I have big concerns that a lot of the AI inundating sales teams today (some of which I've deployed) is not making teams more successful. In many cases, it's doing the opposite. We're providing unnecessary crutches while our muscles atrophy.

Before this series expands into where we're using AI, let's start with what it's being used for.

Broadly, there are two buckets: Automation/workflows and information. In many cases, it's workflows outputting information.

That information usually comes in the form of documents (account research, call summaries, account history, potential pain points/opportunities, etc.).

But most great salespeople I know are audio and visual learners. The five-paragraph essay was never their thing.

That translates to sales, though. Strategic deals are still won and lost in conversations, times when those crutches aren’t available. In those moments, it's easy to lose deals with one verbal misstep if you don’t know your stuff.

How do we get the team to learn information, not just have it? I don’t think all these documents are it.

I don't have a solution yet, but I get pitched a lot (I have a sickness and pick up every cold call for fun), and this problem is only getting worse.

Everyone is talking about AI in sales right now.

So am I.

I’m a big believer in it. We’re building an AI GTM company at Pitstop, and I use AI every day in my own work.

But today I posted a job advert for a Revenue Associate to support me in founder-led sales.

That is not a contradiction.

It is because I think AI will augment salespeople far more than it will eliminate the need for good ones.

AI is already incredibly useful. It can help with research, preparation, summarising calls, drafting follow-up, reducing admin, and generally making sales execution faster and cleaner.

That matters.

But there is still a big difference between supporting execution and owning judgment.

Good sales support is not just about getting tasks done.

It is knowing what matters in a live deal.
It is spotting weak signals early.
It is helping decide where founder time should actually go.
It is maintaining momentum across real conversations, not just generating more activity.

That is why, even as someone building in AI, I wanted to open a role for a person to work alongside me.

I doubt I’m the only one who sees it this way. Even frontier AI companies like Anthropic are actively hiring account executives, sales development, customer success, and sales leadership roles.

That tells you something.

The future of sales is not AI or people. It is AI making good salespeople better.

And it is probably increasing the value of the people with the best judgment, discipline, and commercial instinct.

AI can raise productivity.

I still think great people are the edge.

Curious whether others are seeing the same thing.

Richie Choudhary Thomas Copeman Steve Davies

Here’s every way I currently use AI in sales, no bs:

- Find “lookalike” accounts for deals we’ve recently completed so I can prospect best-fit accounts (thank you Kyle Asay)

- Find the most felt pain points at the exec-level to hypothesize and test in my outreach and discovery strategy. (Shout out to Jen Allen-Knuth for this.)

- Draft my cold emails with an extremely specific messaging matrix - Always editing them before sending. (Got this one from Jason Bay)

- Consolidate prior convos into high-level problem statements to recap on calls. (Nick Cegelski, thank you)


That is it.

Most of the work I actually do is still manual. AI rarely gives me anything I can send out right away.

I don't hate AI.

But I can't stand the nonstop noise. Every conversation doesn't need to be about AI.

I used to spend 45 minutes researching a prospect before every call.

Now I spend 4.

Here’s what I changed — and what I do with the other 41 minutes.

Before, I was manually doing all of it myself:

Scanning their LinkedIn. Reading company news. Googling recent press. Trying to find one personal hook so I didn’t sound like every other rep.

It felt thorough.

It was just slow.

Now I use AI to build a full prospect brief in under 5 minutes.

Their company priorities. Recent wins. Likely pain points. Natural conversation openers.

Same prep. A fraction of the time.

So what do I do with 41 extra minutes?

I make more calls.

I follow up faster.

I actually listen on the call instead of mentally replaying my prep notes.

The research didn’t get worse. It got sharper.

Because I stopped doing the part that doesn’t require me.

This morning I asked what you’re still doing manually because it feels safer.

For most sales reps — it’s prospect research.

Not because it doesn’t matter.

Because your brain is worth more on the call than in the prep.

What would you do with 41 extra minutes a day?

I've built dozens of AI agents across our GTM operation.

Here’s how I decide which one to build -

Most teams think “adding AI” means dropping ChatGPT into one workflow and moving on.

That is not an agentic system.

Agents are:

→ Always-on
→ Trigger-based
→ Making decisions
→ Taking actions

No human in the loop for 90% of the low-value work.

The real question is not “which tool”.

The real question is “where in your GTM does an agent belong”.

Here is the diagnostic I use across 4 functions.

Sales

→ Time from buying signal to first outreach
→ How reps prep discovery (15 minutes of Google = agent)
→ What happens to overnight replies
→ How you choose which deals to push this week

Marketing

→ How you know which campaigns drive pipeline
→ Where competitive intel comes from
→ Time from idea to campaign live
→ Who decides inbound → sales vs nurture

RevOps

→ How clean your CRM data is
→ How many tools a lead touches before a sequence
→ Which reports still live in spreadsheets
→ What breaks when you 2x volume

Customer Success

→ How you detect churn risk early
→ What signals show expansion readiness
→ How manual onboarding feels for the team

Any answer with “too slow”, “manual”, or “we do not” is an agent slot.

Then match to 5 agent types:

→ Research: signals, company intel, tech stack
→ Enrichment: data waterfall, contacts, email verify, CRM gaps
→ Content: sequences, briefs, reports from data
→ Routing: reply tags, scoring, stage updates, alerts
→ Monitoring: churn, pipeline, anomalies, data drift

Start with one.

Pick the slowest, most repetitive, most time-sensitive workflow.

Team size rule:

→ Under 10: Routing first (reply classification or lead scoring)
→ 10–50: Enrichment first (data quality unlocks all)
→ 50+: Monitoring first (what you cannot see hurts you)

I mapped 20 concrete agent builds across Sales, Marketing, RevOps, and CS into one cheat sheet.

