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AI Tech Publishing

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

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Latest from AI Tech Publishing

90 recent articles
AI Tech Publishing
AI Tech Publishing
May 1, 2026 · Artificial Intelligence

Turning Harness into a Distributed Context Management System for Long‑Task Agents

The article explains why the reliability of long‑task agents now hinges on harness design rather than model strength, and details four harness innovations—programmatic tool calls, sub‑agents as isolation boundaries, context compression, and skill‑search priority—that Glean uses to build a distributed context management system.

Context CompressionSub‑agentsagent harness
0 likes · 11 min read
Turning Harness into a Distributed Context Management System for Long‑Task Agents
AI Tech Publishing
AI Tech Publishing
Apr 29, 2026 · Artificial Intelligence

Who Tests When AI Generates 99% of Code? Inside a Self‑Repairing Agent Harness

The article explains how a self‑repairing Agent Harness replaces traditional QA by looping evaluation, triage, automated fixing, verification and AI‑gated canary release, using a three‑judge reviewer, model‑based sampling and six daily engineering tasks to keep AI‑driven products reliable.

AI AgentsAI-driven QAAutomated Testing
0 likes · 16 min read
Who Tests When AI Generates 99% of Code? Inside a Self‑Repairing Agent Harness
AI Tech Publishing
AI Tech Publishing
Apr 29, 2026 · Artificial Intelligence

Why Do AI Agents Forget and Hallucinate? A Complete Guide to KV‑Cache Memory Mechanisms

The article explains that AI agents’ forgetting and hallucinations stem from token‑level attention scores causing key‑value cache eviction before retrieval, then surveys KV‑cache basics, naive growth, streaming‑LLM windowing, SnapKV’s attention‑guided compression, token‑retention studies, Memory Sparse Attention, compares these methods, and discusses practical system pitfalls and design implications.

AI AgentsAttentionKV Cache
0 likes · 20 min read
Why Do AI Agents Forget and Hallucinate? A Complete Guide to KV‑Cache Memory Mechanisms
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 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 designCognitive ArchitectureLLM memory
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