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Secure AI Agents: The Prompt Injection Trifecta

Filed Under: Secure Tagged With: Agentic AI, AI Agents, AI Security, Cybersecurity, Data Exfiltration, Hermes Agent, LLM Security, MCP, Memory Poisoning, OpenClaw, OpenHands, Prompt Injection, Sandboxing, Secure AI Agents, Tool Use

Secure Ai Agents Lethal Trifecta Feature Image

The scariest AI agent is not the one that writes a strange paragraph. It is the one that can read private data, process untrusted instructions, and send information somewhere else.

Sagas for AI Agents: Undoing What an Agent Already Did

Filed Under: Share Tagged With: Agentic AI, AI Agents, AI Safety, Autonomous Agents, Compensating Transaction, Distributed Systems, Idempotency, Multi-Agent Systems, Orchestration, Saga Pattern, Software Architecture, software engineering

A glowing AI agent whose chain of actions across systems can be walked back by amber undo-arcs when a step fails

We are racing to hand AI agents real power — agents that book travel, file expenses, edit files, move money, and deploy code, mostly on their own. The demos are dazzling. But there

Human PR Review of AI Agents: The Judgment Ratchet

Filed Under: Share Tagged With: Agentic AI, AI Coding Agents, Claude Code, Code Governance, Code Review, Design Patterns, Developer Experience, Engineering Leadership, Pull Requests, Software Architecture, Technical Debt

Human PR review of AI agents — a senior engineer steering a fleet of coding agents at the pull request boundary

When agents write most of your code, the pull request stops being a defect-catching gate and becomes something more important: the steering wheel of the entire system. The compiler

DORA Metrics for AI Coding Agents: Stop the Gaming

Filed Under: Measure Tagged With: Agentic AI, AI Coding Agents, Cost Per PR, Developer Productivity, DevOps, DORA Metrics, DX Core 4, Engineering Leadership, Engineering Metrics, Goodhart's Law, Software Delivery

Dora Metrics Ai Coding Agents Feature Image

An agentic loop that no one measures is a slot machine. It feels productive — tokens are flowing, PRs are opening, dashboards are green — but you have no idea whether the machine i

Secure Agentic Harness: The Lethal Trifecta at Fleet Scale

Filed Under: Secure Tagged With: Agentic AI, AI Coding Agents, AI Security, Claude Code, DevSecOps, Lethal Trifecta, LLM Security, MCP, Prompt Injection, Sandboxing, Supply Chain Security

Secure Agentic Coding Fleet Feature Image

When you go from one engineer running one AI agent to a fleet of code-writing agents running an enterprise loop, you haven’t just added a productivity tool. You’ve stood up a new p

Build a Claude Code Enterprise Harness

Filed Under: Create Tagged With: Agentic AI, AI Agents, AI Coding Agents, AI Software Development, Claude Code, Claude Code Hooks, Context Engineering, Developer Tools, Enterprise AI, Model Context Protocol, Subagents

A Claude Code enterprise harness assembled from agents, skills, hooks, MCP and permissions

An agent that writes code is a demo. An agent fleet you can trust on a million-line codebase is a harness — and a harness isn’t a feature you turn on. It’s a composition of primiti

The Agentic Development Loop, Explained for Engineers

Filed Under: Learn Tagged With: Agentic AI, Agentic Development Loop, AI Agents, AI Coding Agents, AI Software Development, Claude Code, Context Engineering, Developer Tools, Multi-Agent Systems, Orchestration

The agentic development loop — a closed feedback cycle of gather, act, verify feeding an orchestrator and specialist agents

If you’ve only met AI coding as autocomplete — a model finishing your line before you do — you’ve met the least interesting version of it. The agentic development loop is a differe

OpenClaw vs Hermes AI Agents: Architecture Guide

Filed Under: Learn Tagged With: Agent Frameworks, Agent Memory, Agentic AI, AI Agents, AI Architecture, AI Evaluation, AI Security, Developer Tools, Hermes Agent, LangGraph, MCP, OpenClaw, OpenHands, Self Hosted AI, Software Architecture

Self-hosted AI agent architecture comparison with gateways, memory, tools, and security

An AI agent that lives in your group chats, reads a calendar invite, opens a browser, edits a file, runs a shell command, remembers what you prefer, and reports back

What is MCP? The Protocol That Lets AI Connect to Your Apps

Filed Under: Learn Tagged With: Agentic AI, AI Agents, AI For Beginners, AI Integrations, AI Tools, Anthropic, Artificial intelligence, Automation, Brave Search, Claude AI, Claude Code, MCP, Model Context Protocol, Notion, Productivity

A luminous network of glowing nodes and connections spreading outward from a central softly pulsing orb — representing an AI

You ask Claude to draft a follow-up email to a client. Claude writes something solid — but it doesn’t know who the client is, what you last discussed, or what’s in your CRM. So you copy the context from one tab, paste it in, get the draft, copy that out, paste it somewhere else. The […]

What is Claude Code? A Plain-English Guide to Anthropic’s AI Coding Agent

Filed Under: Learn Tagged With: Agentic AI, AI Agents, AI For Beginners, AI Tools, Anthropic, Artificial intelligence, Automation, Claude AI, Claude Code, Coding Tools, Command Line, MCP, Model Context Protocol, Terminal, Vibe Coding

A glowing terminal window at night with a robot hand rearranging documents on a dark desk — representing Claude Code as an AI agent

What is Claude Code? A Plain English Guide to Anthropic’s AI Coding Agent You’ve probably used Claude to write an email, summarise a document, or talk through a problem. That’s

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