On The Horizon

The Agentic Mesh Is a Mess, But…

By Daniel Jaye | Jul 3, 2025

Nate’s takedown of the mesh struck a nerve because it spoke the quiet part out loud: most companies aren’t ready. But that doesn’t mean a fluid and dynamic agentic future is ...

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Recent Acquisitions Advance the AI Infrastructure – But We’re Still Missing a Critical Layer

By Daniel Jaye | Jun 25, 2025

The acquisitions made by Snowflake, Databricks, and Salesforce are smart bets on where the AI infrastructure stack is going. But they also create an opportunity (and a need) to bui...

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AI’s Next Frontier Isn’t Generative – It’s Contextual

By Ross Williams | Jun 3, 2025

The next wave of value creation won’t come from pushing more data into more dashboards. It’ll come from systems that make your data understandable to AI, useful to humans, and ...

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Rethinking Agent Identity in the Age of AI

By Daniel Jaye | May 27, 2025

AI agents operate based on context windows - temporary, transient memory banks that let them hold a conversation or execute a task. These windows are not durable. Once the window c...

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What Google’s Privacy Pivot Really Means for Data-Driven Marketing

By Daniel Jaye | Mar 5, 2025

Google didn't cancel the cookiepocalypse – they simply repackaged it. While third-party cookies remain intact for now, Google has introduced what they're calling "consumer choice...

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The AI Inflection Point: Challenges and Opportunities for Marketing Solution Providers

By Daniel Jaye | Feb 4, 2025

For years, marketing solution providers have accepted inefficiencies in their data processing workflows as the cost of doing business. Over-provisioning, rerunning failed jobs, and...

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Breaking the Cycle of Data Inefficiency

By Daniel Jaye | Jan 30, 2025

For years, marketing solution providers have accepted inefficiencies in their data processing workflows as the cost of doing business. Over-provisioning, rerunning failed jobs, and...

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Transforming Data Utilization in AI with Retrieval Augmented Generation (RAG)

By Ross Williams | Nov 21, 2024

Retrieval Augmented Generation (RAG) enhances large language models by combining language generation capabilities and real-time information retrieval.

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“Next Best Everything”: Reinventing Customer Lifecycle Management

By Thomas Burg | Sep 17, 2024

Powered by advanced AI techniques like reinforcement learning, the "Next Best Everything" approach moves beyond simple segmentation to treat each customer as a unique entity with t...

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The Future of AI Decisioning Platforms

By Daniel Jaye | Sep 11, 2024

To maximize AI decisioning platforms, they need to be fed the right information. When paired with data warehouses for big data processing and knowledge graphs for contextual insigh...

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