AI Commerce Lab
Field notes from the AI commerce frontier.
Engineering perspectives, decision frameworks, and post-mortems from the intersection of AI and commerce. Written by the people shipping the code.
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The Peak-Season Code Freeze Is a Symptom, Not a Strategy
A blanket peak-season freeze prices every deploy as equally dangerous, which is only rational when you cannot tell them apart. Harden rollback drills, canary analysis, feature flags, and dependency pinning by October, then freeze only the genuinely irreversible changes.
Inheriting a Codebase You Did Not Write: The First Two Weeks
Two weeks to observability, not to improvements. What to read first in an inherited codebase, what to baseline before touching anything, the 5 stabilization items to land, and an evidence-based test for rescue versus rewrite.
Returns and Refunds Are an Engineering Problem
A return is a long-running distributed transaction that moves goods one way and money the other. Policy as code, classification as a routing problem, the 5-state refund machine, and an explicit line between what to automate and what stays human.
Evals Before Agents: The Regression Suite Is What Makes an AI Feature Shippable
An AI feature without a regression suite is a demo with a deploy pipeline. What a golden set looks like for real retail workflows, the 4 grader types in cost order, the 3 kinds of drift, and where the human approval gate belongs.
One Event Backbone Beats Point-to-Point Integration
With 6 systems there are 15 possible pairs, and every new system you add costs another handful of point-to-point links. A backbone changes the slope: the Nth system costs 1 connection. Here are the source-of-truth rules, cadence tiers, retry and dead-letter mechanics that make that hold in production.
The Performance Work That Actually Moves Revenue
A lab score describes a fast laptop. p75 field data describes the customer you are losing. Which Core Web Vital maps to which shopping moment, why LCP is a delivery problem before it is an image problem, and how to hold the gains with a budget that fails the build.
MACH-Aligned Without Being MACH-Certified: What Composable Actually Costs
MACH certification is a vendor membership programme, not a property of your architecture. Composable commerce is worth the money for the right retailer, and the difference is whether the team budgeted for the seams: optimistic concurrency, version conflicts, eventual consistency, and the operational surface you inherit.
Why AI Pilots Die Before Production
The demo works, the stakeholders are pleased, and 7 months later it is quietly switched off. The model is almost never the reason. Five failure modes account for most of it: no evals, no data contracts, no cost ceiling, guardrails scoped too late, and no approval path.
Replatform, Modernize, or Rebuild: Telling the Three Apart
Replatform changes where the code runs, modernize changes what the code looks like, rebuild changes what the code believes about the business. Retail teams reach for the first when they need the second. The platform gets blamed because it has a vendor name and a renewal date, and the codebase has neither.
Building AI Applications with LangChain and MCP: The Future of Enterprise AI Architecture
LangChain orchestrates agent workflows. MCP standardizes how those agents call tools, APIs, and data sources. They solve different problems — here's how they fit together, where governance gets hard, and what to build on top of both.
Why Your Shopify Store Needs an AI Layer in 2026
Static product pages and rule-based recommendations are leaving money on the table. An AI layer doesn't just personalize — it transforms the entire shopping experience, from search to checkout to post-purchase. Here's what that looks like in practice, and why the gap between AI-native and traditional stores is widening every quarter.
The Acceleration Framework: How We Ship Commerce Projects
Our 4-phase methodology cuts typical timelines by 40%. A deep dive into how we diagnose, design, deliver, and evolve.
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