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Agentic Attack Tooling Research Series: A Guide to All Fourteen Parts
When attack tooling becomes AI-agent-driven, both sides of the conflict change. This is a fourteen-part deep research series: starting from a publicly attributed real-world incident, it unpacks architecture design, coordination mechanisms, and technical principles, then returns to a checklist defenders can use immediately plus isolated research practice.
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.
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.
A Source-Level Architectural Dissection of DeepSeek Harness: How an Everything-Is-a-Plugin Agent Framework Is Built
Dissecting the complete architecture of DeepSeek Harness (dsh) from 219 workspace packages and 450k lines of TypeScript: the Cordis plugin foundation, Event Sourcing session log, the three roles of capability seams, a single home for policy + fail-closed approvals, four layers of context engineering defense, and an equally plugin-based frontend. Includes a porting assessment for in-house Agent infrastructure.
Academic Research Skills Deep Technical Breakdown: How 45+ Agents Collaborate to Complete the Full Workflow from Literature Review to Peer Review
Complete technical analysis of the GitHub Trending #3 project Academic Research Skills: the architecture design of a 13-Agent research team, a 12-Agent paper writing pipeline, and a 7-Agent review panel, plus innovative mechanisms such as Socratic dialogue, integrity gates, and style calibration.
CodeGraph Deep Technical Breakdown: How to Save AI Coding Agents 35% in Costs and Cut Tool Calls by 70%
Complete technical analysis of the GitHub Trending #1 project CodeGraph: the architecture design of pre-indexed code knowledge graphs, the tree-sitter AST parsing pipeline, the MCP tool layer, performance comparison data against native Agents, and the real impact on Claude Code/Hermes Agent.
Cross-Channel Memory Hub: A Full Record of the Memory System Architecture Design for OpenClaw Agent
From daily forgetting to automatic cross-channel integration: a complete record of the architectural evolution of our AI assistant memory system, Session isolation issues, time zone boundary bugs, the three-layer protection mechanism, and the Cron automation integration pipeline.
From Zero to Launch: Agentics Website Development Retrospective and Key Lessons
A complete development retrospective on building a Next.js knowledge platform from scratch with AI Agents (our AI assistant + Claude Code): architecture design, pitfalls, key decisions, and best practices for AI-assisted development.