Justin Ratcliff

I have wide-ranging experience but specialize in outbound marketing, go-to-market strategy, and the craft of cold outreach. 

I have hands-on involvement in scaling a startup, working my way through the SDR, Team Leader, Team Manager, and Director roles in a remotely working team that grew from 10 to 150 over the course of 2 years. I have authored extensive scalable standard operating procedures, ran ample sales development training, conducted 100+ SDR/TL/TM interviews, and am a constant student of the craft. I am confident in leadership roles and strive to be an example for others in everything that I do. My goal is to make the day better for those around me. I enjoy the act of public speaking and consider myself an excellent communicator. I have deep experience collaborating in a workspace at global scale and welcome learning from others in all forms. 

While earning my degree, I became adept in behavioral learning and have an understanding of the processes that play a part in individual decision making. Comprehending the patterns that make up human behavior is ever-growing in importance, and when paired with the technologies at our disposal today, can be the difference in a successful vs. failed experience for a client or employee. I use the lessons that I learned through my time working in the mental health field on a daily basis, and it has made me a better business professional as a result.

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I tried the new Apollo x Claude connection, so you didn't have to...but now, you should. 

It's not about replacing people; it's about collapsing 30 mins into 1 min so you can test multiple campaign angles instead of one. 

A half hour of research happened in one conversation. I gave Claude a broad ICP/problem/solution and asked it to find & add contacts to an Apollo sequence. 

Instead of blindly searching, it:

- Identified that the search was too wide-ranging. 
- Searched the web for recent industry data, news, blog posts, & announcements to build context. 
- Matched my insights with vague input. 
- Identified angles I hadn't considered during brainstorming.
- Presented 10 perfect-fit companies with reasoning for each.
- Found decision-makers in Apollo & placed them in a sequence there. 
- Offered email copy addressing pain points. 
- Gave me a manual workflow for what it couldn't automate.

I can also also update//enrich contact data in Apollo directly from Claude chat. 

The bottleneck isn't building lists anymore. Launching three, four, or more campaign ideas in the time it used to take to build one is the reality. 

This is real pipeline alchemy.   

It's going to make the people who adopt it significantly more effective in their roles.

Here's a list of what Claude can currently do within Apollo. 👇

Founding GTM Leader | Built SDR Team 20→150 | Startup Revenue Builder | Enterprise Outbound Specialist

I’ve obtained a new certification: Certificate of Completion: Al Fluency Framework & Foundations from Anthropic 🤖 

This only takes a couple of hours to complete & is well worth it. 

As a daily user, I still learned quite a few things.

Also, you'll notice some of the "best practices" & "must-have workflows" from the gurus are a bit off base. Thoughtful use of AI follows "The 4 D's". 

Knock some of these free certs out this week.

Something you can do today to improve your GTM flow with Claude:

Ask it to build you a "Reddit Mentions Bot" that sends competitor conversations directly into Slack.

Here's what Claude can build for you:

A fully functional Python or Node.js bot that polls Reddit's free API on a schedule, searches specific subreddits for competitor or keyword mentions, scores each result for GTM relevance, deduplicates across polling cycles so you're never seeing the same post twice, & delivers a clean Slack digest via Incoming Webhook using Block Kit formatting.

Make sense? 

Here's the thing: you don't need to understand the code. 

You just need to deploy it. (hint: Claude can help w/ that, too)

Here's what it can't do:
--> LinkedIn - no public API exists, live tracking isn't possible w/o a paid tool
--> X/Twitter - requires a $100/mo API plan to search mentions
--> Run itself - Claude writes the code, you (or a developer) press go

Why Reddit?

Reddit is underrated as a signal source. Buyers openly discuss tools they're switching from, frustrations, & what they're evaluating in real time, in public, for free. (emphasis on free)

It's pipeline intelligence that most teams aren't capturing.

Claude can have the code ready in a single conversation. All you need is a Slack webhook URL & the time to deploy it.

The bottleneck isn't the tech anymore...it's knowing to ask.

AI will always give you an answer. 

Doesn't mean it's the right one.

This is where your AI fluency deteriorates.

Two competencies live in the center of every interaction.

Can you describe what you want & discern if it’s correct?

How well can you articulate what you actually need?

