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RPRudrendu Paulfreecodecamp.org1d ago · 21 min read

Product Experimentation: Stop Early Without P-Hacking Using mSPRT and Sequential Testing in Python

Your AI product experiment reaches statistical significance on day 14 of a planned 30-day run, measuring a causal inference question: did the LLM-based feature genuinely improve outcomes? Every produc

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RPRudrendu Paulfreecodecamp.org3d ago · 28 min read

Product Experimentation for LLM Platforms: Switchback Designs When User Randomization Breaks Market Equilibrium in Python

Your team ships an intelligent query-routing feature for an LLM SaaS platform. The feature reads each incoming request in real time and decides whether to send it to the fast standard model or the mor

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CCausalWorldcausalworldmodel.comMay 14 · 4 min read

Causal-JEPA: A New Causal World Model for AI Agents

World models are internal simulations that let AI reason and plan about the environment [1, 2]. To work well, such models must understand objects and their interactions, not just pixels [1, 2]. Causal

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CCausalWorldcausalworldmodel.comMay 14 · 6 min read

LeWorldModel: Why AI Needs to Understand Physics to Reach Human-Level Intelligence

Large Language Models (LLMs) like OpenAI GPT systems or models from Google DeepMind and Meta have shown incredible capabilities in language, coding, reasoning, and content generation. Yet, despite the

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RPRudrendu Paulfreecodecamp.orgMay 12 · 21 min read

Product Experimentation with Synthetic Control: Causal Inference for Global LLM Rollouts in Python

Every product experimentation team doing causal inference on LLM-based features eventually hits the same wall: when the provider ships a new model version, there's no holdout. Your infrastructure team

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RPRudrendu Paulfreecodecamp.orgMay 8 · 20 min read

Product Experimentation with Regression Discontinuity: How an LLM Confidence Threshold Creates a Natural Experiment in Python

Causal inference for LLM-based features starts with one question editors ask before they ship anything: Did the change actually move the metric, or did the metric just move? Let's say that your team b

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RPRudrendu Paulfreecodecamp.orgApr 30 · 20 min read

Product Experimentation with Propensity Scores: Causal Inference for LLM-Based Features in Python

Every product experimentation team running causal inference on LLM-based features eventually hits the same wall: when users click "Try our AI assistant," the volunteers aren't a random sample. Your pr

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RPRudrendu Paulfreecodecamp.orgApr 22 · 20 min read

Product Experimentation for AI Rollouts: Why A/B Testing Breaks and How Difference-in-Differences in Python Fixes It

Your team shipped an LLM-based summaries feature to wave 1 workspaces at week 20 and now the post-launch doc is due. You need a causal effect number, a specific estimate you can defend to a statistici

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HBHafsa Benzzicausal-threads.comFeb 10 · 9 min read

Why Real-World Evidence Needs Causal Inference. Lessons from Drug Evaluation Research

By Hafsa Benzzi, MD, PhD Candidate in Clinical Research — Icahn School of Medicine at Mount Sinai Real-world evidence is reshaping how pharmaceutical companies develop drugs, how regulators evaluate them, and how clinicians prescribe them. In Decemb...

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DRDavid Rohdeml4interact.hashnode.devSep 17, 2025 · 3 min read

If You Run An Interactive System Then You Shouldn't Need To Worry About Confounding

Confounding can be defined as the presence of an unobserved (or ignored) covariate, which both determines the treatment allocation and the outcome to the treatment. An example that Ciaran M Gilligan Lee uses concerns vaccination during the COVID pand...

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Trending tags this week

Product Experimentation: Stop Early Without P-Hacking Using mSPRT and Sequential Testing in Python

Product Experimentation for LLM Platforms: Switchback Designs When User Randomization Breaks Market Equilibrium in Python

Causal-JEPA: A New Causal World Model for AI Agents

LeWorldModel: Why AI Needs to Understand Physics to Reach Human-Level Intelligence

Product Experimentation with Synthetic Control: Causal Inference for Global LLM Rollouts in Python

Product Experimentation with Regression Discontinuity: How an LLM Confidence Threshold Creates a Natural Experiment in Python

Product Experimentation with Propensity Scores: Causal Inference for LLM-Based Features in Python

Product Experimentation for AI Rollouts: Why A/B Testing Breaks and How Difference-in-Differences in Python Fixes It

Why Real-World Evidence Needs Causal Inference. Lessons from Drug Evaluation Research

If You Run An Interactive System Then You Shouldn't Need To Worry About Confounding