If you haven’t yet read my post about how I first dove into AI and built my foundation, you might want to start there. It tells how I studied, got certified, and began to understand core concepts. In this post, I am picking up where that left off and sharing how I shifted from learning AI to living with AI by seeking out an ongoing resource that gives the big picture.

The Limits of Slack Snippets

At work, we created an AI discussion channel. At first, it was just links to articles from newsletters. Over time, others joined in, mostly sharing coding tools, small news, and one off updates. Those contributions were useful, but they felt fragmented and gave me only pieces of what AI was doing. What I needed was something more cohesive, something that showed how the parts connect.

That realization pushed me to look for something different: a resource that would let me see AI not as isolated bits of news, but as a field shifting in real time that included tools, research, business, policy, and infrastructure.

Discovering Last Week in AI

I cannot pinpoint exactly how I found Last Week in AI. It was probably a YouTube search for AI topics. Once I tried an episode or two, I knew this was what I was looking for. Every week the podcast, hosted by Andrey Kurenkov and Jeremie Harris, brings a wide angle view of AI: tools and apps, business applications, open source projects, new research, and policy and safety questions.

To give you a sense of what one episode might cover:

• Tools & Apps — for example OpenAI upgrading Codex or Google integrating Gemini into Chrome
• Applications & Business — deals and acquisitions, robotaxi developments, AI firms raising huge rounds
• Projects & Open Source — new benchmarks for long context models or efficient reasoning
• Research & Advancements — work like embodied foundation models or physics based models
• Policy & Safety — AI safety bills, lawsuits about AI copyright, industry regulation

It covers all of those in a single episode. It is not a podcast that only focuses on small updates or generative AI. It works hard to capture the whole scope.

Binging the Evolution (Feb 2023 to Now)

Once I knew it was worth following, I decided I wanted the full story behind it. The podcast rebooted in February 2023 with episode 110, so I started there. Over the course of about a month, I listened to every subsequent episode until I was caught up to the present.

That binge gave me something I did not have before: a sense of how AI has evolved, how trends have emerged, who has been pushing boundaries, and how quickly new advances take hold. It helped me see how today’s breakthroughs link to the past and how the field keeps accelerating.

I am not going to unpack all of those insights in this post. I plan to re-listen and dig into individual themes later. The important point here is that the binge itself reshaped how I see AI’s trajectory.

Not for Everyone (And That Is Okay)

I want to be clear: Last Week in AI is not a light listen. Episodes are long, usually an hour and a half to one hour forty five minutes, and the conversation can get technical. That level of depth might be too dense for some listeners. It is not designed for casual consumption.

For me, it was the perfect fit. I wanted detail, nuance, and connection across the field. Still, if you would prefer a podcast that is more digestible, I have one I will recommend in my next post.

Moving from Fragments to Continuity

Because of this podcast, I have moved from collecting scattered AI updates to having a continuous and informed perspective. It is now a resource I rely on to understand not just what is happening now but how we got here and where we may be heading.

In upcoming posts, I will dig into the themes I discovered: trends, standout research, company moves, infrastructure, and more. For now, finding this kind of consistent and context rich resource feels like the essential next step in my AI journey.