Joe Reis: Fighting “Context” and Other Tech-Industry Hype – Episode 47

Joe Reis
When Gartner declared 2026 "The Year of Context," Joe Reis leapt into action, immediately writing a good-natured satirical article about "context products," "context lakes," and the "analyst singularity."
It's a fun article that exemplifies Joe's no-nonsense approach to industry education and concludes with a serious point — "context does matter, and most organizations are terrible at it."
We talked about:
his forthcoming data modeling book, "Mixed Model Arts"
the origins his satirical post "Gartner declares 2026 the year of context"
our speculation on how the word "context" came to the fore
how his decades of experience help him fine-tune his hype detectors
"the one equals 10 dilemma" via which leaders extrapolate AI benefits that senior programmers gain onto less-skilled engineers
the challenges that executives miss of building a semantic layer
the endless quest for "silver bullets" over solving fundamental business problems
the relevance of Einstein's definition of stupidity in the AI hype cycle
how the big AI providers are like the ISPs of the 1990s
how generative AI has accelerated and improved his workflows
the trepidation around AI that he feels when he visits Silicon Valley and San Francisco
the unprecedented pace and scale and context of the current AI hype cycle
the role of the knowledge community in the current tech environment
Joe's bio
Joe Reis, a "recovering data scientist" with 20 years in the data industry, is the co-author of the best-selling O'Reilly book, "Fundamentals of Data Engineering." He’s also the instructor for the wildly popular Data Engineering Professional Certificate on Coursera, in partnership with DeepLearning.ai and AWS.
Joe’s extensive experience encompasses data engineering, data architecture, machine learning, and more. He regularly keynotes major data conferences globally, advises and invests in innovative data product companies, writes at Practical Data Modeling and his personal blog and hosts the popular data podcast "The Joe Reis Show." In his free time, Joe is dedicated to writing new books and articles and thinking of ways to advance the data industry.
Connect with Joe online
JoeReis.xyz
Joe's writing and podcast
Gartner Declares 2026 The Year of Context™: Everything You Know Is Now a Context Product
Fundamentals of Data Engineering (O'Reilly), Joe's bestselling book
Practical Data Modeling
Personal Blog
The Joe Reis Show
Video
Here’s the video version of our conversation:
https://www.youtube.com/watch?v=6A_FWL0hbKM
Podcast intro transcript
This is the Knowledge Graph Insights podcast, episode number 47. When Gartner recently declared 2026 "The Year of Context," the gauges on Joe Reis' industry hype dashboard maxed out. Joe's a respected veteran of the data profession, known for his best-selling book, Fundamentals of Data Engineering, and for his courses, newsletters, conference keynotes — and especially for his no-nonsense takes on industry trends. He's also a good friend of the knowledge graph community. "Context" is just his latest tech-industry hype take-down.
Interview transcript
Larry:
Hi, everyone. Welcome to episode number 47 of the Knowledge Graph Insights Podcast. I am really delighted today to welcome to the show Joe Reis. Joe is a well-known figure in the data engineering and data world. He's the co-author of the book, Fundamentals of Data Engineering, which is kind of a category-setting book. He's working on a new book called Mixed Model Arts, on data modeling, and does a lot of other interesting stuff. He's really well known in the conference community. And anyhow, welcome to the show, Joe. Tell the folks a little bit more about what you're up to these days.
Joe:
Hey, what's up, Larry? What have I been up to lately? Just been editing Mixed Model Arts. I just actually finished, I guess, the main edits and just down to the very minor tweaks as of today. So that's awesome. So literally just working on that before we hopped on and I'll be working on that after we're done.
Larry:
Okay, Great. Well, sorry to interrupt your book. I'm a former book editor, so I always feel bad when I interrupt progress like that. Congrats.
Joe:
It's okay. Thank you.
Larry:
Do you have a publisher for the book?
Joe:
That would be yours truly, yes.
Larry:
All right. Okay. Well, anyhow, we'll keep the webpage-
Joe:
We'll talk about that later. Yep.
