I’m thrilled to introduce two groundbreaking Agent Analytics nodes from Profound: Bot Visits and Human Referrals. These innovative additions bring AI bot and Answer Engine referral data directly into Profound Agents, revolutionizing how we understand and optimize interactions.
Imagine the possibilities with Bot Visits, where you can track and analyze the influx of AI bot visits to your platform. This insight helps us optimize how we engage with automated traffic, ensuring that our systems are always at peak performance.
On the flip side, the Human Referrals node provides in-depth data about Answer Engine referrals. It’s like having a direct line to understanding how humans are being referred to our platforms, enabling us to craft more targeted strategies that resonate with real users.
With these nodes in place, we’re not just collecting data; we’re gaining a strategic advantage, allowing for more informed decisions and streamlined processes. Let’s embrace this new era of analytics that’s powered by AI intelligence.
As a Profound customer, I’m excited to share that I can now clearly see where my site and pages stand in terms of AI citations compared to other peers in the Profound Agent Analytics Network.
This feature empowers me with detailed insights, allowing for a competitive analysis that helps in enhancing my digital strategy and boosting my AI visibility effectively.
I’ve been on a journey to develop over 10 SEO agent skills in just 34 days. Six of these succeeded on the first attempt, while the remaining four taught me invaluable lessons, especially about the overlooked importance of folder structure that many LinkedIn posts on AI SEO skills seem to miss.
The reliability of these agents isn’t about crafting superior prompts; it lies in the architecture that supports them. Here’s my blueprint for building an agent from scratch, testing it diligently, refining it, and deploying it with full confidence.
Here’s why many AI SEO skills don’t make the cut.
A typical AI SEO prompt seen on platforms like LinkedIn usually looks something like this:
You are an SEO expert. Analyze the following website and provide a comprehensive audit with recommendations.
And that’s where it ends. One simple prompt, often coupled with some formatting directions, is shared with the world. The post then earns hundreds of likes, yet the output—while polished—is often up to 40% inaccurate.
I know because I’ve been there. Initially, I tasked an agent to identify SEO issues on a website, and while it came back with 20 findings, eight were non-existent. The agent hadn’t truly visited many of the reported URLs.
Here are three key issues that doom single-prompt skills:
No tools: The agent can’t physically verify the website; it relies on training data to guess. Queries about canonical tags, for instance, result in assumptions rather than real-time analysis of HTML.
No verification: There’s no check on the truthfulness of output. An agent might report missing meta descriptions across 15 pages, but without verification, we don’t know if these pages are even indexed correctly or intentionally set as noindexed.
No memory: The agent’s feedback varies wildly with each use, showing inconsistency due to the lack of a template or structured history of previous runs.
In essence, if your skill is just a prompt within a lone file, you’ve got a 50/50 chance at best.
Every agent in my system has a dedicated workspace. Consider it akin to a new employee’s desk, equipped with all necessary resources. For example, our agent designed to crawl and map website architecture works within this kind of structured environment:
agent-workspace/
AGENTS.md instructions, rules, output format
SOUL.md personality, principles, quality bar
scripts/
crawl_site.js tool the agent calls to crawl
parse_sitemap.sh tool to read XML sitemaps
references/
criteria.md what counts as an issue vs noise
gotchas.md known false positives to watch for
memory/
runs.log past execution history
templates/
output.md expected output structure
The workspace includes six key components services that just one prompt couldn’t dream of covering fully.
Within AGENTS.md, I’ve articulated a meticulous methodology comprising thousands of words. Instead of a simple instruction like “crawl the site,” I detailed each step: “Start with the sitemap; if it doesn’t exist, check various routes like /sitemap.xml, /sitemap_index.xml, and robots.txt for references.”
Scripts represent the tools the agent utilizes. Instead of writing curl commands from scratch for each crawl, the agent can run node crawl_site.js -url to analyze website data, which is far more efficient and reliable.
References consist of criteria that help the agent distinguish between significant issues and noisy false positives, using a wealth of knowledge I’ve amassed over two decades.
To ensure that every execution is informed by the past, I keep meticulous logs under memory, serving as institutional knowledge that empowers consistency across agent runs.
Through templates, I outline the exact format I expect from the output, thereby maintaining high quality across multiple iterations of the same task.
Building from scratch, the first naive attempt involved simple instructions that inevitably failed when confronted with modern CDNs. By iterating and incorporating tools like crawl_site.js, enhancing with rate limiting, and tackling JavaScript rendering, I’ve honed an architecture that delivers consistent outputs across runs.
The path involves a series of iterations where each failure metamorphoses into a permanent lesson, gradually shaping a sophisticated system. This methodically structured approach ensures that what we build is not just technically proficient but measurably better with every successive run.
I’m excited to introduce you to the innovative iteration nodes in Profound Agents, designed to revolutionize the way we manage complex workflows.
The beauty of the iteration node lies in its ability to encapsulate a series of steps within your Agent. By setting up these steps just once, I can easily pass in a list of items, and watch as each item seamlessly progresses through the specified sequence, simultaneously.
Have you ever found yourself juggling multiple tasks, wishing there was a seamless way to manage everything? I’m excited to introduce the Google Suite integration designed specifically for agents like me. This powerful tool allows us to streamline our workflows by sending emails, creating documents, and even pulling data from spreadsheets with ease.
Imagine being able to access all your necessary documents without switching between different platforms. With this integration, I can not only create and retrieve documents but also extract context from any presentation deck in no time. It’s a game-changer for efficiency and productivity.
What’s even more impressive is how this tool helps with spreadsheet data. I can read and write data seamlessly, making it easier to keep everything up-to-date. The Google Suite nodes provide us with everything we need to master our work environment.
As someone who’s deeply involved in the world of e-commerce, I know how crucial it is to understand whether your Shopify store’s pages are being referenced by LLMs (Language Learning Models). Up until now, that insight has remained elusive for those of us using Shopify. But everything is about to change.
Partnering with Nostra, Profound is bringing comprehensive Agent Analytics capabilities to Shopify brands for the very first time. This groundbreaking opportunity means that we can finally gain an overview of how our web presence is echoed in the digital realm, opening the doors to advanced marketing and strategy opportunities.
