Inside Waverider: how a remote SEO pod runs a week

How our remote pods structure enterprise work

We started Waverider SEO in 2019 as a three-person technical shop in California. Before founding the agency, I ran organic growth for an enterprise marketplace reaching 40M monthly sessions. Managing organic estates at scale taught me one truth. Large websites fail not from a lack of ideas, but from poor operational structure.

Today, Waverider SEO operates as a remote-first team of eleven across US Pacific and Mountain time. Our headquarters remain at 1902 Wright Place, Suite 200 in Carlsbad, California, near the Pacific shoreline. We organize our eleven team members and specialist contractor bench into dedicated pods. Each pod combines technical depth, data science, content systems, and account governance.

Theo Nakamura, our Head of Enterprise SEO, brings twelve years of experience leading complex technical programs, migrations, and re-platforms. Theo pairs with Daniel Okafor, our Technical SEO Lead, who monitors log files, manages crawl budgets, analyzes rendering paths, and builds internal tooling.

Our agentic practice, added in 2024, is led by Priya Raghunathan, Director of Agentic SEO. Priya previously worked in ad tech data science. She built our AI-visibility measurement models and agentic workflows. Sofia Lindqvist, Content Strategy Director, designs editorial systems for large content estates. Ben Whitaker, Analytics & Measurement Lead, owns revenue attribution, executive reporting, and forecasting. Aisha Rahman, Account Director, leads enterprise client relationships and quarterly business reviews. Lucas Ferreira, SEO Strategist, drives entity research, competitive audits, and internal linking programs.

This pod structure allows us to manage 4.2M pages across 38 enterprise engagements since 2019 while maintaining a 94% client retention rate across 2024 and 2025.

Aligning rituals across Pacific and Mountain time

Operating across US Pacific and Mountain time zones requires disciplined communication. We do not rely on ad-hoc messaging or endless meetings. We run a structured week built around clear deliverables.

Monday morning begins with an asynchronous alignment call. Each pod lead reviews log files, crawl anomalies, and AI visibility metrics gathered over the weekend. Daniel Okafor checks server logs to verify how search engine crawlers process site changes. Priya Raghunathan reviews LLM citations, share of answer data, and AI Overviews tracking across core query sets.

By mid-morning on Monday, Aisha Rahman aligns pod priorities with client stakeholders. We set weekly execution goals mapped directly to engineering sprints.

Mid-week check-ins focus strictly on technical implementation and agentic remediation. Theo Nakamura and Daniel Okafor review edge rules and rendering pipelines with client engineering teams. Meanwhile, Lucas Ferreira and Sofia Lindqvist audit content structures to ensure pages remain agent-readable for retrieval engines.

On Friday afternoon, Ben Whitaker compiles performance data into executive dashboards. We track organic revenue, search visibility, and share of answer metrics. Aisha Rahman delivers these concise updates to VP Marketing and Head of SEO buyers.

Executing our Tidewater framework in weekly cycles

Every client program follows our proprietary Tidewater™ method. We execute this framework through four distinct stages:

• Map: We crawl site structures, analyze log files, map entity nodes, and establish an AI-visibility baseline.
• Fix: We execute technical programs and agent-run remediation, ensuring every fix undergoes human engineering review.
• Feed: We structure content for traditional search engines and for retrieval by AI answer engines.
• Measure: We track LLM citations, monitor share of answer, attribute organic revenue, and present executive reporting.

Our work on a major insurance marketplace illustrates this cycle in action. Managing 2.1M product pages required automated execution paired with human oversight. Priya Raghunathan deployed agentic workflows to handle repetitive site fixes. Over 6 months, our agents shipped 11,400 technical fixes, all reviewed by Daniel Okafor before deployment.

The results validated the process. AI citations grew 2.3x in 6 months. Share of answer expanded from 9% to 27% on core queries.

A similar focus governed our platform migration for a US home-goods retailer with 1,800 SKUs and 12M annual sessions. Theo Nakamura managed the migration strategy, reducing crawl waste by 71%. The project achieved a zero-loss migration and drove a 63% increase in organic revenue over 11 months.

Human review for agentic workflows and code

Agentic SEO accelerates technical remediation, but unverified automation risks site integrity. We treat AI agents as specialized team members operating under human supervision.

When Daniel Okafor writes internal tooling or Priya Raghunathan configures agentic workflows, every script adheres to strict governance standards. Agents identify schema errors, broken canonical tags, and internal link gaps. However, no code reaches production environments without approval from Theo Nakamura or Daniel Okafor.

For content structured for AI answer engines, Sofia Lindqvist reviews every entity model. We align content markup with official documentation on developers.google.com/search and structured data schemas on schema.org. This verification process ensures content remains accurate and easily parsed by LLM retrieval systems.

Our B2B SaaS client program demonstrates the power of governed technical execution. Managing 60k URLs across 9 locales, Theo Nakamura resolved hreflang errors, moving from 41k errors down to 0. Over 14 months, non-brand clicks increased by 148%, and the client board officially adopted our executive dashboard.

What we stopped doing to protect execution

Sustaining a 27-month average engagement requires protecting team focus. Over years of agency growth, we systematically eliminated low-value activities.

First, we stopped writing lengthy, manual audit slide decks. Detailed decks often sit unused in shared drives. Instead, we deliver actionable ticket backlogs directly into client engineering boards, backed by clear executive reporting dashboards.

Second, we stopped running manual keyword density reports. Modern search engines and AI answer engines evaluate entity relationships and context rather than keyword repetition. Lucas Ferreira focuses on entity mapping and retrieval optimization instead of legacy keyword tracking.

Third, we stopped executing unverified script deployments. Automated tools can introduce crawl errors if left unchecked. Every technical fix generated by an agent goes through engineering review before release.

Finally, we stopped hosting status meetings without pre-distributed log file data and measurement metrics. If data does not show clear movement in crawl efficiency, AI citations, or organic revenue, we investigate the underlying system before gathering the team.

This operational discipline ensures our team of eleven delivers consistent results for enterprise brands across every stage of growth.