1) JavaScript SEO: SSR/SSG/ISR/CSR is a systems design decision
Rendering traps: when your site looks fine but Google sees an empty shell
Pagination + faceted navigation: prevent infinite crawl spaces
Treat filters like an API surface area: if you allow infinite combinations, bots will waste crawl budget and dilute quality signals.
Guardrails:
- Canonical strategy (self vs parent)
- Noindex for low-value combinations
- Parameter handling (UTMs, internal params)
- Page caps (e.g., noindex or don’t generate page > 50)
- Only submit what you truly want indexed in sitemaps
2) Programmatic SEO with quality gates (TripAdvisor-style pages)
TripAdvisor is a classic example of ranking with predefined search results pages that match clear intent (e.g., “restaurants in San Diego” with cuisine filters).
The lesson isn’t “generate 10,000 pages”. The lesson is: build programmatic pages like a product line with measurable quality controls.
Programmatic SEO without spam: build an internal quality gate
Non-technical SEO that still matters: dedicated landing pages for targeted keywords
Technical SEO ensures pages can be discovered and indexed. Growth often comes from having a clear page for a clear intent:
- “technical SEO audit”
- “Core Web Vitals improvement”
- “Next.js SEO”
Each needs its own landing page: clear outcome, proof method, deliverables, and a next step.
Organic traffic compounds: a strong page keeps working when ad spend is zero.
3) Structured data beyond basics: schema as a contract (and CI discipline)
Treat schema markup like typed data and an API contract with Google: version it, test it, and make it part of release quality.
Useful schema types (when you have real content to support them):
- Article, BreadcrumbList
- FAQPage (only if the page contains real Q&A)
- VideoObject (if video is central)
- Organization / service modeling (so Google understands what you offer)
Add schema validation to CI/CD (small effort, big stability)
Schema regressions happen the same way broken links happen: a template changes and thousands of pages degrade.
A pragmatic approach:
- keep schema generators in one place (helpers)
- add lightweight tests for required keys
- add a smoke check that renders a few key pages and ensures JSON-LD exists and is sane
Video content: don’t ship “just a YouTube link”
If video helps users decide, treat it as core content:
- align video with page intent
- include a written summary on the page (not only video)
- add VideoObject schema when appropriate
4) SEO observability: instrument crawlers like an SRE
Search Console is useful, but it’s delayed and aggregated. For engineering decisions, you want direct signals.
A minimal “SEO observability stack”:
- CDN/server logs: what bots actually request and what responses they get
- an indexation funnel dashboard (at least for top pages)
- probes: automated checks that critical pages contain real server-rendered content
Canonicalization bugs: how to prove it at scale
Canonical mistakes in dynamic apps often come from a template bug.
Test it at scale:
- take sitemap URLs (or a sample)
- fetch HTML
- parse canonical
- validate “self canonical” vs intentional parent canonical
Sitemaps at scale: think “queue management”
Sitemaps are a priority signal. Keep them clean:
- split by content type (articles, categories, programmatic pages)
- never include noindex URLs
- don’t overthink changefreq; focus on accurate freshness/invalidation instead
5) Core Web Vitals: INP and LCP as conversion engineering
Core Web Vitals are not “just a ranking factor”. They are UX and conversion.
Tie CWV directly to your funnel (pricing → contact, service page → lead, blog → service). Fix the interactions that block user intent.
INP is the bottleneck: find interaction jank in real flows
INP improvements come from understanding main-thread work during real interactions:
- split long tasks, yield to the main thread
- move heavy work off-thread (Web Workers)
- control third-party scripts (often the hidden INP killer)
LCP is a rendering strategy problem
LCP improves when you prioritize first-view resources:
- image/CDN strategy (right format, right size, correct priority)
- font loading strategy
- SSR/streaming choices that reduce “empty shell time”
6) Standing out in the AI era: quality + architecture wins
In the AI era, “more content” is easy. Differentiation comes from:
- real trade-offs and real failure modes (engineering reality)
- consistent information architecture (services → proof → guides → next step)
- measurable outcomes and a feedback loop
Want to connect the engineering work to business outcomes? See:
Mini FAQ
Does FAQ schema guarantee a rich result?
No. It’s a signal, not a guarantee.
Is CSR always bad for SEO?
Not always-but it increases risk unless you control what bots actually get.
Is programmatic SEO inherently spam?
No-if you have quality gates, dedupe rules, and indexation discipline.
Conclusion
Technical SEO in 2026 is engineering: rendering strategy, indexation control, schema discipline, observability, and quality gates for scale. When those are stable, content and landing pages compound instead of creating crawl debt.