AI gathers account research, stakeholder context, executive priorities, deal history, CRM context, recent company signals, prior-conversation recaps, and structured call-prep inputs into concise briefs, tables, value pyramids, and meeting plans—often surfaced directly in the seller's workflow or chat tools—so sellers and account managers can personalize outreach, prepare for calls and client meetings, understand deal context, and spot risks or opportunities faster.
The seller or account manager still decides which accounts and opportunities matter, validates the research, signals, and hypotheses, and uses judgment to shape outreach, live conversations, meeting strategy, relationship management, negotiation, and next steps.
AI assembles recent company news, funding events, org changes, CRM history, and likely business priorities into a short prep brief before a seller meeting.
Gong / LinkedIn Sales NavigatorAI monitors signals like funding, hiring, job changes, and press mentions, then summarizes why now may be the right time to reach out or what to address in the next meeting.
Clay / ZoomInfo CopilotAI compiles public signals like earnings calls, interviews, and company updates into a short summary of likely executive priorities and pains before outreach or a meeting.
ChatGPT / ClaudeI help companies navigate AI adoption -- from strategy to production. Whether you are building your first LLM-powered feature or scaling an agentic system, I can help you get it right.
Design and build LLM-powered products and agentic systems
Go from idea to production with a clear implementation roadmap
Build AI with human-in-the-loop in regulated environments
Bring AI sales agents, your CRM data, and your business context into the one place your sellers already work. Run your entire revenue motion without ever leaving Slack.
Prospect, manage pipeline, and close deals in a seller-first workspace. Agents handle the grind so sellers can focus on what matters: building relationships and closing deals.
I do full-cycle sales.
No human SDR. No AI SDR. And I’ve hit 202% of my Q2 quota.
The only thing I use AI for is research. Which is funny — because half of LinkedIn would have you believe AI is replacing salespeople and I'm in trouble.
I use AI to reduce call prep time by 80% and that's what matters.
Before a call, I use it to:
→ Pull everything public on a prospect.
→ Find relational context — how does this company compare to others of its size? What are companies like them usually dealing with? Pattern recognition.
→ Format lists (lots of lists) and generate structured outputs I can actually use.
That's it.
I don't ask it to brainstorm with me.
I don't ask it to be creative and think for me.
I don't ask it to handle objections or plan discovery calls.
I ask it to help me get informed faster.
Because the goal isn't to automate sales. The goal is to spend less time gathering information and more time talking to people and building trust.
AI has changed how I work as a federal sales leader.
I use AI in a few practical ways:
1) Internally, Michael Broadwood has created different GPTs for things like building slide decks, internal messaging and writing support. I use the internal GPT environment to access the IGEL knowledge base and compile information. For example, when I need a white paper or a one-page brief for a partner or customer, or to understand how IGEL fits a specific government program.
2) I use ChatGPT for my daily schedules and prioritization. I take my calendar, my to-dos and screenshots of tasks from Evernote, dump them into ChatGPT and ask it to prioritize them for me. It is not always perfect, but it puts some logic into the list and gets me in the ballpark. Then I use that to build a working document for the day, where I plan my day-almost down to the minute.
3) And I also use AI to do quick research before client calls. If I have a call about a specific program a partner is working on, I can run a quick AI search, get a high-level understanding of the program and share it with the team before the meeting. It gives the team a starting point, gets us in sync, and helps us understand whether we may be a fit for that platform or opportunity.
In federal sales, AI helps me get smarter, maximize productivity and avoid wasting other people's time, but it does not replace the fundamentals. We still need to figure out how people prefer to communicate, find ways to differentiate ourselves, stay persistent and build our network. AI helps us be more efficient. But what we do with that efficiency is still up to us.
Hacking my way to P-Club using AI as a sales rep. Here's what's working:
1. Claude MCP + CRM + AI enrichment tool to make value pyramids, company initiatives, goals, etc: Build a .MD file that's really good at it, and you can just plug in top accounts to learn your approach in 5 minutes. Outcome is .html files you can review as a dashboard.
2. Claude MCP + CRM + LinkedIn Sales Nav Connector + AI signal enrichment tool (I use Backstory) + Apollo: This is the crazy one. Automatically prioritize accounts > use value pyramid memory > build prospect list > write emails > *human review* send emails. 10~20 great emails a day on autopilot. Closest I've felt to being a hacker.
