Blog
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Why the Future of AI Isn't About Better Models—It's About Better Data Foundations
A recent Substack article, Everyone's Watching the Wrong Benchmark, argues that the AI industry is focused on the wrong competition. While much of the conversation…
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What Databricks’ $6.9 Billion Run Rate Says About the Future of AI
The AI conversation has spent the last three years focused on models. Which model is smarter? Which agent is more capable? Which copilot will transform work?
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Why DDAI Uses Fivetran Instead of Building Custom API Connectors
Last weekend, I caught up with an old friend and my co-founder from Logic Box Software, where we spent more than a decade building custom CRM systems. He has a deep…
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Your MCP Server Isn't the Solution
Every week I see another post about MCP servers being a great way to analyze business data. The promise is compelling. Connect an AI model directly to your business…
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The Modern Data Stack Landscape — And Why Midmarket Companies Still Struggle With Data
Every growing company wants to become “AI-ready.” Leadership teams want faster answers about revenue, CAC, churn, profitability, pipeline health, and cash flow. But most…
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Doomerism: Why Every Generation Thinks the End Is Near
Every generation seems convinced it is living at the edge of catastrophe. The details change, but the pattern does not. In the 1950s, it was nuclear annihilation. In the…
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From Fragmented Data to Trusted Insight: Introducing the New DDAI Professional Services Portfolio
We’re excited to introduce the new DDAI Professional Services portfolio — a structured set of services designed to help companies move from disconnected systems to a…
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Why BI Careers Are a Smart Bet in the Age of AI
There’s a growing narrative that AI will replace analysts. In reality, it’s doing something more subtle—and more impactful. AI is reducing the effort required to produce…
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AI Loves Data — But It Doesn’t Fix It
One of the core reasons AI feels like such a step change is simple: it can process massive amounts of data instantly. What used to take hours of querying, exporting, and…
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Everyone Talks About the Semantic Layer — But What Does It Actually Do?
Lately the term “semantic layer” is showing up everywhere in modern data and AI conversations. It sounds technical, important, and vaguely necessary. But for most…
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When SaaS Interfaces Disappear, Data Becomes the Product
Today, data is constantly being created and loaded into business systems like CRMs, ERPs, billing platforms, and marketing tools.
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How DDAI Turns Fragmented CRM Data into Enterprise-Grade Analytics at Scale
Modern CRMs are designed to adapt to how a business operates—not force it into a rigid structure. Custom objects and properties are features, not bugs. HubSpot…
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Decisions at the Speed of Thought
For the past decade, the modern data stack has centered on the cloud data warehouse, with platforms like Snowflake, BigQuery, and Redshift forming the foundation for…
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The Great SaaS Compression: the Shrinking Software Stack and the Rise of the Intelligence Layer
For decades, the SaaS industry has followed a predictable trajectory: more software, more tools, and more seats. At the center of the stack are platforms that store…
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RevOps Use Case Series (Part 5): Aligning Growth, Spend, and Profitability
By now, we’ve covered the foundational pillars of operational clarity.
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RevOps Use Case Series (Part 4): Pipeline Velocity and Revenue Predictability
After executive reporting, runway visibility, and unit economics are under control, the next leadership question becomes inevitable: “Can we trust our forecast — and do…
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RevOps Use Case Series (Part 3): Getting to Trustworthy Growth Economics
After reporting and runway, RevOps teams inevitably get pulled into questions about growth efficiency:
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RevOps Use Case Series (Part 2): Runway & Cash Forecasting Without Guesswork
After executive reporting, the next question RevOps teams get from leadership is almost always some version of this:
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RevOps Use Case Series (Part 1): Executive & Investor KPI Reporting Without the Fire Drill
RevOps teams are supposed to be strategic partners to leadership. In reality, they’re often stuck responding to the same high-pressure request over and over again:
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Why Most BI Projects Fail (and How to Make Yours Work)
You’ve seen this movie before. Leadership wants dashboards. RevOps wants answers. You buy a BI tool, wire up your systems, and hope it all comes together. Six weeks…
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How Mid-Sized Businesses Can Unlock Enterprise-Level Insights
Data is no longer just information—it’s the lifeblood of competitive advantage. Enterprises know this, which is why they pour millions into advanced platforms like…