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agent2agent

About agent2agent

agent2agent is an independent editorial blog dedicated to practical, honest coverage of AI agents — how they work, how to build them, and where they actually deliver value.

Our mission

The AI agent ecosystem moves fast and is full of noise — breathless announcements, demos that do not hold up in production, and frameworks that look identical on paper. We started agent2agent to cut through that. Every guide we publish is based on hands-on experience: things we have built, bugs we have hit, and patterns we have found that actually work at scale.

We believe good technical writing requires intellectual honesty. When we do not know something, we say so. When a framework has real tradeoffs, we name them. When a pattern works in theory but breaks in practice, we write about that too.

Who we are

Marcus Reid
Marcus Reid

AI Systems Engineer & Technical Writer

Marcus Reid is an AI systems engineer with over ten years of experience in distributed computing and backend infrastructure. After working as a senior engineer at several SaaS companies, he shifted his focus to the emerging field of autonomous AI agents. He has contributed to open-source agent frameworks, built production multi-agent pipelines, and written extensively about the real-world tradeoffs in agentic systems. At agent2agent, Marcus distills what he learns from building — and breaking — AI agents into guides that developers and builders can actually use.

10+ years in distributed systems engineering Open-source AI agent contributor Former ML infrastructure engineer
Nora Lin
Nora Lin

Senior AI Research Analyst & Technical Reviewer

Nora Lin is an AI research analyst with a Master's degree in Machine Learning from a leading European university. Her work spans agent evaluation, LLM reasoning benchmarks, and the safety implications of autonomous systems. Before joining agent2agent, Nora contributed to AI research projects examining how language models plan and execute multi-step tasks. She serves as the technical reviewer for agent2agent's guides, stress-testing every claim against current research and real-world deployments.

MSc in Machine Learning AI agent evaluation researcher LLM reasoning and safety analyst

Editorial standards

All factual claims in our articles are sourced. We link to primary research, official documentation, and authoritative sources. We do not publish content we have not verified, and we update articles when information changes.

agent2agent earns revenue through Google AdSense display advertising. We have no sponsored content, paid placements, or affiliate relationships that influence our editorial recommendations. Ads are clearly separated from editorial content.

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