3. Important meetings moments feed: (CRM + AI signal Enrichment) this is a uniquely powerful one. When anyone at my company (like an exec) connects with anyone across my book of business, I get a notification. For example, our head of product meets with a head of product at a different company to network. Sean comes knocking for intros.
4. Pipeline weakness signals (CRM+ AI Signal Enrichment) : Got a signal engine set up over my forecasting tool that tells me what opps I'm winning and losing. Spend a lot of time trying to strengthen the weak ones. Think Clari, but much more memory/stronger AI machine learning modeling using activity signals. Gives me recommendations for actual actions.
5. Gift card or swag bribing glory: this one is a bit controversial, but can work if you do it right. Gift cards are currently an 18:1 ROI for pipeline development. I vibe coded a swag landing page that showcases my offering in <5 min and they can unlock the custom swag. Possible good way for your BDR to meet with IC's/manager level to learn more info about the company. Doesn't have to be you, so you can keep separation. It's not a play for execs.
What else are people using AI for right now? Teach me something!
HubSpot just quietly let AI agents run inside your workflows.
The new "Run Agent" action (private beta) drops any Breeze agent in as a workflow step. Not a separate tool. An actual node in your automation.
A CRM event fires it → you pick the data the agent sees → it reasons → the output updates the record, routes the owner, or sends the follow-up.
Three I'd build first:
1- Form submitted → agent scores the lead → route to the right rep
2- Deal stage changes → agent briefs the account → alert the rep before the call
3- Ticket created → agent drafts a reply → set priority, notify owner
It's capped at 500 runs a day and free while in beta. That changes when it ships, so test it now.
For RevOps teams, this is the moment AI stops being a sidebar and becomes part of the machine.
What's the first workflow you'd hand to an agent? 👇
#HubSpot #RevOps #BreezeAI #AIAgents #SalesOps
Here are 10 things I now use AI for every single day to help us close more sales:
PS - free AI sales coach that helps you do all of this yourself (Link below)
1. Build call plans using P.P.O. — Purpose, Plan, Outcome. You send it the account, persona, stage, and meeting goal. It builds you a plan so you walk into every call knowing exactly why you're there, what you're covering, and what decision you're driving toward. Strong calls are designed, not improvised.
2. Turn call notes into follow-up emails in under 2 minutes. Paste in your notes and it writes a clean recap with the pain you uncovered, the business impact, the agreed next step, who owns it, and the deadline. Your buyer gets clarity. You stay in control of the deal.
3. Build discovery questions using F.A.L.L. — Frame, Ask, Listen, Layer. Give it the persona and deal context and it builds questions that make discovery feel like a real conversation. Not an interrogation. Not a checklist. The kind of call where the buyer starts selling themselves.
4. Pressure-test deals against the 3 Whys — Why anything, why us, why now. Paste in a deal summary and it tells you whether you actually have a deal or just an opportunity someone forgot to disqualify. Most pipeline problems are visibility problems.
5. Handle objections using AIA — Acknowledge, Isolate, Answer. Send it the exact objection word for word and it gives you a response that doesn't sound defensive, doesn't over-explain, and doesn't give ground you don't need to give.
6. Build multi-threading plans using the 5x8 Methodology. Tell it the account and your current contact. It helps you identify the 5 people you should be engaging and maps out how to get there. Single-threaded deals die. This is how you fix that before it's too late.
7. Test whether your champion is real or just friendly. There's a difference between someone who likes you and someone who will go to bat for you internally. It pressure-tests for Power, Pain, and Personal Win so you stop confusing access with influence.
8. Script your next steps before every call ends. Before the call, it helps you plan exactly how to confirm value, prescribe the next step, and get the next meeting booked before you hang up.
9. Clean up your forecast using real criteria. Give it your active opportunities and it classifies them as Best Case, Most Likely, or Commit based on whether budget is confirmed, the business case is built, technical sign-off is done, legal is in motion, exec alignment is real, and there is a clear path to signature.
10. Sort your day by actual revenue impact. It helps you separate what moves pipeline from what just feels productive. Prospecting, deal progression, executive access, mutual action plans, call prep, follow-up — versus the admin that fills a calendar but doesn't fill a quota.
Free AI sales coach to help you do this yourself: https://lnkd.in/epxVqjPP
If you want me to coach you directly: https://lnkd.in/exDqSB6S
My outbound activity is up over 500%. My cold call volume is up over 1,200%. And I haven't added a single hour to my week.
