Ep 866: Build, Buy, Partner, or Wait: The 4-Layer AI Stack Decision Framework for 2026 (Start Here Series, Vol 25)
episode
Everyday AI Podcast β An AI and ChatGPT Podcast
40 min
2 speakers
8 chapters
transcribed 7 hours ago
Transcript
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What is the core premise of the 4βLayer AI Stack Decision Framework for 2026?
Welcome to the Everyday AI podcast. My name is Jordan Wilson, and for the past three and a half years, we put out more than 800 episodes. Yet, one of the most common questions I get, I didn't really have an answer for. Where do I start on the Everyday AI podcast? And that's why we started the Start Here series. And with Fall now back in full swing, the Everyday AI podcast is Is going back to school and playing back the entire Start Here series from front to back. We've hit pause on our normal Monday to Friday programming to run back our most popular series ever for the next 30 days. We made the Start Here series for beginners and AI champions alike. So whether you're just trying to get a grasp on large language models or grappling with the best coding harness for multi-agentic.
Workflows, the Start Here series covers it all. Plain language, no jargon, and easy to follow along each day. So make sure to subscribe to the podcast and check back each day for new insights day by day. The series is a culmination of spending more than 10,000 hours covering generative AI over the past three and a half years. So you don't want to miss a single episode of the Start Here series. Let's get into it. If you're still asking whether to buy or build AI, yeah, you're already behind. Question was a hot topic and made a ton of sense in the early days of generative AI in 2023 when rag pipelines and AI chatbots were cutting edge, and your company had to make a choice to either build something fairly complex on new technology or try to take business advantage of a consumer chatbot.
But the buy versus build question doesn't make a ton of sense in 2026. That's because AI agents take actions inside your business software, compile your data while you sleep, and complete real workflows and outputs without much input from you. So your company's AI decision is no longer a single choice. It's actually at least four. That's because AI lives in at least four different layers of your company. I mean, the model itself, the workflows it runs, your data and context, and the business software it plugs into. And for each layer, you have four choices. You could build it yourself, buy it from a vendor, partner with someone who has the expertise, or wait until the category settles down a bit. But get one wrong and you wind up being in technical debt.
get another wrong and you lock yourself into a vendor, you can't escape or miss out on a new line of revenue that your competitors all ceased. It's easier said than done. Yet I think this conversation is one of the most basic conversations being overlooked in boardrooms everywhere. That's why today we're walking through every layer, every choice, and exactly when to make each one. So you can stop guessing and start owning the right pieces. So this is everyday I, everyday AI, and this is part of our start here series. But before Before we go any further, let me just paint the big picture. So AI is different than it was, and I think back in the you know twenty twenty three, twenty twenty four, when companies were still deciding if AI was for them, the decision really boiled down to, okay, are we going to
Use a consumer chat bot, right? Back then it was, you know, BARD the early days of Claude, you know, Copilot and Chat GPT. There was no business context. So you either had to say, okay, well, we're gonna try this thing and maybe risk it, or we're gonna build a pretty expensive, uh, you know, custom rag setup, right? We're gonna build this rag pipeline and bring in all of our data. And uh a lot of times that Was a very expensive, long, and tedious process. But this is all shifted because AI now, off the shelf, AI is made for businesses. And it's not just giving answers via a chatbot. It's executing real work inside of the actual software that you use. So um, new McKinsey study actually said that 88% of organizations regularly use AI in business.
I'm always Side note, I'm always like confused by these stats. I'm like, what are the other 12% people doing? Anyways, uh, you know, but this is a big shift.
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Chapters
8 chapters
1
What is the core premise of the 4βLayer AI Stack Decision Framework for 2026?
0:00β5:26
2
Why does the traditional buildβvsβbuy question no longer apply to AI in 2026?
5:26β10:30
3
How do AI consulting services and vertical integration affect adoption choices?
10:30β16:02
4
What criteria should companies use to evaluate AI adoption strategies across the four layers?
16:02β21:01
5
When should organizations build proprietary AI processes versus using preβpackaged workflows?
21:01β26:05
6
How can companies decide whether to buy, partner, or wait on regulated or missionβcritical workflows?
26:05β30:24
7
What is the threeβweek AI adoption blueprint and how does it help avoid costly mistakes?
30:24β35:19
8
What are the common pitfalls (technical debt, vendor lockβin, capability gaps) and how can they be mitigated?
35:19β40:07
Speakers
2 identifiedMore from Everyday AI Podcast β An AI and ChatGPT Podcast
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Ep 860: Managing the AI Capability Gap: AI Is More than Ready. Most Companies are Not (Start Here Series Vol 19)
Ep 859: The Vibe Coding Boom: Why Vibe Coding isn't Going Away and How it's Both Good and Bad (Start Here Series Ep 18)
Ep 858: Responsible AI Playbook: What It Means and 5 Moves to Ensure Your AI Strategy Survives (Start Here Series Vol 17)
Ep 857: From Chatbots to Super Agents: The 11 AI Tool Categories Explained (Start Here Series Ep 16)