Jonathan Boshoff

Black & White Zebra

SEO Content Manager

AI SEO Academy

Founder

Search Engine Optimization Consultant

Digital Sisco

SEO Manager

BrainFinance

Senior SEO Specialist

Top Draw Inc.

Senior Digital Marketing Specialist (SEO)

Bluetrain Inc.

Digital Marketing Specialist (SEO)

Sherwood Dodge

Internet Marketing Manager

D2C Media Inc

Online Marketing Manager

Sun Valley Honda

Jonathan Boshoff is an SEO consultant with expertise in artificial intelligence. Jonathan is a leading expert in AI SEO. He founded the AI SEO Academy, offering comprehensive online courses that meld SEO knowledge with cutting-edge AI applications.

Jonathan develops AI-powered applications, tools, and Python scripts that optimize and automate SEO tasks.

Beginning his career in 2012, Jonathan accrued a wealth of experience working as an SEO specialist in digital marketing agencies and in-house marketing roles. He has executed hundreds of SEO projects, achieving 2-3x revenue increases from Organic search. His diverse client portfolio includes Fortune 500s, startups, e-commerce, finance, technology, and more.

SEOs are freaking out over Google’s quiet change to the &num=100 parameter.

Here’s why it matters:
- Every rank tracking tool relied on an API parameter (&num=100) to pull the top 100 results.
- LLMs and AI tools also rely heavily on this parameter to do research.
- Google killed it. Now you only get 10 results per query.

The “fix” is pagination (the start parameter gets page 2, page 3, etc.), but that means running 10 separate queries to retrieve the same 100 results.

The ripple effect:
- API costs spike 10x overnight.
- Tool makers have to scramble to re-engineer their systems.
- Dev teams are working overtime to keep basic functionality alive.

Google didn’t warn anyone. One switch flipped, and every rank tracker broke.

When one quiet API change can break the ecosystem and multiply costs by 10x, you see just how dependent this industry is on Google’s whims.

Founder of the AI SEO Academy: Building compounding growth engines

In the past 7 days, my n8n automations did the equivalent of 153 hours of SEO work.

That’s about four full-time employees. 
If you consider studies showing knowledge workers average only ~4 hours of meaningful work per day, you could argue it’s closer to eight.

The work being automated is the repetitive execution.
The work I actually do is planning and implementing growth roadmaps.
That's the fun, high-leverage part of SEO most people wish they had more time for.

The workflows I’ve built mirror exactly how I’d do the work manually.
They run nonstop, freeing me to focus on strategy and execution.
That’s why the impact compounds.

And this is just my personal account. When I factor in client automations, the hours saved are far higher.

The reality is I’m already matching the workload of a small SEO agency without building a team.

Automation handles the repetitive parts, and I get to focus on the growth levers.

This is the future: operators running an army of agents while spending their own energy on strategic planning and high-impact moves.

When you replace manual hours with automation, you don’t just save time. You reclaim the best part of your work and scale the value you deliver.

Founder of the AI SEO Academy: Helping you turn SEO into a compounding growth engine with AI

Most AI models can’t browse the web through their API. Which means if you’re relying on them for “live results,” you’re often just getting hallucinations.

The fix? Give your agents their own Google Search tool.

In my latest video, I show how to:
- Build an AI agent from scratch in n8n
- Connect it to Google’s programmable search engine API
- Customize region, language, and result types

The result: agents that can run real web searches, pull back live data, and even combine it with page scrapers for deeper context.

It takes minutes to set up and opens up endless use cases.

👉 Video link in the description

Don’t trust “magic prompts.” Equip your agents with real tools.

Cost Comparison vs Deep Research:
This method is roughly 5× cheaper than o4-mini-deep-research and ~20–40× cheaper than o3 Deep Research, depending on token mix and caching.

GPT-5-Mini is $0.25/M input and $2/M output (vs $2/$8 for o4-mini and $10/$40 for o3), so a typical 1M in + 300k out run is about $0.85 on Mini vs $4.40 on o4-mini and $22 on o3.

This workflow is a 1:1 automated replica of a marketing agency's SOP.
Instead of humans clicking through every step, AI and automation handle the entire process.

Old Way
- Write a detailed SOP
- Hire people to follow it exactly
- Scales with headcount
- Every new team member needs training

New Way
- Turn SOP into a detailed workflow
- Let AI execute it exactly
- Scales effortlessly
- No training required, just occasional troubleshooting

SOPs scale with headcount. Automated workflows scale without limits.

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