Notion hasn't changed how I sell — but it's completely changed how I spend my time.
The hours I used to spend reading the news, scanning alerts, and trying to turn it all into something I could actually tie to Notion's value and bring into prospect conversations? Most of that happens now while I'm asleep.
In this video I walk through one of the many automated workflows I've built for myself and run every single day.
It scans all 75 accounts in my book of business, surfaces the breaking news and hot topics for specific accounts, and flags the persistent themes showing up across all of them — the shared challenges I can build a real point of view around. Then it takes that POV and automatically drafts targeted cold outreach against it.
All before I wake up.
Since I rolled this out at the start of May, that jump in activity has directly sourced more than $300K in new pipeline — not because I'm working more hours, but because the prep and the POV building are already done before I sit down.
I get to spend my time on the part that actually closes deals — the conversations.
If you're a sales leader and you want to learn how to replicate workflows like this for you or your team, comment "Custom Agent" below and I'll reach out — or just DM me directly.
Sharing something super useful for folks working in HubSpot. HubSpot has added a new workflow action called "Run Agent" that lets you place an AI agent inside an automation. Up to now, workflow steps have mostly been mechanical, things like sending an email or updating a property. This action is different, because it hands the thinking task to Breeze AI agent, gets a result back, and then passes that result to whatever step comes next.
Now you get to control three things: which agent runs, what information it receives, and how the answer comes back. The answer can return as plain text, or as structured data, which means specific named fields you define up front such as company size or industry. The structured option tends to be the more useful one for automation, because each field can flow cleanly into later steps like updating a record or branching the contact down a different path.
HubSpot gives two example use cases that make it concrete. A Company Research agent can pull together a summary of a prospect's company and write it onto the record before a sales rep makes the first call. A Customer Health agent can score an account into a category, and the workflow then routes healthy and at-risk contacts down different branches automatically. The common thread is that the agent handles the judgment step, and the workflow handles everything around it.
A few practical notes if you want to try it. It is currently in beta, capped at 100 runs per day, free during the beta but credit-based once it launches fully, and it needs a Professional or Enterprise plan. One thing worth knowing: the agent dropdown only shows agents from HubSpot's Breeze ecosystem, so you cannot plug in an external agent here. Still, it is a meaningful shift in what HubSpot workflows can do, and worth a look if automation is part of your day. This is a Beta feature. :)
PS: This will only work if you have installed agents in the first place. :)
Learn More: https://lnkd.in/g4Svqs2c
#RevOps #HubSpot #GTMEngineering #MarketingOps #AIautomation
Most salespeople are terrified of AI. I’m not.
AI is not killing great salespeople.
It’s exposing transactional ones.
And after 25+ years carrying a quota at the highest levels for AT&T, Verizon, T-Mobile, and Microsoft I believe most people are misunderstanding what’s actually happening right now.
For years, average sellers survived because information itself created leverage.
Customers needed us to:
• Explain products
• Gather information
• Compare vendors
• Translate complexity
• Summarize capabilities
• Coordinate resources
AI is rapidly erasing that advantage.
And honestly?
Good.
Because the best salespeople were never valuable because they had information.
They were valuable because they understood PEOPLE.
According to McKinsey, generative AI could automate up to 60–70% of the activities employees spend time doing today.
Gartner predicts AI agents will soon handle a massive percentage of routine B2B sales interactions.
And Salesforce research shows most buyers now prefer self-service research before ever talking to a salesperson.
That reality terrifies many people in sales.
It doesn’t terrify me at all.
Because once information becomes commoditized…
Trust becomes the differentiator.
AI can summarize a meeting.
But it cannot sit across from an exhausted executive wondering whether this decision could impact their career.
AI can write an email.
But it cannot genuinely understand pressure, politics, fear, burnout, uncertainty, ego, or ambition inside an organization.
AI can automate outreach.
But it cannot earn trust over years of consistency.
That is still profoundly human work.
And ironically, AI is forcing sales back toward what it was always supposed to be:
Human.
The people who are going to dominate this next era are the ones who can:
• Build trust at scale
• Create emotional safety
• Navigate ambiguity
• Understand organizational politics
• Stay calm under pressure
• Connect dots others miss
• Build ecosystems of relationships that survive change
• Make customers feel seen and understood
That’s the future.
I use AI every single day.
Religiously.
