A conversation about pricing, the shift from software to AI, and why human intent and taste remain durable competitive advantages.
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On AI, business decisions, and building teams.
Archive
How to build a brand measurement system: a Bayesian playbook
An opinionated playbook for data science leaders: connect brand tracking, Bayesian MMM, experiments, and VARX to commercial decisions.
Sep 15, 2026
Amortized Bayesian Inference for MMM: Train Once, Reuse
Our BayesFlow webinar with Stefan Radev, explained through a marketing mix model: how amortized inference works, when it pays off, and how to validate it.
Sep 11, 2026
Daimon — From AI Experiment to Company Operating System
What changed when an AI agent moved out of private tabs and into the shared conversations where PyMC Labs actually works.
Aug 9, 2026
The 25 Most Asked Questions About Bayesian MMMs
Practical answers for marketing leaders and data scientists on building, validating, interpreting, and acting on Bayesian marketing mix models.
Aug 4, 2026
How I Verified Climate Change While Planning a Trip to Berlin
A Bayesian detour through 66 years of rain data. The model couldn’t beat the naive baseline, and proved that nothing can. The trend coefficient was the real payoff.
Jul 3, 2026
No One Said the Ferrari Luce Felt Like a Ferrari
I ran 850 synthetic interviews to test Ferrari’s electric Luce, showing how AI panels can speed concept, campaign, and website research.
Jun 16, 2026
Agentic MMM: Skills, Guardrails, and the New Job of the Data Scientist
What it takes for AI agents to build reliable marketing mix models: opinionated skills, deterministic guardrails, and a changing role for data scientists.
Jun 3, 2026
Ask Your MMM Anything: Agentic Dashboards for Marketing Mix Models
How Decision Lens lets stakeholders question marketing mix models directly, the three problems it solves, and the hard parts that remain.
May 11, 2026
Which MMM Priors Actually Matter: A Sensitivity Analysis
A sensitivity analysis across 14 prior configurations reveals which Bayesian MMM priors are inert, which remain influential, and where ROAS error persists.
May 10, 2026
What Happens When Stakeholders Can Talk to Bayesian Models?
A working agent on top of a PyMC-Marketing model shows how stakeholders can question Bayesian MMMs in plain English without routing requests through a data scientist.
May 5, 2026
The Only Two Things That Still Matter: Intent and Taste
A conversation about pricing, the shift from software to AI, and why human intent and taste remain durable competitive advantages.
Mar 31, 2026
Synthetic Buyers: Testing Products and Creatives at the Speed of Software
A summary of my SAMI talk on synthetic consumers: using LLM-simulated buyer panels to pre-screen products, creatives, and messaging before spending real money.
Mar 25, 2026
Bridging Tomorrow’s Uncertainty: Combining Chronos2 Foundational Models with PyMC-Marketing for Marketing Forecasting
How to combine foundational time series models with Bayesian Marketing Mix Models for scenario planning when future control variables do not exist yet.
Mar 17, 2026 · Published elsewhere ↗
What Do Data Teams Actually Look Like in 2026? A Large LinkedIn Benchmark
I analyzed LinkedIn data on 213 tech companies to benchmark data and AI team composition. Role mix matters more than team size.
Mar 14, 2026
I ran 25 experiments on AI brainstorming. More agents beat better prompts.
Experiments across 1 to 22 AI agents show why scaling agent diversity can matter more than better prompts for generating varied ideas.
Mar 14, 2026
Bayesian Autoresearch for Causal Inference: When You Can’t Score the Thing You Care About
Adapting Karpathy’s autoresearch to Bayesian causal modeling, where the treatment effect has no ground truth and the agent must optimize a proxy.
Mar 11, 2026
Agentic Data Science: How to Engineer Trust into Analytics and Modeling Agents
Engineering trust and reliability into AI agents for analytics and statistical modeling.
Feb 26, 2026 · Published elsewhere ↗
I Gave 24 LLMs a Personality Test. Their Answers Say More About Training Than You’d Expect.
A Big Five survey across 24 LLMs finds distinct behavioral fingerprints by model family—and shows why the statistical patterns need careful interpretation.
Feb 23, 2026
100,000 Agent Skills in 3 Months. Most of Them Are Untested.
The AI agent skills ecosystem grew explosively. Security scanning followed. But nobody is checking whether skills actually work. That’s the gap.
Feb 22, 2026
Agentic Data Science: Three Pillars of Trustworthy AI
Why shipping judgment is harder than shipping code, and three pillars for building AI agents you can trust.
Feb 18, 2026 · Published elsewhere ↗
Let Bayes tune Bayes: hyperparameter optimization for causal MMMs with Optuna
Combining Optuna’s Bayesian optimization with PyMC-Marketing and CRPS to systematically tune Media Mix Model hyperparameters, instead of guessing.
Dec 20, 2025
Synthetic Consumers & the Future of Product Testing
A conversation on how synthetic consumers are reshaping product testing and market research.
Dec 1, 2025 · Published elsewhere ↗
Can an LLM Evaluate Ad Creative?
Exploring the capabilities and limitations of AI in creative evaluation.
Nov 15, 2025 · Published elsewhere ↗
Introduction to Bayesian Thinking for Business Leaders
Why traditional statistical methods often fail in business contexts, and how Bayesian approaches can help you make better decisions under uncertainty.
Nov 12, 2025
Synthetic Consumers: The Promise, The Reality, and The Future
How LLMs are changing market research and product testing through simulated consumer behavior.
Nov 1, 2025 · Published elsewhere ↗
LLMs Reproduce Human Purchase Intent via Semantic Similarity Elicitation of Likert Ratings
A method enabling LLMs to generate realistic consumer survey responses, achieving 90% of human test-retest reliability.
Oct 9, 2025 · Published elsewhere ↗
AI Innovation Lab: Reimagining Product Innovation with Synthetic Consumers and Agentic Workflows
An end-to-end platform combining agentic workflows and synthetic consumers for every stage of product development.
Jun 3, 2025 · Published elsewhere ↗
Agentic Systems for Bayesian MMM and Consumer Testing
How two production systems use agentic AI to move Bayesian MMM and consumer testing from manual analysis toward collaborative decision-making.
Jun 1, 2025
Agents of Innovation: AI-Powered Product Ideation with Synthetic Consumer Testing
How a distributed multi-agent system enables parallel evaluation of hundreds of product concepts through synthetic consumer testing.
Apr 15, 2025 · Published elsewhere ↗
Turning Customer Feedback into Action: An LLM Blueprint
A systematic approach to analyzing app reviews at scale using large language models.
Dec 1, 2024 · Published elsewhere ↗
Bayesian Marketing Mix Models: State of the Art and Future
An overview of Bayesian marketing mix modeling at HelloFresh, including the methods that work in practice and directions for future development.
Nov 1, 2022 · Published elsewhere ↗
Rethinking Customer Lifetime Value using Machine Learning at HelloFresh
Building Morpheus, a machine learning algorithm for weekly customer-level lifetime value predictions.
Dec 7, 2020 · Published elsewhere ↗
Bayesian Media Mix Modeling using PyMC3, for Fun and Profit
How HelloFresh built a Bayesian media mix model with PyMC3 to optimize marketing spend allocation.
Aug 24, 2020 · Published elsewhere ↗
Beyond Recommendation Engines
Rethinking personalization beyond traditional recommendation systems at HelloFresh.
Jan 1, 2020 · Published elsewhere ↗
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