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Welcome to this week's issue of Unpacking Meaning. If you received this from a friend and enjoy it, ​subscribe here.

Your buyer might never read your homepage, but their AI agent will.

And that AI agent is building a shortlist that could make or break your deal.

The B2B SaaS buying process is quietly changing.

• Procurement teams deploy AI agents to research vendors and compare features.
• Sales teams use AI to qualify prospects and gather competitive intelligence.
• Decision-makers let AI agents handle the heavy lifting of vendor discovery, then review the shortlist these agents create.

This creates what I call the "dual-audience problem." Your messaging needs to satisfy both human psychology and machine parsing.

Most B2B SaaS companies aren't prepared for this shift. They're still optimizing for human attention spans while AI agents are already scanning their sites, building vendor comparisons, and influencing buying decisions.

When emotional hooks meet algorithmic logic

The old messaging playbook relied on emotional hooks to grab attention, benefit-heavy headlines that "spoke to pain," persuasive copy that built desire, and social proof to overcome objections. This approach worked because humans made buying decisions with their emotions and justified them with logic.

But AI agents don't have emotions. They scan for structured data, not emotional triggers. They parse feature lists, not benefit statements. They compare specifications, not brand stories. They flag inconsistencies that humans might miss entirely.

The challenge isn't that emotional messaging is dead, humans still need to feel confident about their decisions. The challenge is that your copy now needs to work on two completely different levels simultaneously.

The agent-ready messaging framework

After analyzing dozens of B2B SaaS sites through both human and AI lenses, I've identified four critical dimensions that determine whether your messaging works for both audiences.

1) Crawlability is about semantic clarity.

Can AI agents easily extract and understand your key information?

When I run client homepages through Claude or ChatGPT and ask "What does this company do, who do they serve, and how are they different?" the results are often shocking. Companies that seem clear to humans produce confused, generic responses from AI. The problem isn't the AI, it's that the messaging lacks the structural clarity that both humans and machines need to process information efficiently.

2) Consistency becomes critical when AI agents are cross-referencing your claims across multiple touchpoints.

Humans might not notice if your homepage says "30% faster deployment" while your case study mentions "25% implementation speed increase." But AI agents flag these discrepancies immediately. They're building detailed comparison matrices, and inconsistencies make you look unreliable or, worse, get you filtered out entirely.

3) Specificity matters because AI agents excel at parsing concrete, measurable details.

Vague benefits like "streamlined workflows" mean nothing to an algorithm (nor to a human tbh). But "reduces manual data entry by 60% for mid-market finance teams using NetSuite" gives both humans and AI something concrete to evaluate. The specificity that helps AI agents also helps human buyers envision themselves using your solution successfully.

4) Redundancy in messaging takes on new importance when you consider how AI agents navigate websites.

They don't follow the same linear path as humans. They might jump directly to your pricing page, then to case studies, then to your API documentation. Your core differentiators need to appear in multiple contexts, restated in ways that make sense for each page's purpose.

How would I solve for this?

This dual-audience challenge is exactly why we've been doubling down on what we call the "UX of copy": messaging that's both psychologically compelling and structurally sound.

We're integrating synthetic research into our process, using AI to not only augment real human insights but also validate copy with AI agents. This means we test every piece of messaging through both lenses:

• Does it resonate with your human buyer personas?
• Can AI agents extract the key information accurately?

Our structured storytelling approach crafts narratives that flow naturally for humans while maintaining the semantic clarity AI agents need. We're working more closely than ever with designers and developers to ensure your messaging architecture supports both human conversion flows and machine parsing.

3 moves you can make today

1. The first step is running an AI audit of your homepage. Use ChatGPT or Claude to analyze your homepage and ask what your company does, who you serve, and how you're different (this is, in short, your positioning). If the AI struggles to answer clearly, so will the procurement agents that are already scanning your site. Compare the responses from each model to get a more accurate and comprehensive idea of how each perceives you.
2. Next, create what I call internally a "specifications sanctuary", a dedicated page with structured, scannable information about features, integrations, security, and compliance. Make it easy for both humans and AI to find and compare your capabilities against alternatives.
3. Finally, standardize your terminology across every touchpoint. Audit your site and channels for inconsistent feature names, benefit claims, and specifications. Create a glossary and ensure every page uses the same language. And btw, a good messaging framework should help you do this naturally.

The competitive window

The companies that figure this out first will have a massive advantage.

While competitors are still trying to understand how to empathize with the “humanness” of their B2B buyers, you should be already capturing both human interest and agent recommendations.

Agent Experience (AX) isn't just coming to B2B SaaS. It's already here. Will you be ready before your competitors figure it out?

DISCOVERY

📡 Introducing: Research Reports

I’m launching a new series of deep dives on my site called Research Reports—for founders, marketers, and copywriters who want to stay ahead of how we understand (and simulate) our customers.

First up:

🧠 The State of Synthetic Research in 2025

Synthetic research—once a fringe experiment—is now being used by marketers, UX teams, and even product leaders to simulate buyer behavior, validate messaging, and test ideas at scale.

This report covers:

• What synthetic research really is (and isn’t)
• Where it’s being used today in SaaS, UX, and GTM teams
• Real-world examples from tools like Synthetic Users, AskRally, TeamGPT, Claude, and more
• Performance benchmarks (yes, there’s actual validation data)
• Limitations, ethical considerations, and where things break down
• A roadmap for how to start using synthetic research now without overrelying on it

⚠️ It’s not a replacement for human research. But it’s a serious edge if you know where to point it.

​📖 Read the full report →​

🎧 Want messaging that actually drives results?

I sat down with the Logan at Demand Gen Confidential to break down how I approach copywriting like a systems designer, not just a writer.

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We dug into:

• Why the “profitability era” demands a smarter messaging strategy
• The real difference between positioning and messaging (most teams blur it)
• My decision-making framework for writing copy that converts
• How AI and synthetic research are changing the game for B2B marketers
• Plus... how drums and punk rock shaped my approach to marketing 🤘

If you care about message–market fit, usable insights, and copy that earns its keep, this one’s worth a listen.

​Tune in here →​

🎙️ Sharpen your message, grow your list, win early customers

I joined Courtney Johnson on Slay the Gatekeeper to talk all things newsletters, messaging, and making your first offer actually convert.

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We covered:

• Why your newsletter should start before you're ready
• The “cheat codes” I use for writing copy that converts
• How to decode your buyer’s decision process (and use it in your content)
• How I use AI tools like Gemini, Claude, and TeamGPT without sounding like an AI
• My favorite trust-building tactic: personalized Loom audits (that don't sound like I know everything)

If you’re building an audience, refining your positioning, or just want your writing to pull more weight—this one’s for you.

​Listen here →​

RESONANCE

Steven Pressfield, Turning Pro

Have a great weekend!

Cheers,

Chris

Chris Silvestri Founder & conversion alchemist

🙌🏻 Let’s be friends (unless you’re a stalker)​

When you're ready, here's a few ways I can help

Not sure where to start? Take our free message-market fit scorecard.​