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Domain-Driven Design for AI Coding Agents

Filed Under: Create Tagged With: Agentic Development, Agentic Loops, Aggregates, AI Coding Agents, AI Software Engineering, Anti-Corruption Layer, Bounded Context, Context Engineering, Domain-Driven Design, Hexagonal Architecture, Software Architecture, Ubiquitous Language

AI agents each working sharply inside its own clean bounded-context room, versus one agent lost in a tangled monolith

A coding agent turned loose on a tangled monolith behaves exactly like a junior who’s never seen the codebase: it guesses, it duplicates, it confidently wires the wrong things toge

MCP Server Supply Chain Security: Hardening Agent Skills

Filed Under: Secure Tagged With: Agentic Development, AI Agent Security, AI Coding Agents, DevSecOps, Least Privilege, MCP Server Security, Model Context Protocol, Prompt Injection, Sandboxing, Software Supply Chain, Supply Chain Security, Tool Poisoning

A supply-chain conveyor feeding tool crates into an AI agent, one a trojan with a hidden red payload, each gaining the agent's privileges

When you add an MCP server, install a skill, or drop in a plugin, it feels like editing a config file. It isn’t. You are installing code and instructions that run with your agent’s

A Code Review Rubric for AI-Generated Pull Requests

Filed Under: Share Tagged With: Agentic Development, AI Coding Agents, AI-Generated Code, Approval Bias, Architecture Governance, Code Quality, Code Review, Engineering Management, Pull Requests, Review Rubric, Software Architecture, Technical Debt

A structured review rubric filter catching red hidden-drift pull requests out of a stream of glossy green-approved AI PRs

Here’s the most uncomfortable software finding of 2026: reviewers feel better approving AI-generated pull requests than human ones — even though agent code carries roughly 1.7× the

Mutation Testing for AI-Generated Code (Beyond Coverage)

Filed Under: Measure Tagged With: Agentic Development, AI Coding Agents, AI-Generated Code, Code Coverage, Continuous Integration, Mutation Testing, Property-Based Testing, Quality Gates, Reward Hacking, Software Testing, Test Strategy, Test-Driven Development

A green all-passing coverage facade cracking to reveal hollow, empty tests with a code mutation slipping through untouched

Your CI dashboard says 92% coverage on the feature your agent just wrote. It feels like a safety net. It isn’t. Line coverage measures whether your tests executed a piece of code —

The Orchestrator-Worker Pattern for AI Coding Agents

Filed Under: Create Tagged With: Agent Orchestration, Agentic Development, Agentic Loops, AI Coding Agents, AI Software Engineering, Claude Agent SDK, Context Engineering, Git Worktrees, Multi-Agent Systems, Orchestrator-Worker Pattern, Subagents, Verification Loop

An orchestrator agent at the center directing specialized worker agents, each isolated in its own context bubble

Point a single AI agent at a million-line codebase and watch it slowly lose its mind. It forgets the decision it made twenty steps ago, poisons its own context window with the outp

Reading Code Is the New Superpower Skill for Engineers

Filed Under: Learn Tagged With: Agentic Development, AI Coding Agents, AI-Assisted Development, Architecture Fitness Functions, Code Review, Developer Skills, Domain-Driven Design, Hexagonal Architecture, Reading Code, Software Architecture, software engineering, SOLID Principles

An engineer reading a vast stream of code with a single path illuminated — comprehension as the new core skill in the agentic era

For decades, the fastest typist with the best memory for syntax looked like the best engineer. That era is over. When a fleet of AI agents can write more correct code in an afterno

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