enabling stable reuse across multiple channels while handling streaming adaptation, session routing, approvals, execution isolation, and deployment packaging in a unified control plane.

AgentExecution IsolationGateway
0 likes · 14 min read
Seamless Cross‑Domain Connections in Hermes Agent via Gateway Boundary Separation
AI Step-by-Step
AI Step-by-Step
Apr 14, 2026 · Artificial Intelligence

How Hermes Memory Splits Knowledge for Efficient Agent Recall

The article analyzes Hermes' memory architecture, showing how it separates user preferences, environmental facts, conversation history, and procedural skills into distinct storage layers—file‑based defaults for high‑frequency data and vector‑based augmentation for large‑scale semantic retrieval—thereby improving reliability, transparency, and maintainability of LLM agents.

AgentFile MemoryHermes
0 likes · 12 min read
How Hermes Memory Splits Knowledge for Efficient Agent Recall
AI Step-by-Step
AI Step-by-Step
Apr 12, 2026 · Backend Development

Make Agents Survive Crashes and Restarts: Building a Persistent Task Engine with Durable Execution

The article explains how durable execution, exemplified by Temporal’s Workflow and Activity model, transforms long‑running Agent tasks—such as refund approvals that involve human sign‑off, external APIs, and overnight processing—into recoverable, auditable pipelines that survive crashes, restarts, and timeouts.

ActivityAgentDurable Execution
0 likes · 16 min read
Make Agents Survive Crashes and Restarts: Building a Persistent Task Engine with Durable Execution
AI Step-by-Step
AI Step-by-Step
Apr 11, 2026 · Information Security

Beyond Prompt Guardrails: Full‑Stack Security Governance for AI Agents

The article explains how production‑grade AI agents require a full‑stack security framework—covering input sanitization, runtime policy enforcement, output verification, and audit—to mitigate ten OWASP attack surfaces such as prompt injection, tool misuse, memory poisoning, and cascading failures, with practical defense layers and red‑team testing guidance.

AI agentsLeast AgencyMemory Poisoning
0 likes · 14 min read
Beyond Prompt Guardrails: Full‑Stack Security Governance for AI Agents
AI Step-by-Step
AI Step-by-Step
Apr 10, 2026 · Artificial Intelligence

Unlock Deep Answers from LLMs with Dynamic Multi‑Expert Prompting

The article explains why single‑role prompts limit large language model depth and introduces a dynamic multi‑expert aggregation prompting method that first performs a neutral diagnosis, generates complementary experts, conducts structured debate, and aggregates results through NGT, producing comprehensive, actionable solutions for complex problems.

AI product strategyNGTPrompt Engineering
0 likes · 16 min read
Unlock Deep Answers from LLMs with Dynamic Multi‑Expert Prompting
AI Step-by-Step
AI Step-by-Step
Apr 8, 2026 · Operations

How to Light Up the Black Box of LLM Agents with Full‑Stack Observability

The article explains why traditional logs are insufficient for LLM agents, outlines five observability dimensions—tracing, metrics, behavioral governance, state & memory, and evaluation—and provides concrete, open‑source‑based steps to instrument, monitor, and act on agent workloads in production.

Behavioral GovernanceLLM agentsMetrics
0 likes · 11 min read
How to Light Up the Black Box of LLM Agents with Full‑Stack Observability
AI Step-by-Step
AI Step-by-Step
Apr 6, 2026 · Artificial Intelligence

Why Single Agents Fail: Embracing Multi‑Agent Microservice Architecture

When a single AI agent’s logic hits bottlenecks, the article explains how breaking responsibilities into bounded microservice agents, using pipelines for deterministic steps and supervisors for dynamic routing, yields clearer contracts, shared state, easier debugging, and more stable, scalable task execution.

AI architectureAgent FrameworksMulti-Agent
0 likes · 12 min read
Why Single Agents Fail: Embracing Multi‑Agent Microservice Architecture
AI Step-by-Step
AI Step-by-Step
Apr 5, 2026 · Artificial Intelligence

How Context Engineering Powers Dynamic Business Data Assembly for LLM Agents

The article explains why relying solely on handcrafted prompts leads to hallucinations in LLM agents and presents six concrete context‑engineering practices—XML isolation, hierarchical ordering, KV caching, vector reranking, async memory compression, and minimal few‑shot examples—illustrated with a full e‑commerce refund‑handling case study.

AgentLLMRAG
0 likes · 10 min read
How Context Engineering Powers Dynamic Business Data Assembly for LLM Agents
AI Step-by-Step
AI Step-by-Step
Apr 3, 2026 · Artificial Intelligence

Why Building AI Agents Requires a Full System‑Engineering Harness

The article explains that simply scaling large language models cannot sustain long‑running, production‑grade AI agents, and that a dedicated Agent Harness—acting as an operating system with orchestration, memory, governance, tool execution, and feedback loops—is essential for reliable, industrial‑scale automation.

AI agentsAgent HarnessLLM
0 likes · 9 min read
Why Building AI Agents Requires a Full System‑Engineering Harness