Dissecting the AI Hype Cycle—with Joshua Greenbaum (Enterprise Applications Consulting)
About the episode
What if AI is just the latest Blockchain?
In this episode of Futureproof, Prakash Chandran sits down with Joshua Greenbaum of Enterprise Applications Consulting to explore the AI hype cycle. Josh reflects on his 30 years of technology consulting and explains how AI is following the same trajectory as other technologies, where true value can get lost in the froth and frenzy of investors and founders trying to capitalize on it. Together, they explore the reality of whether SaaS really is dead, the criticality of standardizing data in the AI era, and the central question that all AI companies should be able to answer.
Topics covered include:
- Technology history repeats itself. While technology itself changes constantly, the way it is received in the market doesn’t. From dotcom to Blockchain, the hype cycle has a pattern.
- The hard parts of SaaS. SaaS is certainly changing, but reports of its death have been greatly exaggerated. AI that can build prototypes is far from replacing companies like Salesforce, which have learned from years of on-the-ground work with real customers and real problems.
- The importance of data standardization. The value of AI will come down to how well it can access the information it needs. Standardization of data and logic is critical to this outcome, and one that companies have to get right before they can succeed with AI.
- The lone developer. Developers aren’t going away, but developers that work in a vacuum may be. Building is a team sport even more than it was before, and the developers who can see and understand business problems are the ones that will build the future.
- The real question all AI companies need to ask. No business leader is waking up in the middle of the night thinking, “I need a large language model!” All companies, and AI companies in particular, must remain laser-focused on the actually important question: “What business problem am I solving?”
Chapters
00:00
Meet Joshua Greenbaum
Prakash introduces Josh’s background spanning three decades of enterprise technology analysis, from SAP’s R/3 launch to today’s AI wave—and why his pattern-matching is worth paying attention to.
02:10
A Career Built on Enterprise Tech
Josh traces his path from tech journalism to covering the dawn of the ERP market in Europe, landing a front-row seat to SAP’s R/3 launch and the rise of global systems integrators.
05:19
Technology Moves in Circles
A discussion on why every new platform re-creates the same cycle: new tools emerge, practitioners learn the limits, hype builds, and organizations must eventually do the hard work of change management.
08:11
The Hype Machine and Its Victims
Josh describes how financial incentives drive over-promising in every cycle—from blockchain to generative AI—and why practitioners must stay grounded while the market froths.
10:01
Is SaaS Really Dead?
They unpack why SaaS is dead is a dangerously reductive statement, exploring the decades of complexity, compliance logic, and edge-case handling baked into platforms like Salesforce and SAP that cannot be replicated overnight.
13:38
Prototypes vs. Production Reality
Josh explains why building an MVP is easy but maintaining enterprise software through compliance, regulatory changes, and global complexity is an entirely different challenge—one measured in value cycles, not hype cycles.
16:40
Why IT Projects Fail
A deep dive into the persistent 40–50% failure rate of IT projects: missing business stakeholders, technologists second-guessing practitioners, and the failure to think through end-to-end processes before building.
21:44
Speed, Change Management, and Silos
They discuss how AI’s speed actually exacerbates the problem by removing the friction that once forced methodical planning, and why enterprise silos—from data models to departmental politics—remain the deepest obstacle.
26:23
Start with the Data
Josh argues that data standardization is the non-negotiable foundation for any AI initiative, describing how projects routinely stall when teams discover their data is too inconsistent to model.
29:51
It Takes a Village, Not a Fiefdom
He makes the case for replacing the medieval city-state model of enterprise IT—where every department defends its own silo—with a cooperative village mentality that connects supply chain, sales, and customer experience.
33:48
Not Every Problem Needs an LLM
A practical look at the many flavors of AI beyond large language models—computer vision, predictive analytics, compliance engines—and a cautionary blockchain-fish parable about misapplying technology to real-world problems.
40:13
Redefining the Developer
Josh argues that the lone-wolf developer model is outdated: successful projects require cross-functional teams where architects and programmers speak the language of business, not just code.
43:41
What’s in Josh’s AI Toolbox
Josh shares his work with Basis Technologies, an LLM-powered tool that helps enterprise architects map stakeholder networks and understand business problems before writing a single line of code.
46:52
Where to Find Josh
Josh shares where listeners can connect with him and continue the conversation.
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