AI should empowerpeople, not replace us.

We’ve built an AI operating stack that’s helping our recruiting firm move faster without adding more admin overhead.

Current stack:

- AI sourcing workflow to identify candidate leads
- Data enrichment workflow to improve contact and company context
- LLM + MCP connection to read/write directly in our CRM
- AI roll-up workflow to prep outreach-ready records
- Email + texting workflows for faster candidate response
- Social media content agent and scheduler for consistent daily posting and client development

What this does for us:

- Frees recruiters from low-value admin work
- Keeps CRM data cleaner and more current
- Speeds up candidate identification and outreach
- Improves consistency in market visibility and brand presence

We’re doing this with a ~400,000-person database, and it’s made a major impact on execution speed.

If you want the exact framework, comment SYSTEM and I’ll send it.

I've been collaborating with Claude Code for several months on developing a comprehensive recruiter sourcing screener.

Key features include:

- Sourcing candidates from platforms such as Meetup, GitHub, LinkedIn, and other repositories, including Kaggle.
- Scoring candidates to identify the best fits.
- Engage candidates from companies that are actively posting jobs for the roles I aim to fill.
- Eliminating contractors from the candidate pool.
- Providing a concise shortlist of candidates for direct communication.

This innovative approach streamlines the recruitment process and enhances the quality of candidate selection.

83% of sales teams are using AI.

83% of them are getting generic garbage back.

I know because I was one of them.

A year ago I asked an AI tool to write me a cold outreach message for a San Diego business owner. What I got back read like a press release. No context. No pain point. No reason to respond.

The problem wasn't the tool. It was my input.

Here's what I've found after testing this daily: AI is only as good as the instructions you give it. Vague in, vague out. Specific in, you get something actually usable.

So I built a prompt I now use for every cold email. Copy it:
"Write a cold email for a San Diego business owner. Here is the company website: [INSERT URL]. Here is who I am emailing and their title: [INSERT NAME AND TITLE]. Subject line: one line that shows clear value to them, nothing clever. Paragraph one: one sentence on who I am and my legitimacy, one sentence on what I'm offering. Paragraph two: two sentences max. Show I've done homework on their business. Paint a quick picture of what we could do together and what I might need from them. Paragraph three: two sentences. Direct call to action. Include a phone number so they don't have to go back and forth." 📋

That's the difference between a generic blast and something that feels like it was written specifically for them. Because now it is.

Here's the bigger lesson for San Diego business owners reading this:
Your wireless setup probably hasn't been reviewed in two to three years. Most haven't. And your carrier isn't calling to offer you a better deal. That's not how it works.

But when you know your options, you have leverage. Sometimes folding T-Mobile into your current setup isn't about switching. It's about having a real choice at the table. 📲

What does your cold outreach look like right now? Are you using AI to build it or still writing from scratch?

Quick thought…
I love AI. I sell AI. I use it daily, Co-pilot is literally my co-Pilot and I’m genuinely excited about what it can do.
However, I’m also a bit bored of LinkedIn sounding like it’s been written by LinkedIn for LinkedIn.
So many posts are perfectly structured, perfectly insightful, perfectly optimised… and completely forgettable. No opinion. No edge. No personality. I swear some people don’t even read what they’re posting. Have I been guilty of AI generated posts of course because AI is brilliant. But it can’t have a hot take. It can’t be wrong. It can’t be sarcastic, awkward, or say something and immediately regret it. That’s our job.
For me, the sweet spot is human led AI. Use it to support your thinking, not replace it.
More real voices please. More personality. More humanness.
Anyone else craving that too?

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.