I’m introducing Pages in Profound—my single command center for monitoring content citations, tracking bot activity, and understanding page health.
Inspired by this post on Try Profound Blog.
Author: @tryprofound
-
Meet Pages: My Command Center for Content Performance
Profound’s content command center puts page analysis beside the article itself, surfacing a 65% score and signals for freshness, structure, readability, and information density. A side-by-side content audit reveals a stark visibility gap: bots can read just 25% of the page, while the JavaScript-rendered human view exposes far more content.
-
GPT-5.6 Support in Profound for Smarter AI Workflows
I’m introducing support for GPT-5.6 in Profound, bringing OpenAI’s newest flagship model family directly into the workflows I rely on for advanced AI performance.
With GPT-5.6, I can work across the new Sol, Terra, and Luna tiers, giving me the flexibility to support everything from frontier reasoning to high-throughput production workloads.
I’m especially focused on what this means for agentic workflows, coding, research, and enterprise knowledge work. GPT-5.6 delivers meaningful improvements in capability, reliability, and efficiency, making it easier for me to apply AI across a wide range of business use cases with more confidence.
Inspired by this post on Try Profound Blog.
-
How I See Profound MCP Reshaping AI Shopping in Retail
I see Profound’s MCP evolution as a meaningful shift for Marketing Engineers. It now connects agents to a knowledge graph and adds 15 new capabilities built around how marketing teams actually work.
For retailers, I believe this demands a serious reframe. Answer engines are already shortlisting products and shaping purchase decisions long before shoppers ever land on retail or ecommerce websites. That compresses the shopping funnel and makes traditional search less reliable as the primary channel for customer acquisition.
Instead of waiting for shoppers to arrive through search, I need to think about how retailers can be recommended throughout the entire shopping journey. That means understanding how people use answer engines for Christmas gifting, how brands earn mentions and citations in relevant AI responses, and how visibility can be maximized across AI search experiences.
I see this report as a practical edge for retailers preparing for the next holiday cycle. It uses real shopper behavior from Christmas 2025, analyzed through Profound’s AI visibility lens, to show how people are using AI to shop for the holidays.
Most importantly, it turns those insights into actionable takeaways. By understanding where answer engines influence discovery, comparison, and purchase decisions, I can see how ecommerce teams should optimize product visibility before the 2026 season ramps up and compete more effectively for the AI shelf this Christmas.
Inspired by this post on Try Profound Blog.
-
How I Help Retailers Win the AI Shelf This Christmas
I see Christmas shopping moving beyond the search bar. More shoppers are now turning to AI answer engines to research products, compare gift options, and decide what to buy long before they land on a retailer’s website.
For retailers, I believe this shift requires a serious reframe. Answer engines can shortlist products, shape preferences, and guide purchase decisions earlier in the journey than traditional search ever did. That compresses the shopping funnel and makes search alone too limited as a customer acquisition strategy.
Instead, I need to think about how retailers can earn recommendations across the entire AI-assisted shopping journey. That means understanding how people use answer engines for Christmas gifting, how brands earn mentions and citations in relevant AI responses, and how ecommerce teams can improve visibility across AI search.
In this report, I give retailers a clearer path to that advantage. I draw on real shopper behavior from Christmas 2025, analyzed through Profound’s AI visibility lens, to show how people are using AI to shop for the holidays.
I also focus on practical takeaways retailers can use now, before the 2026 season ramps up. The goal is simple: optimize ecommerce products early, show up in the AI answers that matter, and win the AI shelf this Christmas.
Inspired by this post on Try Profound Blog.
-
How AI Search Is Reshaping Travel Brand Visibility
I’m seeing travel planning move away from the traditional search bar and into AI answer engines like ChatGPT. For most of the past two decades, a traveler would type a destination-focused keyword into Google, open a dozen tabs, and stitch together a trip one page at a time.
Now, that same traveler can ask a question, keep the conversation going, and let the answer engine synthesize recommendations, compare options, or even help book the trip. The journey from curiosity to decision is becoming faster, more conversational, and far less dependent on traditional search results.
I believe this shift is rewriting how travelers discover brands. Visibility is no longer only about winning top-ranked blue links in Google. Increasingly, it depends on earning mentions, citations, and trust inside AI-generated answers.
For travel brands, that changes the competitive landscape. The companies that show up in AI search are the ones most likely to shape the itinerary, influence the booking decision, and ultimately win the trip.
Inspired by this post on Try Profound Blog.
-
Why I Am Excited About Grok 4.5 Support in Profound
I am introducing support for Grok 4.5 in Profound, bringing SpaceXAI’s newest flagship model into workflows built for deeper, more capable AI analysis.
Grok 4.5 is designed for agentic workflows and knowledge work, which makes it a strong fit for teams and operators who need AI systems that can reason, assist, and move complex tasks forward with more context.
With this support now available in Profound, I can use Grok 4.5 as part of a broader AI workflow and explore how its capabilities help with research, strategy, automation, and day-to-day knowledge work.
Inspired by this post on Try Profound Blog.
-
Why I Run Each Prompt Once Daily: The Data Behind It
I often get asked why I “only” run each prompt one time per day.
For me, the answer comes down to signal quality. Running a prompt once daily gives me enough consistent data to understand performance without overloading the process with unnecessary repetition.
The statistics show that a single daily run is plenty. It gives me a reliable view of how prompts behave over time, while keeping the workflow focused, efficient, and easier to interpret.
Inspired by this post on Try Profound Blog.