Goals//Constraints//Context//Format//Audience//Tone

Vague Input = Vague Output. 

GTM version: You're using Cowork to automate your post-demo f/u workflow. If you configure the task as "write a f/u email after demos", you'll get the generic output we’re all seeing in our inboxes.

But, if you build the workflow with context (deal stage, prospect's stated objection, next step agreed on the call, etc.), Cowork can produce a f/u that realistically reflects the conversation.

Description is what makes automation feel human.

Now, how confident are you in your knowledge base of industry skills & data?

This is the part that will separate you from others. 

AI outputs sound confident even when they're wrong. 

GTM version: Cowork is configured to pull dormant accounts from your CRM & surface them for re-engagement. The logic is sound, but if you don't have the discernment to catch that half of those accounts were marked dead after a lost deal with a specific competitor (one you still don't have an answer for), you're re-engaging prospects that won’t convert.

Discernment is the filter between AI output & your reputation.

Without it, speed becomes a liability.

Description and Discernment are a loop.

Better description ➡ Better output.
Sharper discernment ➡ Better prompt building.

They make each other stronger over time.

Bad sellers don’t get better w/ AI, they get bad faster. 

Learn your craft before multiplying your mistakes.

Gen AI will send you buyers (if it sees you). Here's how I run a GEO test:

1) To start, prep ~10 queries that customers may ask that would lead to your product. The 4 categories of questions I keep in mind are "discovery", "comparison", "use case", & "intent". 

->Discovery questions are broad but direct. 
- What are the best dialers for sales teams?
- What tools help SDRs make more calls per day?

->Comparison questions are concise & place you against the competition. 
- Compare the top AI dialers for outbound sales in 2026.
- What's the best alternative to [comp 1] or [comp 2]?

->Use case questions are specific & describe task completion.
- How can AI help my sales team 10x their cold call volume?
- What software handles voicemail detection & parallel dialing automatically?

->Intent questions signal buying motivation. 
- I need a dialer that integrates with Apollo & Salesloft; what should I use?
- I need an AI dialer with CRM integrations for outbound sales teams.

Start small but build out & tweak as you go. Each model has their own tendencies to account for...

2) Consider all major outlets in which your buyers may operate. You'll get different results for each generative program & can adjust your site strategy accordingly. 

->The 5 I test:
-Claude
-ChatGPT
-Perplexity
-Gemini
-Copilot

3) Run the queries through each chat program & notate results. We're tracking general mentions, prominent mentions, & missing mentions. 

->Weighted as follows:
-Prominent = 2
-Mentioned = 1
-Missing = 0

->Run the following formula:
-GEO Score = (mentions×1 + prominent×2) / (2 × total queries) × 100

Example: (4 Mentionedx1 + 2 Prominentx2) / (2 x 8 Queries) = 50

->Aim for 60+

4) Assess results & revisit strategy. Research how to make your site more accessible to Gen AI crawling & implement the changes. 

5) Automate it. Claude will write JSX code for a personal GEO tool that you can (super politely) ask (or beg) your dev team to set up. 

You'll need some lift from them to connect backend APIs & for securely deploying the tool on something like Vercel, Netlify, AWS, etc. 

But...this is a high-ROI request. This is one way to stay data-driven in '26.

Check the comments for the prompt I used to build my first GEO tracker. 👇

Vibe coding a lead scraper won't save your quarter. Picking up the phone will.

You can now build tools, automations, & workflows in hours that used to take teams weeks.

The builder communities are full of talk about tools and automations, & almost none about the channels that actually close deals.

Sellers think building replaces selling.

It doesn't.

AI can help you build tools, automate research, create workflows, & scale personalization.

It cannot replace revenue motion.

Revenue still comes from the same places it always has: 
→ Phone 
→ Email 
→ LinkedIn 
→ Conversations 
→ Follow-ups 
→ Pipeline discipline

You can't vibe code your way out of doing the work.

The real advantage? Modern sellers can now build their own leverage.

Need a lead scraper? Build it. Need research automation? Build it. Need outreach personalization? Build it.

Those tools should feed your pipeline, not replace it.

The best sellers in the AI era will have a builder mindset...but will still maintain activity across every channel.

They'll ship tools in the morning but still pick up the phone after lunch.

AI won't replace great sellers, but it'll expose those who have stopped selling.

