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Native MCP integration: bringing real tools into your agent workflow
MCP connects agents to docs, databases, APIs, and internal tools—so they act on real sources of truth instead of guesswork.
MCPAI AgentsIntegration
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Agent hooks: automate the small things you always forget
Event-driven hooks (like on file save) can run docs/tests/formatting automatically—keeping your PRs merge-ready.
AutomationAI AgentsTesting
2 min read
Steering files and context management: teaching agents your “house style”
Steering helps you define rules, style, and workflows so agents follow your team’s conventions instead of inventing their own.
AI AgentsContextWorkflow
2 min read
EARS notation: writing requirements so AI doesn’t guess
EARS turns fuzzy ideas into testable requirements—especially useful when you rely on agents to implement features.
RequirementsEARSAI Agents
3 min read
Kiro and Spec-Driven Development: from vibe coding to viable code
Kiro turns prompts into EARS-style requirements, designs, and task plans—helping you move from “ideas” to shippable, verifiable code.
AI AgentsSpec-DrivenProductivity
4 min read
Securing LLMs and Autonomous Agents in Production
As agents dynamically execute code and freely access databases, cybersecurity paradigms must adapt drastically. An exploration of prompt injection, data exfiltration, and sandboxing architecture in 2026.
SecurityAI AgenticCybersecurity