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AI Tech Publishing

In the fast-evolving AI era, we thoroughly explain stable technical foundations.

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Recent Articles

Latest from AI Tech Publishing

77 recent articles
AI Tech Publishing
AI Tech Publishing
Apr 27, 2026 · Artificial Intelligence

Why Build Your Own AI Evaluation Harness? 7 OpenAI‑Inspired Recommendations

The article explains why generic AI testing platforms fall short, outlines how to design a testable AI system from day one, and presents seven practical recommendations—from using Codex or Claude Code to manage regression and iteration test sets, to leveraging entropy diagnostics and custom domain‑expert UX.

AI evaluationEvaluation FrameworkOpenAI
0 likes · 8 min read
Why Build Your Own AI Evaluation Harness? 7 OpenAI‑Inspired Recommendations
AI Tech Publishing
AI Tech Publishing
Apr 27, 2026 · Artificial Intelligence

Context Window Strategies in Agent Harnesses: Pi, OpenClaw, Claude Code, Letta, Alyx

The article analyzes how five Agent Harness frameworks—Pi, OpenClaw, Claude Code, Letta, and Alyx—handle context windows, file pagination, tool result limits, session pruning, and sub‑agent isolation, revealing convergent design patterns that treat the context as a managed memory system.

Agent HarnessContext ManagementFile Pagination
0 likes · 21 min read
Context Window Strategies in Agent Harnesses: Pi, OpenClaw, Claude Code, Letta, Alyx
AI Tech Publishing
AI Tech Publishing
Apr 25, 2026 · Artificial Intelligence

A Comprehensive Guide to Harness Engineering for Reliable AI Agents

This article systematically breaks down Harness Engineering—a framework that organizes large models, context, tools, state, sandboxing, security, and evaluation into a reliable AI agent engineering system, showing how to move agents from demo to production.

AI agentsContext ManagementHarness Engineering
0 likes · 21 min read
A Comprehensive Guide to Harness Engineering for Reliable AI Agents
AI Tech Publishing
AI Tech Publishing
Apr 22, 2026 · Artificial Intelligence

Why Longer Context Makes LLMs Forget Faster: 7 Failure Modes and Memory System Solutions

The article analyzes how extending the context window of large language models leads to rapid forgetting, outlines seven concrete failure modes, examines cognitive‑science‑based memory architectures, and walks through practical layers—from Python lists to markdown files to vector retrieval—highlighting why simple context expansion alone cannot solve the problem.

Agent designLLM Memorycognitive architecture
0 likes · 10 min read
Why Longer Context Makes LLMs Forget Faster: 7 Failure Modes and Memory System Solutions
AI Tech Publishing
AI Tech Publishing
Apr 21, 2026 · Artificial Intelligence

Why Your AI Agent Stays a Toy: Six Production‑Readiness Gaps and How to Bridge Them

Moving an AI agent from a controlled demo to an unattended production environment introduces six critical gaps—fault handling, state persistence, observability, credential security, cost control, and human supervision—each requiring specific infrastructure, practices, and a comprehensive readiness checklist to avoid costly failures.

AI agentsCost managementfault tolerance
0 likes · 15 min read
Why Your AI Agent Stays a Toy: Six Production‑Readiness Gaps and How to Bridge Them
AI Tech Publishing
AI Tech Publishing
Apr 20, 2026 · Artificial Intelligence

How Claude Code Achieves 92% Prompt Cache Hit Rate and Cuts Costs by 81% – A Deep Dive

This article explains the mechanics of prompt‑caching for large language models, breaks down static versus dynamic context, details KV‑cache operation and its pricing, and shows how Claude Code’s 30‑minute programming session reached a 92% cache hit rate that reduced inference costs by 81%, concluding with three production‑grade design rules.

AI agentsAnthropic APIClaude Code
0 likes · 13 min read
How Claude Code Achieves 92% Prompt Cache Hit Rate and Cuts Costs by 81% – A Deep Dive
AI Tech Publishing
AI Tech Publishing
Apr 19, 2026 · Industry Insights

AI Will Replace Programmers? Why You Should Stay Calm

Amid widespread claims that AI will replace programmers, the article argues that current AI demos are limited to simple apps, while real software engineering requires deep problem definition, architecture design, and operational judgment—skills AI cannot replicate, making programmers' cognitive expertise more valuable than ever.

AIAutomationcognitive skills
0 likes · 7 min read
AI Will Replace Programmers? Why You Should Stay Calm
AI Tech Publishing
AI Tech Publishing
Apr 19, 2026 · Artificial Intelligence

How to Build Production‑Ready Agent HITL: State Machines, Event Sourcing, and Distributed Coordination

The article presents a detailed engineering guide for deploying production‑grade AI agents with Human‑in‑the‑Loop, covering a three‑layer decoupled architecture, tool‑level and hook‑level interception, a six‑state session state machine with event sourcing, robust timeout handling using CAS, and cross‑node coordination for multi‑agent workflows.

AgentDistributed CoordinationEvent Sourcing
0 likes · 17 min read
How to Build Production‑Ready Agent HITL: State Machines, Event Sourcing, and Distributed Coordination
AI Tech Publishing
AI Tech Publishing
Apr 17, 2026 · Artificial Intelligence

Why Your AI Agent Crashes: 7 Hosting Patterns Compared

The article explains why AI agents fail when deployed with the wrong hosting model, presents a systematic comparison of seven patterns—Cron, Reactive, Daemon, Pipeline, Service, Adaptive, and Mesh—detailing their problem scope, typical scenarios, concrete Python or TypeScript implementations, when to choose each, and the trade‑offs, while warning against the common mistake of over‑engineering from the start.

AI agentsadaptive schedulingcron
0 likes · 21 min read
Why Your AI Agent Crashes: 7 Hosting Patterns Compared