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Linyb Geek Road
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Linyb Geek Road

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Recent Articles

Latest from Linyb Geek Road

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Linyb Geek Road
Linyb Geek Road
Jul 27, 2026 · Artificial Intelligence

Why RAG Misses Casual User Questions and How to Optimize Retrieval

Real users ask informal, incomplete questions that often miss the right documents, so the article classifies common failure types, explains three query‑optimization techniques—Query Rewrite, Multi‑Query, and HyDE—provides concrete prompts, code snippets, selection guidelines, evaluation metrics, and practical deployment pitfalls.

HyDELLM RetrievalMulti-Query
0 likes · 14 min read
Why RAG Misses Casual User Questions and How to Optimize Retrieval
Linyb Geek Road
Linyb Geek Road
Jul 26, 2026 · Operations

From Alert Flood to Fault Insight: The Real Starting Point of AIOps

The article explains that successful AIOps begins not with sophisticated models but with turning a flood of fragmented alerts into a single, context‑rich incident view that tells operators how many failures occurred, which business services are impacted, and where they should start investigating.

AIOpsalert aggregationchange management
0 likes · 14 min read
From Alert Flood to Fault Insight: The Real Starting Point of AIOps
Linyb Geek Road
Linyb Geek Road
Jul 26, 2026 · Operations

Postmortem: How an Alert Flood Masked the Real Problem

A late‑night incident flooded the on‑call channel with dozens of red alerts, hiding the true root cause—a core service latency spike—until the team re‑ordered information, prioritized early signals, and applied a simple three‑tier alert classification to restore clarity and speed up resolution.

AIOpsIncident ResponseObservability
0 likes · 11 min read
Postmortem: How an Alert Flood Masked the Real Problem
Linyb Geek Road
Linyb Geek Road
Jul 25, 2026 · Artificial Intelligence

Why AI’s Biggest Value Is Not Speed but Redesigning Work

The author outlines four AI adoption levels—from automating routine tasks, to extending capabilities, to expanding cognitive boundaries, and finally becoming a collaborative partner that reshapes entire workflows—arguing that AI’s true value lies in redesigning work rather than merely speeding it up.

AIAI adoption levelsMicrosoft Copilot
0 likes · 7 min read
Why AI’s Biggest Value Is Not Speed but Redesigning Work
Linyb Geek Road
Linyb Geek Road
Jul 24, 2026 · Artificial Intelligence

How OpenAI’s Harness Engineering Template Enables Self‑Improving AI Code Generation

OpenAI’s internal team built a million‑line codebase in five months without a single human‑written line by using Codex agents, structuring the repository as a rule‑enforced environment, and iteratively automating testing, review, and maintenance to let AI drive the entire software development lifecycle.

AI agentsAI code generationCodex
0 likes · 13 min read
How OpenAI’s Harness Engineering Template Enables Self‑Improving AI Code Generation
Linyb Geek Road
Linyb Geek Road
Jul 24, 2026 · Artificial Intelligence

Inside Claude Code’s Harness: How Loops, Planning, Sandboxes, and Memory Power AI Programming

The article dissects Claude Code’s harness control framework, showing how a simple execution loop, planning layer, sandboxed tools, hierarchical delegation, and persistent memory—implemented with CrewAI—enable reliable AI‑driven code fixing, while highlighting trade‑offs, overhead, and future limitations.

AI agentsClaude CodeCrewAI
0 likes · 17 min read
Inside Claude Code’s Harness: How Loops, Planning, Sandboxes, and Memory Power AI Programming
Linyb Geek Road
Linyb Geek Road
Jul 23, 2026 · Artificial Intelligence

Achieving 94% AI Code Generation: How a Single Skill Automates the Entire Development Pipeline

This article details how a structured "Skill" pipeline transforms AI‑assisted coding from a flaky helper into a reliable end‑to‑end development engine, achieving a 94% code‑generation rate by breaking the workflow into eight verifiable stages, building a three‑level knowledge base, and enforcing strict red‑line rules.

AI code generationknowledge basepipeline engineering
0 likes · 34 min read
Achieving 94% AI Code Generation: How a Single Skill Automates the Entire Development Pipeline
Linyb Geek Road
Linyb Geek Road
Jul 23, 2026 · R&D Management

How Specification‑Driven Development Tames AI‑Generated Code with Three Loops and Six Human Checks

The article explains a specification‑driven development workflow that anchors AI‑generated code to a living requirements document through six closed‑loop stages—requirement authoring, clarification, code generation, cross‑compilation, download verification, and issue fixing—highlighting three iterative cycles and six human decision points that keep the process traceable and safe for industrial control projects.

AI code generationSpecification-Driven Developmenthuman-in-the-loop
0 likes · 6 min read
How Specification‑Driven Development Tames AI‑Generated Code with Three Loops and Six Human Checks
Linyb Geek Road
Linyb Geek Road
Jul 22, 2026 · Artificial Intelligence

How to Structure Specs for Complex Multi‑Agent Tasks

The article explains how to design a structured spec for complex, multi‑agent workflows by separating an orchestrator from dedicated executors, defining thin entry contracts, organizing rules, docs, and skills into distinct directories, and layering skills into orchestrator, phase, and atom levels to ensure traceability and maintainability.

AI workflowMulti-AgentRules
0 likes · 18 min read
How to Structure Specs for Complex Multi‑Agent Tasks