AI in sales is one of those things where once you use it, you can't really go back.

And I am not talking about it replacing humans.

I am talking about the efficiency gains.. Not just getting faster, but also producing better outputs.

I love to frame using AI as a way to "make my outside the box ideas & thinking come to life" in a more meaningful way.. With AI being there to question me & challenge how I am thinking about certain scenarios.

It's fun stuff.

One of my favorite recent use cases is call prep and creating exec summaries for clients.

Being able to stitch together unique data sources into one cohesive story in minutes is a huge unlock.

More to come.. Anthony Intelligence (AI)

I spent the last 3 months building AI into my actual sales workflow.

Not theory. Not a course. Real calls, real prospects, real results.

Here's what changed:

Before: 2-3 hours writing proposals
After: 20 minutes. AI does the draft. I clean it up.

Before: Forgetting to follow up by day 7
After: 5-touch sequences written and scheduled automatically

Before: Walking into discovery calls cold
After: I know their pain points, budget signals, and likely objections before I dial

Before: Researching prospects by hand
After: 50 qualified leads in under an hour

I documented everything. 14 chapters. Real prompts. Copy-paste ready.

Called it "The AI Sales Consultant's Playbook."

$37. Link in comments.

If you're in commission sales and still doing this stuff manually — this is the shortcut I wish I had.

Spent the last few weeks thinking about this because I keep seeing posts about AI killing sales and clientfacing roles.

Quick background, Senior AM at a high-ticket consulting firm. 3 years in the role. Work with clients from earlystage to 2 mil + businesses.

Here's my honest take after using AI heavily in my workflow :)

AI is great at tasks. It is terrible at humans.

And account management, at its core, is a human job. Specifically

Clients don't pay for information, they pay for accountability. AI can generate a strategy. It cannot call you out when you're avoiding executing it and That's what I do.

Reading a client's real state ,not what they say, but what they mean . is a skill built over hundreds of conversations. No model has sat through what I've sat through.

When things go sideways (and they always do), clients don't open ChatGPT. They call their AM. Ownership and trust are human things.

My actual workflow >> AI handles prep, research, templates, summaries. I handle judgment, relationships, escalations, and the hard conversations.

Net result: I have more bandwidth for what actually moves the needle.

The role isn't dying. It's being filtered. Average AMs who coast on coordination will struggle. AMs who bring real judgment and use AI as a force multiplier? More valuable than ever.

Anyone else in client success finding this to be true???

You are still researching accounts manually, & it is costing you deals.
I gave Claude one instruction at 8am.
By 8:15, a full prospect brief was done.

No prompts. No back and forth. No wasted time.
Most reps miss the shift.

They speed up tasks, but still lose time.

That is not the real shift.
The real shift is giving it the whole research job,
then coming back to a finished brief.

I dropped a goal into the Cowork tab in Claude Desktop, went for coffee, & came back to a completed document in my folder.

It had already done the work that usually slows reps down.

It read the files, searched the web, worked through the research, & saved the output to my computer.

The brief pulled the only signals that matter before an account meeting:

Recent trigger events, new executives, acquisitions, funding rounds, rebrands, product launches.

Top 3 company priorities, what the business is focused on, how progress is measured, and what each priority is trying to solve.

Top 3 technology investments, where budget is already going, and why. If your product sits near those bets, you are joining an active decision, not trying to create one.

Top 3 business risks, named, sourced, specific. The issues most likely to block those priorities.

That is why this matters.
Good account research is not collecting background information.

It is finding change, budget, pressure, & risk before the conversation starts.
Manual research still gets treated like good prep.

Most of the time, it is just slow admin dressed up as sales work.
Stop researching manually or not at all. Use a focused prompt & get ahead.

I built this as a Claude skill.

You save the instructions once, point Cowork (or Claude Code) to the file, give it a company name, website, and save location, then leave it alone.

For anyone not using Cowork or Claude Code, I adapted the same research framework for Perplexity, ChatGPT, Gemini, and Claude Web.

Claude link: https://lnkd.in/ePn3EeqY
ChatGPT link: https://lnkd.in/eA22JqYP
Perplexity link:https://lnkd.in/e9esfeeT
Gemini link: https://lnkd.in/ePn3EeqY


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I'm running $140K/month selling AI to Fortune 500 companies. All through Claude Code.

No team. No apps. One terminal.

Here's what's inside the Business Brain:

→ The Revenue Architecture — exact folder structure behind a $140K/month operation
→ The Context File — one document that teaches AI your entire business in seconds
→ The Integration Layer — Gmail, Calendar, Airtable, and project management in one CLI
→ The Selective Loading System — AI reads only what's relevant, zero hallucination
→ The Voice Engine — enterprise emails and WhatsApp messages written in your exact tone
→ The Client Intelligence Stack — every deliverable, blocker, and relationship in one place
→ The Sales Framework — ICP scoring, objection handling, and pricing psychology
→ The Runbook Library — 30-minute workflows compressed into single commands
→ The Relationship Layer — auto-loads context on every person before you message them

Before: 14 apps, 3-hour admin mornings, writing the same enterprise email from scratch every time.
After: One terminal. AI already knows the client, the deal, the history, and how I talk.

→ No more Notion, Monday, HubSpot, or switching between 15 apps
→ No more losing context between clients, deals, and relationships
→ No more writing enterprise emails from scratch every time
→ No more 30-minute workflows that should take 3 minutes
→ No more AI that doesn't know your business, your voice, or your clients

Same system I've used to close $300K deals and manage Fortune 500 clients for 18 months.

You're not using AI as a tool.

You're deploying infrastructure that runs your entire business without you.

Like + comment "AI" + repost, and I'll DM it to you.
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