Agents operating on data without anything to help them causes “believable nonsense.” Data quality stops agents from misrepresenting what the warehouse contains but you need context engineering to put the right meaning, rules, and situational information in front of the model at the right moment.More
Tag Archives: data quality
222: Ashley Langford: How senior MOps practitioners are navigating the 2026 job search
Jason breaks down the 5 non-negotiables of minimum viable readiness before you deploy any AI agent, explains why the marketing ops function is becoming more critical as AI takes over execution, and argues that unbounded AI autonomy creates more risk than warehouse data ever will. He also defends GTM engineering as a real discipline rather than a rebrand, and closes with a Dune analogy.More
221: Jason Dobbs: You need Minimum Viable Readiness for AI because perfect data doesn’t exist
Jason breaks down the 5 non-negotiables of minimum viable readiness before you deploy any AI agent, explains why the marketing ops function is becoming more critical as AI takes over execution, and argues that unbounded AI autonomy creates more risk than warehouse data ever will. He also defends GTM engineering as a real discipline rather than a rebrand, and closes with a Dune analogy.More
203: Jordan Resnick: How to distinguish fake traffic from real machine customers
Distinguishing fake traffic from real machine customers requires reading behavior. Jordan shows how AI-driven bots now scroll, click, and submit forms while inflating dashboards with activity that never converts. The signal lives in speed, sequencing, and follow-through. Teams that act protect the conversion point, block synthetic demand early, and report only after traffic earns trust.More
191: Aboli Gangreddiwar: Self healing data agents, hivemind memory curators and living documentation
Aboli and Phil explore AI agent use cases like self-healing data quality agents, AI hivemind memory curator, documentation agents and AI browsers and a bunch more!More
190: Henk-jan ter Brugge: The Head of Martech at Philips thinks martech has outgrown marketing and it’s time we lead like pirates
Henk-jan works like a pirate inside the navy, exposing inefficiency with data, redesigning roles around real capabilities, and breaking AI promises into measurable wins backed by clean data and clear standards. He treats composability as an operating model with budgets tied to usage, gives local teams autonomy within guardrails, and measures martech by how it serves people and drives revenue.More
179: Tiankai Feng: The comeback of data quality and how NLP is changing the data analyst role
Data governance feels like the Jedi Council, steady with its rules, while marketing ops moves like the Rebel Alliance, quick to adapt when perfect data never arrives. Tiankai believes progress comes from blending discipline with curiosity, bringing data in early as a partner, not a critic.More
174: Joshua Kanter: A 4-time CMO on the case against data democratization
Joshua spent the earliest parts of his career buried in SQL, only to watch companies hand out dashboards and call it strategy. Teams skim charts to confirm hunches while ignoring what the data actually says. He believes access means nothing without translation. You need people who can turn vague business prompts into clear, interpretable answers.More
142: Lourenço Mello: Snowflake’s Product Marketing Lead on the marketing data stack of the future
Lourenço drops us straight into the gravity well of martech, where Snowflake’s latest report pulls in the tools that really matter, letting the fluff float away. It’s all about data gravity, bringing the applications to the data instead of wasting energy shuttling data around. This shift is redefining what’s possible, streamlining operations, and giving marketers a new superpower to harness the forces of AI and analytics.More
116: Kevin Hu: How data observability and anomaly detection can enhance MOps
Dr. Kevin Hu gives us a masterclass on everything data. Data analysis, data storytelling, data quality, data observability and data anomaly detection. We unpack the importance of balancing data perfection with actually doing the work of activating that data. He highlights data observability and anomaly detection as a key to preempting errors, ensuring data integrity for a seamless user experience. More