The AI team on headless commerce
You went headless for control. The agents fit that decision: changes arrive as commits through your CI, the edge is a managed surface, and everything is auditable.
Headless setups trade platform convenience for control — and inherit the obligation to do everything themselves: rendering discipline, structured data, performance budgets, SEO correctness. The agents slot into that world natively. Builder ships as reviewable commits through your git workflow; Ops treats Cloudflare as a first-class surface; Visibility verifies that what the crawler receives matches what you meant to render — the failure class headless is notorious for.
Changes as commits, not admin clicks
On a headless build the deploy pipeline is the store. The agents respect that completely.
Builder: page and component changes as branch commits, through your review and CI
Rendering verification: what crawlers and AI engines actually receive, checked continuously
Structured data and metadata correctness at the rendered layer, not the source
Ops: cache rules, edge functions, and real-user performance per route
The headless failure class: render vs. crawl
The classic headless regression is invisible: a hydration change, and suddenly product metadata renders only client-side and half your structured data vanishes from the crawled page. Visibility diffs rendered output against expectation continuously, so that class of regression is caught at the deploy that caused it — not in next quarter’s traffic report.
Commerce data stays decoupled
Whether the backend is Shopify, BigCommerce, or a custom service, catalogue and order data flow to the agents independently of the front end — Analyst and Retention work identically while Builder works through the repo. The decoupling you chose is the decoupling the agents use.
How it works
Connect repo, edge, and data
Git workflow, Cloudflare, GA4, and the commerce backend — each agent gets its native surface.
Baseline rendering and speed
Rendered-output correctness and real-user performance per route become tracked baselines.
Work through the pipeline
Changes flow as reviewable commits; regressions are flagged against the deploy that introduced them.
What you get
Agent changes that pass through the same CI as human ones
Render-layer SEO regressions caught at the causing deploy
Edge configuration managed per route with a recorded baseline
Full audit trail alongside your existing git history
Frequently asked questions
Which frameworks does it work with?
The workflow is framework-agnostic — it operates through git, the rendered output, and the edge, so Next.js, Astro, Nuxt, Remix, and custom stacks all present the same surfaces.
Can agent commits be reviewed like human PRs?
That is the default. Each change arrives as a branch with a description of intent and evidence; your existing review and CI gates apply unchanged.
How does it verify what crawlers see?
By fetching and rendering pages the way crawlers do and diffing the result against the expected metadata and structured data — continuously, not as a one-off audit.
Does it require Cloudflare specifically?
Edge-level work is built on Cloudflare. On other CDNs, Ops still monitors and reports, with fixes delivered as configuration recommendations rather than applied directly.
Keep reading
Site speed optimisation
Find what actually slows real users down, fix it, and stop the regressions that undo it.
Cloudflare
Edge performance, caching, and bot protection — managed continuously by the Ops agent.
Store localisation
Sell properly in more than one language — localised pages, correct hreflang, per-market SEO.
B2B & wholesale
RFQ-driven sites where the conversion is an enquiry and the buyer is a business.
Put the team to work on your store
Connect your storefront, analytics, and email stack, set a goal, and let the agents run the work end to end. Start on the free plan with your own model key.