What's up, it's Zayd.

Something weird is happening in B2B sales. People are getting so paranoid about AI-generated outreach that they're starting to call human-written messages "AI slop."

I see it constantly now. Someone posts a thoughtful, well-researched message, and the first comment is always "Ugh, more AI garbage," but actually it was written by a human who spent 20 minutes researching the prospect.

Meanwhile, the same people stay silent when I share actual AI-generated messages that get enthusiastic responses. There's a fascinating psychology at play here and it's changing how outbound sales actually works.

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The Pattern That Reveals Everything

Here's what happens every week on LinkedIn:

1. Someone posts: "AI outreach is garbage, stop sending me robot messages"

2. I reply with actual Valley messages that got positive responses

3. Complete silence from the original poster

Example Valley Message That Got a Demo: "Saw your recent Series A announcement and how you mentioned scaling challenges in the TechCrunch interview. We work with similar companies who face the same issue. Happy to share what's worked for them if you're interested."

Prospect Reply: "This is incredibly well researched. Let's hop on a call."

Where's the outrage now?

The Great AI Messaging Confusion

People have developed what I call "AI radar," but it's completely miscalibrated. They're identifying the wrong signals as "artificial."

What People Think Indicates AI:

• Any mention of recent company news

• Reference to LinkedIn posts or content

• Personalized details about their business

• Professional, polished writing

What Actually Indicates Bad AI:

• Generic compliments ("I was impressed by...")

• Vague value propositions

• Template language ("I stumbled across your profile")

• No specific research or context

The irony is that good AI-generated messages often feel more human than the lazy templates humans have been using for years.

The Bias Breakdown

I've analyzed thousands of outreach messages, and there's a clear pattern in what people label as "AI":

Messages Called "AI" (Even When Human-Written):

• "Noticed you recently raised funding..."

• "Saw your post about hiring challenges..."

• "Your company's growth in the logistics space..."

Messages NOT Called "AI" (Even When They're Templates):

• "Hope you're doing well!"

• "Quick question about your company..."

• "I'd love to pick your brain..."

The bias is backwards. We're suspicious of research and personalization…the things that literally make outreach better.

The Real Quality Spectrum

Here's how messaging quality actually breaks down:

Terrible (Whether Human or AI): "Hey [NAME], noticed you work at [COMPANY]..."

Bad: "Hi Sarah, I was impressed by your work in marketing..."

Good: "Saw your recent post about the challenges of scaling content production. We've helped similar companies reduce content creation time by 60%..."

Excellent: "Noticed your team just posted for a VP of Sales role, and in your recent interview you mentioned the challenge of scaling pipeline without adding headcount. Similar companies we work with have solved this by..."

The quality boils down to research, relevance, and value.

Why the Silence When I Share Good Examples?

When I post actual Valley messages that get positive responses, the "AI is ruining sales" crowd suddenly has nothing to say. Why?

Cognitive Dissonance 

Admitting good AI outreach exists means acknowledging they might be wrong about the entire category. It's easier to stay outraged than admit nuance exists.

Moving Goalposts 

When shown effective AI messages, they shift to "well, that's different" or "that's not really AI." The definition keeps changing to preserve their position.

Investment Protection 

Many of the loudest critics are selling courses, books, or services about "human-first" outreach. Good AI messaging threatens their business model.

The Valley Messaging Engine

Since everyone asks how we generate 30-40% response rates, here's our actual process:

Layer 1: Intent Identification

• Website visitor tracking

• Content engagement monitoring

• Social media activity analysis

• Company news and funding alerts

Layer 2: Research Depth

• Individual: LinkedIn posts, Twitter, podcasts, interviews

• Company: Recent news, competitor analysis, strategic initiatives

• Industry: Market trends, regulatory changes, growth headwinds

Layer 3: Message Construction

• Lead with specific, recent context

• Connect to probable business challenge

• Offer relevant value or insight

• Include soft call-to-action

Layer 4: Human Oversight

• Review for accuracy and tone

• Customize based on relationship warmth

• Approve before sending

The result is messages that feel personal because they are personal, even when AI helps write them.

The Ironic Truth

The people complaining loudest about AI messaging are often the ones sending the worst human-written templates:

"Hope this email finds you well. I wanted to reach out because I think there might be some synergies between our companies..."

Meanwhile, our AI-generated messages include details like:

• Specific quotes from recent interviews

• References to competitor moves

• Mentions of new hires by name

• Context about recent company milestones

Whether written by humans or AI, good outreach has these characteristics:

• Specific Context: References something recent and relevant, not generic company information.

• Clear Value Proposition: Explains exactly what you offer and why it matters to them specifically.

• Proof Points: Includes examples of similar companies or situations where you've helped.

• Soft Approach: Asks questions or offers information rather than pushing for meetings.

• Natural Language: Sounds conversational, not corporate or template-like.

The Future of Outbound

The AI messaging bias is creating an interesting opportunity. While everyone argues about whether AI is good or bad, the companies using AI well are quietly booking more meetings.

The future belongs to teams who can:

• Use AI to do better research faster

• Generate personalized messages at scale

• Maintain human oversight for quality

• Focus on value rather than volume

Meanwhile, the purists will keep sending "Hope you're doing well" emails and wondering why their response rates are declining. Next time you see someone complaining about AI outreach, ask them to show you the messages they're receiving. I guarantee 99% are garbage templates, not actual AI research and personalization.

Like with anything, don't judge the entire category by the worst examples.

How I Can Help?

Let me book sales calls for you while you’re battling the bots and the Brads. Seriously.

I built Valley to be your automated SDR and empower AEs. Get started today and watch your calendar fill up with qualified leads.

How can we work together 🏔️

1. See more of Valley’s messaging examples, feel free to roast them: https://joinvalley.notion.site/

2. Generate more demos for your company using LinkedIn: https://meetings.hubspot.com/zayd-from-valley/tryvalley
   

3. Become a Valley partner and get 20% recurring commission for every user you bring in: https://withvalley.notion.site/valley-affiliate-partner-program