Vibe code for efficiency. Prospect for production.

Tools create leverage. Activity creates pipeline. You need both.

(P.S. Can't wait to read "The Pragmatic Progemner" 🤣 )

I once watched a GTM motion completely fall apart because of one underperforming rep.

Series A company. Great product. Early traction.

We built the CRM, set up sequences, started booking meetings.

But the rep was chasing everyone remotely relevant:
-airlines 
-healthcare networks 
-SaaS companies 
-legacy enterprises

No focus. No pattern. No results.

A quarter went by & nearly nothing had landed.

So I did what any leader would do: I sat down with the rep & got brutally honest.

We cut every ICP except one: Healthcare systems.

Hit the phones & meetings doubled within 14 days.

Because the messaging was dialed in, we eventually landed a major enterprise healthcare client, w/o ever targeting enterprise accounts specifically.

Focus doesn't limit your upside. It unlocks it.

Figure out what you do best & go talk to the people you help most. 

I still think about that rep when I see a team chasing a handful of ICPs.

The rep was me. 🤷‍♂️

Most people think AI fluency means knowing which tools to use, or how to prompt to get the voice of your favorite sales guru in your next cold email.

It doesn't.

You can use Claude, GPT, & Gemini every single day & still be uninformed about AI.

Listen,

The problem isn't access to AI…everyone has it.

What’s making an impact now is how we deploy it into the world around us.

AI Illiteracy:
➡No thoughts on whether AI even needs to be involved (we’re still better at human things). 
➡No strategy around how to describe what you need (this should arguably take the most time). 
➡No filter on whether the output is actually good (get better at auditing). 
➡No ownership of what happens next (if you lose access to a platform b/c of your AI practices, it’s ultimately on you).

That's not fluency. It’s just usage.

Automate the things that make sense. Execute the rest. 

Learning “The 4D Framework” for AI helps you understand when to delegate tasks, how to describe what you want to accomplish with it, discern between good//bad outputs, & how to think about the responsibility you carry to others when presenting it publicly. 

You could already be strong in one D, but weak in the others.

Don't just get faster...get better.  

It’s too much to cram into this post, but if you’ve not had a chance to dive in, I’ll f/u on the 4Ds this week.

If for nothing else…learn them so you don’t fall for LinkedIn engagement bait.

Your GTM motion is broken.

It's not (always) your reps' fault.


When I audit my own leadership performance, these are the 5 signs I look for, and the fixes I go back to every time:

1: Your reps are pitching different things to different prospects.

→ You haven’t locked an ICP. Reps fill the gap with instinct; do they really understand the problem you solve as you do? 

Fix: Define one segment well & build everything around it.
--
2: You're getting meetings, but demos aren't converting.

→ Your messaging is attracting the wrong buyers. 

Fix: Audit your last 20 demos. What did you fix for ones that closed? What did they have in common? 

That's your real ICP.
--
3: Pipeline looks full, but nothing is closing.

→ Stage definitions don't exist. An “opportunity” is just that & nothing more to your team.  

Fix: Conduct a gap analysis on your sales journey & map your stages. Define what must be true to enter/leave each. 

Make it binary.
--
4: Reps are burned out, and activity is dropping.

→ No playbook means they're winging it every day. Winging it is for the birds (exhausting). 

Fix: Document the sequence, talk tracks, & objection responses. 

Build them a real playbook. Professional sports teams can’t operate w/o one. 

Why should your professional team be any different?
--
5: You've missed forecast 3 months in a row.

→ You're forecasting on gut, not data. Defining stages help w/ this but also…

Fix: Set a pipeline age limit. 

Anything over 60 days without movement gets reviewed or cut. 

This will clean things up.
--
GTM failures get blamed on reps.

Broken reps are usually a symptom, not the cause.

A healthy system removes symptoms.


What would you add to this list? ♻️ Repost if this would help a founder or sales leader in your network.

Before using an AI tool, two decisions have been made, consciously or not.

Most people make them unconsciously, causing problems. 

Delegation mistakes are everywhere.

Not every task should be handed to AI.

Some require:
→ judgment
→ context
→ relationships
→ actual experience

GTM Example: teams letting AI write cold outreach from scratch
 → no buyer context
 → no triggers
 → no voice

It’s faster.