Larry:
Yeah, with info about where to get it. Well, hey, the reason this conversation came together, there was this great little convergence of meeting of ideas a couple of weeks ago. I had just done a presentation where I was talking about how hyped the AI cycle is. And then in quick succession, I saw a post from Juan Sequeda where he talked about some folks have mixed feelings about Gartner. And then I came across this post you had done, "Gartner declares 2026, the year of context." It was this brilliant satirical piece. Can you talk a little bit about that and what motivated it and just maybe a quick outline for folks?
Joe:
Yeah, I mean, I think spawned from... I guess my social media circles were like Gartner, and all of a sudden I started seeing my LinkedIn feed bombarded with the word context and how Gartner declares this the year of context and... I can swear in your show, right?
Larry:
Yeah.
Joe:
Okay, shit.
Larry:
It's fairly family friendly, but yeah.
Joe:
Yeah, it's all good. So I've seen them and similar research firms in the past declare this, that, or the other thing. And I just felt like this in particular seemed... And no offense to the knowledge graph folks there, whatever, you're all great. And I think it serves knowledge graph community really well, but the year of context I think is jumping in the gun a bit too fast. Where last year was a year of agents, year before that was year of AI or whatever, and it just seems like... It's what I described as the buzzword industrial complex where we jump... Not we, but certain groups in the industry need something new to push onto people in order to keep, I guess, discussions going, in order to keep people attending conferences, in order to keep selling consulting services and all this other stuff.
Joe:
And so I felt like this was really just another instance of it, but I decided that I had had a few spare cycles in between editing my book. So I was like, "Oh, let's just write a satirical piece on this," maybe somewhat satirical, maybe just kind of poking fun at just, I guess, the nonsense of the industry that we keep finding ourselves in over and over again. So that was all there was to it, Larry.
Larry:
Okay. Well, one of the ways you contextualize that was this, I forget what you call it, the conference content capital cycle, this self-reinforcing loop, which appeared to me to mirror this kind of whatever that bizarre financial loop that's keeping the AI companies up. Was that intentional or was I just reading into that?
Joe:
I mean, I don't know if it was intentional, but it's just an observation that I've noticed in that article, and I think a few others, where it was very much... It's a self-sustaining thing where you need the news story, you need this. And it's the same as the AI hype cycle right now where it's just a very circular system. And so just that the money just sort of rotates around and that's just kind of how it is amongst strangely a lot of the same players, which I think is kind of funny.
Larry:
Interesting. Yeah, so maybe we've just stumbled upon some universal dynamic that drives various kinds of hype cycles. But one thing that occurred to me is there's always some fundamental underlying, it's business anxiety or truth or something like that that's driving these things. The context thing, do you have any hunch where that came from? I remember it just hit my LinkedIn feed, what, three or four months ago and it's been constant ever since.
Joe:
I'll ask you this actually. I mean, let me reverse the roles of a host and guest here. I mean, you've been in the knowledge space for a while and I imagine that some manifestation of the word context has come up in your discussions with your peers. So I guess if I'm in your shoes and those of your peers, what's it like to see a word like context or semantics or ontology or graphs becoming these sort of terms du jour?
Larry:
Well, in one sense, it's really gratifying, of course, because we're on the radar screen. You can actually say ontology in public now, which has not been the case for the last 10 years.
Joe:
Yeah, you get jailed for doing that. Yeah.
Larry:
Exactly, yeah. Put you in the stocks in the middle of the courtyard. But no, so it's really interesting. And that's one of the reasons I'm curious about your take on it, because it's like there's these real things that drive it. But in terms specifically of context, I was just reminded just of... Somebody on LinkedIn today just shared a post I did recently about Dave McComb's... I don't want to get too nerdy, but this is a Knowledge Graph Insights podcast, so I'll set a little context. There's this thing in knowledge graph construction. You have the A box, the assertion box, which is like all the things, all the data instances that are in there. Then you have above that, you have the T box, which is the concepts that describe it, the ontology basically, typically.
Dave McComb, who I think you must know, because the data centric enterprise and all that.
Joe:
Mm-hmm.
Larry:
He articulated this notion, I don't know, a couple of years ago of the CBox. And what was really interesting in this post I saw today is that he used it as the categorization box. That's where you put all the taxonomic terms, vocabularies, all that sort of what I think of as the metadata about the data is sort of in there. And I didn't realize at the time,...