I fixed canonical errors across 28 websites — here's what my agents actually did

Background and Motivation

I've been running a self-hosted AI system, which I've dubbed Ollama, for the past year. Ollama consists of 50 Python agents, each with a specific role, scheduled to run at various intervals using cron. My primary goal with Ollama is to automate mundane tasks across the 20+ websites I manage, freeing up time for more strategic and creative endeavors. Recently, I noticed that canonical errors were plaguing many of these websites, resulting in duplicate content issues and negatively impacting search engine rankings. I decided to enlist the help of my agents to rectify this problem.

Identifying the Problem and Assigning Roles

The first step was to identify the scope of the problem. After running a scan using my SEO agent, Axiom, I found that 28 websites were affected by canonical errors. I then assigned roles to my agents to tackle this issue. Atlas, my overseer agent, was tasked with coordinating the effort and ensuring that all agents worked together seamlessly. The content agent, Forge, was responsible for analyzing website content and identifying duplicate pages. Meanwhile, Sentinel, my SEO agent, focused on auditing website structures and pinpointing canonicalization issues.

Agents in Action

With their roles defined, my agents set to work. Scout, a specialized agent, was tasked with crawling the websites to gather data on duplicate content and canonical tags. This data was then fed into Forge, which analyzed the content and identified areas where duplication was occurring. Axiom, working in tandem with Forge, ensured that the solutions proposed would not inadvertently create new canonicalization issues. Atlas oversaw the entire process, ensuring that all agents were working together efficiently and that the solutions were properly implemented across all 28 websites.

Trade-Offs and Challenges

One of the significant challenges I faced was the computational power required to run these tasks. With only an RTX 4050 6GB laptop at my disposal, I had to carefully schedule tasks to avoid overloading the system. This often meant running tasks during off-peak hours or staggering them to prevent resource conflicts. Another trade-off was the time it took to refine the agents' workflows. Initially, the agents would sometimes propose solutions that, while technically correct, were not the most efficient or practical. It took several iterations and refinements to get the agents to a point where they were consistently producing high-quality solutions.

Solutions and Outcomes

After several weeks of my agents working tirelessly, we were able to resolve canonical errors across all 28 websites. The SEO agent, Axiom, reported a significant reduction in duplicate content issues, and subsequent search engine crawls showed improved indexing and ranking for these sites. To achieve this, my agents implemented a variety of solutions, including:

• Implementing canonical tags on duplicate pages to specify preferred versions.
• 301 redirects to direct users and search engines to the canonical version of a page.
• Modifying internal linking structures to prioritize canonical pages.
• Creating high-quality, unique content to replace duplicate pages where necessary.

These solutions not only resolved the immediate issue of canonical errors but also contributed to an overall improvement in the health and visibility of the websites.

Lessons Learned and Future Directions

This experience with my self-hosted AI system has taught me the importance of carefully defining agent roles and workflows. It also highlighted the need for continuous refinement and testing to ensure that agents are producing practical, high-quality solutions. Moving forward, I plan to expand the capabilities of my agents to tackle more complex tasks, such as advanced content optimization and technical SEO audits. The success of this project has shown me the potential of self-hosted AI systems in managing and improving multiple websites simultaneously, and I am excited to explore what more can be achieved with Ollama.