It also kills reply rates.

Being a credible source of knowledge in your field has never been more important. 

The bigger problem? Diligence.

People treat AI output like it's “done.” 

It’s not. 

It’s a draft you’re responsible for.

Your name is on it. Your reputation is attached to it.

The AI won’t be there when a prospect pushes back.

This shows up fast in GTM:
→Forecasts no one pressure-tested
 →Sequences no one actually proofed
→“Insights” pulled from hallucinated summaries

AI didn’t create the problem. Lack of ownership did. 

The tool got you there quicker…but you also created the mess.

Diligence isn't about slowing down. It's about staying in the driver's seat when AI is doing the work.

Use AI aggressively this year.

But...decide when it’s allowed in…and take responsibility for what comes out.

Delegation w/o diligence = leverage without control.

That’s where things break.

AI was supposed to fix my CRM.

Auto-logging…Auto-enrichment…Zero manual entry.

My pipeline was still a mess as I sipped upon my Monday morning coffee (I’m an instant guy, Medaglia D’oro, it’s the business).

Here's what the tools won't fix (the coffee may help):

1) What "Discovery" actually means. 

That's still on you.

Mine used to mean "we talked once." 

I changed it to: problem confirmed, outcomes articulated, & next step on the calendar. 

Things started to split, but made sense for the first time.

Additional Stages ≠ Additional Complexity. 

It’ll slow things down for you. 

And speed up your pipeline. 

2) Whether the person you're talking to can actually sign? 

Also…still on you.

Decision maker confirmed…Yes or No. 

One field. 

Saves you surprises at EOQ.

3) Scrapping stale deals? 

Yeah, that one, too. 

I had 40 open opps. Maybe 10 were real. The other 30 were hiding where my motion was breaking. I hadn’t defined it & the system didn’t know to respond. 

30-day rule: nothing moves, deal drops off the wagon.

Throw em in the strongbox for reengagement campaigns. 

Better tools won't fix bad judgment calls:

Stage definitions, relevant required fields & a ruthless cut rule. 

That's still the job, even when it's you & AI.

Anthropic fed the fear-mongering community today with its theoretical capability data drop.

It’s actually great news for salespeople.

Anthropic analyzed 2 million real conversations with Claude and published a radar chart comparing what AI can do vs. what people are actually using it for.

The gap is massive.

The blue area shows the theoretical capability of AI to perform job tasks today. The red area shows real-world usage. Across almost every knowledge job, the blue area is far larger than the red.

Meaning: AI can do a lot more than people are actually using it for right now.

That gap is the opportunity.

Most people see this and think, “AI is coming for jobs.”


But the more interesting takeaway is this:

-There’s a massive distribution problem.

-The world doesn’t just need builders. 

-It needs people who can sell what AI makes possible.


This is where sales roles become more powerful, not less.

The next generation of great sellers won’t just pitch products.

They’ll:

• Build AI tools to solve customer problems.
• Optimize solutions in a live sales cycle.
• Automate workflows specific to the client.
• Turn ideas into a working process within minutes.

Instead of saying “Let me check with engineering,” they’ll say “Give me 5 minutes, I’ll build it.”

That changes everything.

We're entering a market where:

-Builders who can't sell struggle to distribute their work.

-But sellers who can build with AI become unstoppable.

They control:

• Problem discovery
• Solution design
• Distribution
• Revenue

The chart isn't a warning.

It's a launchpad for those willing to adapt.

The sellers who learn to build with AI will be there when the dust settles.

Most "RevOps" at early-stage startups in '26 are prompt jockeys with a sales title.

Before, it was Salesforce admin.

Now, it's "I set up Clay workflows & connected Apollo to Claude."

That’s more tool configuration than revenue architecture. 

Real RevOps in 2026 looks like this:

→ You own the revenue model, not just the tech stack.
→ You define what "pipeline health" means before the CEO asks.
→ You can audit a forecast & tell the team why it's wrong.
→ You know when AI agents are hallucinating…you're not just the person who turned them on.
→ You know whether to add a new tool & you're willing to axe three old ones to do it.
→ You built the model, not the dashboard. 

AI didn't raise the bar for RevOps, but it did expose who was always just an admin.

The strategists get faster. 

The admins get automated.

Which one are you building toward?

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