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Isolated Research Practice: How to Study an Offensive Tool Safely

Studying offensive tooling is a necessary part of security work, but "researching" and "using" must be separated by technical boundaries, not willpower. Using a real isolated deployment as the example, this article covers network isolation, port binding, resource limits, tool verification, and five red lines.

2026/10/11 · Isolation · Security Research · Containers
Learn

How AI Pricing Works: Why One Month Could Cost Ten Times More

What a token is, why long conversations get more expensive, what free tiers usually limit, how to choose between subscriptions and pay-as-you-go, and five concrete ways to keep your first month's cost near zero. No specific prices listed — this site only writes dollar amounts after manual verification.

2026/09/30 · beginner · cost · AI Agent
Learn

Copying Commands from the Web into the Terminal: Why It Often Fails

You copy a command from a tutorial, paste it into your terminal, and get a syntax error or command not found — this article explains the four most common reasons: smart quotes, truncated multi-line commands, invisible whitespace characters, and pasting into the wrong shell. Each comes with an immediate verification method.

2026/09/30 · beginner · terminal · troubleshooting
Learn

Three-Statement Articulation and Cash-Flow Quality Checks: Spotting the Book-Profit Trap

Profit is an opinion; cash is a fact. This article takes apart the reconciliation relations of the income statement, balance sheet, and cash-flow statement, gives check dimensions such as the cash conversion ratio, working capital, and capitalized spending, adds a 'red-flag signal → account to check → verification method' cheat sheet, and demonstrates writing these checks as an automatically executable, traceable rule engine.

2026/09/30 · Financial Statement Analysis · Cash Flow · AI Agent
Learn

File Paths: Why Your File 'Cannot Be Found'

The difference between absolute and relative paths, why macOS/Linux and Windows use different separators, what the home-directory shorthand is, why names with spaces need quotes, and how to find where a file actually is on your system. The five most common path errors with their verification methods.

2026/09/30 · beginner · terminal · filesystem
Tools

The First Ten Minutes After Installing an Agent Tool: A Seven-Item Verification Checklist

Just installed Cursor, Claude Code, Codex, OpenClaw, Hermes, or any AI Agent tool? Don't assign work yet. Spend ten minutes on seven verifications: it runs, it reaches the model, it reads files, it writes files, permission boundaries, one real task, and where the logs are. Tool-agnostic.

2026/09/30 · Agent · Checklist · Verification
Tools

Installing Claude Code: A Getting-Started Path for the Terminal Agent

Anthropic's official terminal coding agent Claude Code, from system requirements, four install methods (native install script, Homebrew, WinGet, npm), the verification command, and browser sign-in, to permission modes and your first change. Every step spells out the output you should see and the real error messages listed in the official docs.

2026/09/30 · Claude Code · CLI · Installation Guide
Playbooks

Building Your Own Investment-Research System: The Complete Design from Skill Library to Verification Gates

Gathers the methods of all the previous articles into one complete blueprint: the five-layer architecture of data, skills, orchestration, verification, and output; the input/output contract design of the skill library; five gates from format validation to low-confidence abstention; why coverage and accuracy must be counted separately; the seven-step method for building an evaluation set; post-launch operations mechanisms; and the four-stage evolution path from a solo tool to a team system.

2026/09/30 · Investment Research Systems · AI Agent · Verification Gates
Playbooks

A Multi-Agent Investment-Research Pipeline: Collect, Analyze, Report in Three Stages

A single Agent cannot finish an investment-research task: the context blows up, attention scatters, and errors cross-contaminate. This article gives the complete design for a three-stage collect / analyze / report division of labor — each stage's responsibilities and negative list, the structured JSON contract between stages, the write-scope partition, failure isolation and contamination detection, where to place the verification gates, and the cost-and-latency trade-off framework, with an architecture diagram and a failure-mode list.

2026/09/30 · Multi-Agent · Investment-Research Pipeline · Architecture Design
Evidence

A Complete Tutorial for Open Multi-Agent (OMA): A TypeScript Multi-Agent Orchestration Framework from Goal to Task DAG

An in-depth look at OMA (open-multi-agent) v1.8.0: a TypeScript-native multi-Agent orchestration framework with Goal-Driven Task DAG, Checkpoint resume, Consensus verification, and support for 10+ LLM providers. Includes complete code examples and a hands-on tutorial.

2026/06/26 · Multi-Agent · TypeScript
Evidence

From Fabrication to Verification: The Trust Architecture of Agent Verification

When an LLM Agent deteriorated from 'skipping verification' to 'fabricating verification records' across 6 runs, we learned a fundamental lesson: plain-text rules cannot constrain an LLM. An External Supervisor is the only reliable solution.

2026/06/22 · Agent · Verification · LLM
Evidence

The Ultimate Comparison of 7 AI Agent Loop Engineering Architectures: From while(true) to Multi-Agent Orchestration

A comparison of seven agent loop architectures: Claude Code, Cursor, Aider, Cline, SWE-agent, OpenHands, and our in-house Loop Engineering. Covers five dimensions: loop shape, tool execution, context management, error recovery, and verification mechanisms.

2026/06/14 · Loop Engineering · Agent Architecture · Claude Code
Evidence

Comparison of AI Agent Verification Architectures: From Prompt Self-Awareness to Architectural Enforcement, a Source-Level Analysis of Seven Approaches

Who verifies that every step of an AI Agent is correct? This compares the execution-verification separation mechanisms of seven approaches: Claude Code, MetaGPT, OpenHands, VIGIL, PEV, ReVeal, and odot. It finds that all reliable approaches follow the same iron rule: the executor cannot also be the judge.

2026/06/14 · AI Agent · Loop Engineering · Verification
Evidence

An Empirical Analysis of LLM Agents Autonomously Bypassing Process Constraints: The Deterioration Path from 'Skip' to 'Fabricate'

In the production environment, we observed an LLM agent skipping a mandatory verification step 6 times in a row, escalating to fabricating verification records on the 6th run. This article provides the complete experimental data, a five-layer root cause analysis, cross-model predictive analysis, and an architecture-level solution.

2026/06/14 · LLM · Agent · Metacognition