It helps me:
• Research organizations in minutes instead of hours
• Understand executive priorities
• Personalize messaging at scale
• Frame strategic meeting hypotheses
• Identify whitespace opportunities
• Analyze negotiation dynamics
• Build better outreach faster
What once took teams days now happens in minutes.
Technology amplifies the person using it.
If the seller lacks empathy, curiosity, discipline, strategic thinking, emotional intelligence, or authentic care for people…
AI simply scales mediocrity faster.
Do you think AI will commoditize salespeople or force the profession to evolve into something far more valuable?
For my entire playbook, check out "Moneyball Sales"
📘 Paperback: https://lnkd.in/gHunVM8R
📱 Kindle: https://lnkd.in/g-3N52Hu
🎧 Audible: https://lnkd.in/gdY6nHkw
All proceeds go to The Michael J. Fox Foundation for Parkinson's Research
What does an Agent first Sales person look like? Marc Benioff said something in the latest SaaStr Podcast that really sharpened my thinking. He said "When I now write a V2MOM* I always have a Salesforce executive and Agent with me....I like having an AI Partner...it is another tool in the toolchest.."
I've used Copilot, AonGPT, ChatGPT, Gemini (yet to fully immerse myself in Claude) for sometime to support my client interactions and sales processes for myself and the team. Getting to the crux of the problem for an enterprise sales person; deals are complex, especially at Aon. We don't struggle with a lack of capability or content but we do need to maximise the following:
The information across teams
High quality and consistent deal qualification
Utilisation of internal expertise
Our time to prepare deeply for every client interaction
Internal relationship mapping
If we get this right we always show up informed and can create tangible value for our clients.
This is how I use an agent most effectively. At Aon we use Microsoft Co-pilot so this is where I have built my agent called 'Aon Sales and Client Insights'. The goal is simple; 'Help me (and others) think more strategically before every client interaction'.
My agent
The UX is simple, I have created 7 bespoke prompts that I can choose to start my Agent from preparing a client meeting, analysing as sales opportunity, planning Aon Client Leadership support, leveraging our Human Capital and Risk Capital Structure to the next steps in a deal.
I found using AI to help you build these and the agent description and instruction really valuable. I spent time in ChatGPT explaining what I was trying to achieve with my agent to build the prompt title and system prompt. This is fully aligned with how we work at Aon. For example, ACL will not mean too much to someone in another business but at Aon, it is our superpower.
Building out the prompts
Behind this is a clear Agent Description and Instruction. This part is crucial to get right. The description explains what it is and when it should be used, so colleagues (and AI agents, if enabled) can use it effectively. The Instructions direct the behavior of the agent, including its tasks and how it completes them.
Agent Builder for System Prompt
The Instruction is 5,100 characters, I've shown a screenshot above but again, take time and use AI to help write this out. It is a critical part to the effectiveness of the AI. Especially how you want to think about the prompts i.e. for my area of work, a human capital lense is crucial.
Knowledge. What are the sources I want my agent to use to generate responses? Firstly I have allowed the agent to search all websites. In addition I have uploaded X17 specific documents that are proprietary Aon datasets and further specific sites (including Sharepoint sites) that I want it to focus in on. For example, we just released our Human Capital Trends Study, so this is one of those datasets.
So what is an example of the output? I was recently preparing for a meeting with a top 3 global asset management firm.
Using one of my prompts the Agent provided me with a comprehensive overview of the situation for this client based on their annual report and other clients notes I have. It then ran a comparison to their key objectives against the broader market by analysing 17 different Aon datasets (surveys, benchmarks and case studies that I had uploaded) and then provided me with key insights and most importantly, 4 qualification questions to help qualify the gaps in the opportunity.
What I love about this is whether you are in HR, Customer Success, Broking or Finance, this is completely scalable. I can deploy this to my sales team and we can iterate to ensure this is going to deliver best value today and in the future. It helps focus your meeting prep and reduce time looking for information.
As our CEO, Greg Case , said recently "We are a firm of 60,000 colleagues today....we do not aspire to be a 30,000 colleague firm in the future doing the same work we do today, we are committed to a firm of 60,000 colleagues using AI to deliver to deliver more value for our clients...".
For me, this is such a great demonstration of the value of AI to ultimately deliver better decisions to our clients.
I'd be curious to understand how others are using Agents in this space.
*V2MOM is a management and communication process used by the team at Salesforce. It is an acronym that stands for vision, values, mission, objectives, and measures.