Built for a field that refuses to sit still

Every other engineering discipline lets you build on what you learned last year. AI does not. Models change under you, best practices flip between releases, and the patterns that matter show up in production months before they show up in any course. There is no curriculum to finish, because the curriculum is still being discovered by whoever is shipping right now.

Most AI content makes this worse. Hype, vendor pitches, and speculation age even faster than the tools they cover. Meanwhile the durable part, how AI actually behaves in front of real users, real data, and real failure modes, goes undocumented.

The only way to stay current in a field that keeps rewriting itself is to learn continuously from the people running it in production, then close the loop yourself: ship something, run it, and let what breaks teach you what no tutorial can. The AI Runtime is that loop, built as a community.

You learn from the weekly newsletter: specific, sourced production lessons on evals, agents, inference, reliability, and cost. You meet the people behind the work at the monthly Boston meetup: two practitioner talks a night, honest production stories, no slideware. And you listen to FDE Talks, the podcast on forward deployed AI engineering, with the people who take AI systems from demo to deployment.

The AI Runtime was founded by Kranthi Manchikanti, an AI Architect at Microsoft based in Boston, and it is built with the practitioners who show up.

The name is the filter. A runtime is the layer where software actually executes, and that is exactly where we focus: the production systems where AI meets real users, real data, and real failure modes. That layer is where the lessons keep their value long after the release cycle moves on.

So we deliberately skip what fills most feeds: vendor pitches, frontier-model release coverage, idea-stage products, and speculation about the future of AI. What is left is the part practitioners actually need, the operational reality of running AI in production.

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The tools will keep changing. The loop will not. The mission is a home where AI practitioners keep learning for as long as the field keeps moving: a newsletter you trust, a meetup worth the commute, a podcast from the field, expanding city by city, free and practitioner-first.

LEARN. SHIP. RUN.