AI Visibility for B2B SaaS: What to Fix First
B2B software buyers are starting to let AI agents do the first pass of vendor research. This piece walks through exactly what a SaaS company needs in place so it doesn't get filtered out before a human ever sees the shortlist.
MCP's July 2026 Spec Deprecates Four Features Your Integration Probably Uses
The MCP 2026-07-28 specification formally deprecates four features: Roots, Sampling, Logging, and the legacy HTTP+SSE transport. Businesses exposing tools or data via MCP now have a 12-month countdown before Tier 1 SDKs drop support entirely. This guide explains what each deprecation means, what replaces it, and how to audit your integration before the clock runs out.
Schema Didn't Boost AI Citations. Here's What It Actually Does
A controlled study of 1,885 pages found adding JSON-LD produced no citation lift on ChatGPT, AI Mode, or AI Overviews. A separate retrieval test found five major AI systems read only visible HTML and ignored schema entirely. Schema is still worth publishing, but for accuracy rather than citations. The lever that actually moves is where you put your answer on the page.
Can AI Agents Actually Buy From You? A Guide to Agent Commerce Readiness
Being recommended by an AI agent is only half the job. The other half is whether that agent can actually get from your homepage to a completed transaction. This guide covers the five points where agent checkout fails, what to publish so it doesn't, and how to test your own site.
MCP Servers: What They Are and Why Your Business Needs One
MCP servers are the connective tissue between AI agents and your live business data. Without one, AI tools answer questions about your company with outdated or incomplete information. This article explains what MCP servers do, who needs them, and how to set your infrastructure up before your competitors do.
Perplexity Optimization: How to Appear in AI Answer Results
Perplexity is now a primary research tool for B2B buyers, yet most brands have zero presence in its answers. This guide breaks down the exact signals Perplexity uses to select cited sources and gives marketers a step-by-step plan to appear in results. From structured data to llms.txt, every fix here has a direct commercial payoff. Brands cited first by AI are 389% more likely to be Googled afterward — so the stakes are real.
How AI Search Engines Find and Evaluate Businesses
AI search engines don't crawl and rank the way Google does. They retrieve, synthesize, and recommend — and the signals they trust are structurally different from classic SEO. This article breaks down exactly how ChatGPT, Perplexity, and Gemini evaluate businesses, which technical signals matter most, and how marketers can close the gap between being indexed and being recommended.
How to Show Up in Google AI Overviews (Without Chasing the Algorithm)
Google AI Overviews pull from a small set of sources Google trusts to answer a query directly. Winning a citation is less about ranking tricks and more about being unambiguously the best-structured answer. This guide covers what earns a spot, how to measure it, and the mistakes that keep good pages invisible.
AI SEO: What It Is and How It Differs from Traditional SEO
AI SEO is no longer a future concept — it is the primary battleground for brand visibility in 2026. This article breaks down exactly how AI SEO differs from traditional SEO, which signals actually matter to AI agents and answer engines, and what practical steps marketers can take today. If your site was built for Google's ten blue links, it is already behind.
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