Reading path4 stops6 stepsAbout 8 minutes of reading
Hiring a team for your site or storewhat to read before the first call.
Four short stops for anyone choosing a partner to rebuild a website or store: what is changing in commerce, how we plan a build and a migration, what the result looked like for a client, and the questions to ask any agency before you sign.
Stop 1
The problemIs a rebuild the right move right now?
Where commerce is heading and the signs that a platform has stopped scaling.
Stop 2
How we workHow do we plan it without losing sales?
The decisions and the phased plan we use so a rebuild does not cost revenue.
- 03ArticleBuild vs. Buy vs. Assemble: A Decision Framework for Engineering Leaders Past $20M ARRDecide what to build, what to buy, and what to assemble before anyone writes code.Read →
- 04ArticleRe-Platforming Ecommerce Without Losing GMV: A Phased Migration PlaybookThe phased migration we use to move a store without losing sales.Read →
Stop 3
ProofHas this team done it before?
A client result, measured before and after.
Stop 4
Before you signWhat should I ask any partner?
The questions that separate a good build partner from a risky one.
Next
Seen enough?A senior principal takes the first call.
Keep reading
Related reading
- Guide
Seven questions to ask before you sign
Seven questions that show whether a delivery partner is set up to protect your launch. Ask every vendor, including us. Written for buyers who need to defend the choice to a CEO or a board.
Read → - Industry Report
The State of E-Commerce, Mid-2026
A mid-2026 industry report on where e-commerce actually stands: the real cost of replatforming, why look and feel still sells but no longer closes, and what the agentic shopping surge means for merchants. AI-referred retail traffic grew 393% year over year in Q1 and now converts 42% better than other channels. The highest-ROI investment in retail right now is not a new storefront. It is making the storefront you have legible to machines.
Read → - Whitepaper
Starting AI Adoption: A Sequence for Mid-Market Engineering Teams
The order of operations we use with mid-market engineering teams that have been told to ship AI and do not know where to start. Six stages, named exit criteria, the anti-patterns that predict failure, and the first-90-days view that ties architecture, evaluation, and model economics into a coherent adoption sequence.
Read → - Whitepaper
Evaluation Before Shipping: How to Test an AI Application Before It Hits Production
The release-gate playbook for AI features. Covers the five evaluation dimensions, how to build a lean golden set, where LLM-as-judge is trustworthy and where it lies, rollout mechanics with named exit criteria, and the regression suite that keeps a shipped AI feature from quietly rotting in production.
Read → - Whitepaper
Choosing the Right Model (and Knowing When to Switch)
A practical framework for matching LLM model tier to task. Covers the four axes (capability, latency, cost, reliability), cascade routing patterns that cut cost 60 to 80 percent without measurable quality loss, switching costs you did not plan for, and the worked economics at 10K, 100K, and 1M decisions per day.
Read → - Whitepaper
Workflow or Agent? A Decision Framework Before You Architect Anything
Most production 'agents' are workflows that overshot. This paper distinguishes deterministic LLM pipelines from autonomous agents, names the four questions that decide which one to build, and covers the failure modes specific to each path. Includes the 'earned autonomy' principle for promoting workflows to agents only after instrumentation justifies it.
Read →
Practices
Where this leads
- Websites & commerceWebsites and stores
Designed in the browser with 3D and motion, built by our engineers, and tested on every device before launch.
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