Writing on how decisions get modeled, built, and deployed.
LangChain, LangGraph, Claude ADK, Google ADK, PydanticAI — different names, different abstractions, same promise. This article cuts through the framework noise and identifies the five architectural properties that actually determine whether an LLM system survives production.
LLMs can extract structured data from anything — until they cannot. This article documents the failure modes of LLM-only parsing in production pipelines, and presents a layered architecture where determinism comes first and the LLM is used only where it is structurally irreplaceable.
La plupart des échecs GenAI en entreprise ne viennent pas d'un mauvais modèle. Ils viennent d'un mauvais design de workflow, d'une absence de mandat et d'une architecture incapable de faire agir un système.
Most companies are not ready for autonomous commerce agents. The practical starting point is Agentic RAG: systems that retrieve business context, reason over it, and produce decision-ready outputs.
Two initiatives can show the same ROI and still deserve very different decisions. The missing variable is time-to-ROI: how fast the initial investment is recovered.
Sales volume mixes demand and inventory effects. Sell-through rate captures what actually matters: how fast inventory clears under pricing and context constraints.
Most CRM organizations don't have a feedback loop. They have a broadcasting system. The shift from propensity to uplift modeling changes everything.
Modern LLMs are objectively better at nuanced language tasks than legacy systems. But when you zoom out from a single prompt in a playground to a production environment processing millions of requests, the paradigm shifts entirely. Here is why using an LLM as a universal parser and router is often the wrong architectural choice.
Pourquoi le forecast de lancement produit est souvent un exercice politique plus qu'une estimation robuste, et comment le transformer en système probabiliste et explicable.
Interactive tools and calculators for practitioners — built to explore ideas, not to sell software.
Available for consulting engagements in forecasting, pricing, and decision systems. More about me