ninobareque
Newbie
- Mar 26, 2026
- 22
- 19
Hi BHW,
I’m a Staff software engineer (10+ years XP), and instead of building another bloated Shopify store, I’ve spent the last few weeks building a programmatic + edge-first SEO system to dominate a high-ticket niche in a LATAM market (Colombia) — SUS-304 kitchen hardware.
This is not churn & burn.
I have real imported inventory, local fulfillment, and I’m building for scale.
I’m approaching this with a simple belief:
→ Engineering + speed of execution can outperform traditional SEO playbooks.
Curious to see if that actually holds.
Typical setup with platforms like Shopify:
With this edge-first system:
The key difference:
→ In most setups, scaling traffic increases cost and complexity.
→ In this setup, scaling traffic only increases opportunity.
This changes how I approach SEO entirely:
→ I’m not optimizing within constraints — I’m defining them.
My hypothesis:
Most Shopify-based stores are structurally limited before they even start competing.
Curious if anyone here has seen the same — or thinks this doesn’t actually matter in rankings.
→ Without strict standardization, PSEO becomes unmanageable very fast.
Trying to keep this high-level for now and share deeper details as things evolve.
Goal:
→ Capture local demand first
→ Build strong positioning in a controlled environment
→ Expand into top 10 cities after validation
I’ll update this thread with:
Let’s see if engineering + execution can outperform traditional SEO — or if I’m completely wrong.
I’m a Staff software engineer (10+ years XP), and instead of building another bloated Shopify store, I’ve spent the last few weeks building a programmatic + edge-first SEO system to dominate a high-ticket niche in a LATAM market (Colombia) — SUS-304 kitchen hardware.
This is not churn & burn.
I have real imported inventory, local fulfillment, and I’m building for scale.
I’m approaching this with a simple belief:
→ Engineering + speed of execution can outperform traditional SEO playbooks.
Curious to see if that actually holds.
The Stack ($0 Infra, Fully Live)
- Edge Infra: Cloudflare Workers + Pages
- Core System: Built using Claude Code (agentic workflows for generation + structure)
- Analytics: PostHog (deep funnel + behavioral tracking)
- Architecture: No CMS, no plugins, no bloat
- TTFB < 100ms
- LCP ~1.2s
- CLS = 0
- Infra cost: $0/month
Why $0 Infra Actually Matters (vs Shopify / Typical Stacks)
This is not just about saving money — it’s about removing structural limitations.Typical setup with platforms like Shopify:
- Monthly subscription ($39–$399)
- Multiple paid apps (reviews, SEO, CRO, speed) → $50–$300+/month
- Increasing JS bloat from plugins
- Slower performance as the stack grows
- Limited control over core architecture
- Hidden costs (databases, functions, bandwidth)
- Performance inconsistencies
- Fragmented systems that don’t scale cleanly
With this edge-first system:
- Cost ≈ 0 regardless of traffic → I can scale without financial pressure
- No plugin overhead → performance stays consistent as I grow
- Full control of HTML output → precise SEO execution
- No platform constraints → I can build exactly what the use-case needs
- Instant deployment at the edge → faster iteration cycles
The key difference:
→ In most setups, scaling traffic increases cost and complexity.
→ In this setup, scaling traffic only increases opportunity.
This changes how I approach SEO entirely:
- I can test aggressively
- Launch hundreds of pages without risk
- Iterate faster than competitors
→ I’m not optimizing within constraints — I’m defining them.
My hypothesis:
Most Shopify-based stores are structurally limited before they even start competing.
Curious if anyone here has seen the same — or thinks this doesn’t actually matter in rankings.
Engineering System (This is the real play)
Everything is standardized and generated through controlled inputs:- SEO checks: semantic structure, indexability, internal linking
- CRO checks: CTA placement, above-the-fold clarity, friction audit
- PSEO variables: location, modifiers, intent clusters
- Reusable templates: generated via structured logic (not blind page generation)
- Generate page structures
- Enforce consistency across templates
- Scale variations without introducing technical debt
→ Without strict standardization, PSEO becomes unmanageable very fast.
Trying to keep this high-level for now and share deeper details as things evolve.
Strategy (Phase 1 → Local Capture)
- Fresh domain (.com)
- Programmatic landing pages:
- Product × City
- Category × City
- Intent variations (not just keyword swaps)
Goal:
→ Capture local demand first
→ Build strong positioning in a controlled environment
→ Expand into top 10 cities after validation
- Planning to launch Google Ads after initial indexation (~1 month)
Current Status (Launch Phase)
- Site: LIVE
- Build time: ~few weeks
- Indexed pages: starting now
- Traffic: planning to start paid acquisition in ~1 month after initial indexation
- Reviews: will be acquired gradually (real customers only)
Questions for those scaling aggressively
- Sandbox / Trust Acceleration:
How much impact have you seen from combining strong UX + immediate paid traffic on fresh domains? - Authority in LATAM:
Fastest clean ways to build authority links in markets like Colombia? - Backlinks Strategy:
Is it still worth buying backlinks in 2026 for local niches, or are you seeing better ROI with PR / real mentions? - Analytics Tradeoff:
Using PostHog early vs going fully server-side for performance? - PSEO Scaling Reality (2026):
Where are you seeing diminishing returns — volume vs variation? - Local Domination:
Highest ROI actions to win a single city fast?
End Goal
- Dominate 1 city → expand to 10 major cities
- Keep infra near $0 while scaling
- Build a defensible SEO + conversion system
I’ll update this thread with:
- Indexation data
- Ranking movement
- Conversion metrics
- What actually works vs what breaks
- Claude Code workflows
- Edge architecture decisions
- PSEO generation logic
Let’s see if engineering + execution can outperform traditional SEO — or if I’m completely wrong.









