SEO Standards Are Changing

New technology is changing the way that SEO professionals handle implementation.

Cover image for the SEO Standards Are Changing blog post about AI tools, MCP servers, prompting, and token optimisation.

Key takeaways

  • New technology is changing the way that SEO professionals handle implementation.
  • All professionals are feeling immense pressure to adopt AI or be left behind.
  • Standards don’t eliminate value; they shift it elsewhere in the stack.
  • Dash Audits aims to handle the prompt and context engineering for you.

Key takeaways

  • New technology is changing the way that SEO professionals handle implementation.
  • All professionals are feeling immense pressure to adopt AI or be left behind.
  • Standards don’t eliminate value; they shift it elsewhere in the stack.
  • Dash Audits aims to handle the prompt and context engineering for you.

The New Technology

New technology is changing the way that SEO professionals handle implementation. Many veteran coders like Steve Yegge, Simon Willis, & Boris Cherny of Anthropic have left manual coding entirely for ‘vibe coding’, which has sped up their productivity. All professionals are feeling immense pressure to adopt AI or be left behind. This is why Dash Audits exists, as it uses the latest technology to scale the services and value that a consultant can provide.

SEO Standards Are Changing

While it’s not currently the case, agentic systems will be simple to use for everyone. They will have more skills and connect to every data vendor. Model Context Protocol (MCP) servers connect Codex and Claude Code to tools like Google Search Console & Google Analytics. Experts can now sift through large amounts of data using natural language. MCP server are causing the value to shift in SEO:

'Standards don’t eliminate value; they shift it elsewhere in the stack. When a standard emerges, it flattens the connectivity layer, making integration cheap and interoperability ubiquitous. That just shifts the value upstream to those who provide scale and reliability, and downstream to those who solve domain-specific problems that the standard doesn’t. This pattern is the key to understanding why most API companies failed and why most MCP startups will, too.'

In other words value is now created downstream by wider marketing teams comprised of domain specific experts using AI, and upstream for AI powered SEO services that are scalable and reliable to the many.

Prompts & Domain Expertise is Valuable

Now that any technical person can set up Claude Code or Codex, it has democratised the web. Business owners can efficiently build their own website, attempt user experience, design and SEO. To the trained eye, websites that come out of this kind of basic prompting and depth of domain knowledge look roughly the same. Whilst this may be a good starting point for a business, website users will likely see the same patterns and artifacts emerging in the products, which may lead to distrust. To create a website that stands out from the crowd, someone with a trained eye using the AI tools consistently is required. Even for professionals it takes months of experience with tools like Claude to create a great set of prompts and techniques that they can use across projects.

For more complicated website problems, simple prompts and random data context is not going to create optimal solutions. Prompts require detailed sculpting, domain expertise, and sufficient data context for unique results. On top of this, there are changing prompting standards for each AI model. Extensive time will need to be invested in prompt and context engineering to keep up with things.

Token Optimisation & Context Windows

Websites are going to get bigger, better or more complex as code is not the bottleneck - instead growth is conjoined with token limits, and the context window of the large language model. Businesses will invest a lot of time trying to optimise the prompts, data context and guide the AI to not exceed these limits. This will be true even for the free-to-use open source AI models that are only 3 months behind the state of the art.

Capturing New Value

Dash Audits aims to handle the prompt and context engineering. This allows businesses to save time and to save token count. Our system optimises three things: Prompts based on common SEO & website marketing problems, Data context, and results (based on who’s interacting with it). For a conversion funnel, the data context may include:

  • Target audience data
  • Traffic data (cross channel / GSC)
  • Performance data (GA4)
  • Optimised HTML
  • Screenshots
  • Marketing problem
  • Conversion goal
  • Prompt generated based on the above

More complex use cases include optimising pages in funnels that overlap based on multiple traffic sources, intent, audiences and conversion goals. On a larger scale it becomes possible to optimise site wide marketing campaign roll outs based on common user pathways and how content weaves through the website.

Want to see this workflow live?

Try the free SEO audit tool for a fast sample, or review the full feature walkthrough and request a tailored live demo for your team.

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