AI-enriched prospect research, account targeting, scoring, prioritization, routing, sequencing, and outbound orchestration

Most AI sales tools answer questions. https://t.co/j9G9olW0LT wants Claude and ChatGPT to actually run the outreach campaign.

https://t.co/j9G9olW0LT made its revenue execution platform callable directly from Claude and ChatGPT, letting sellers ask their AI assistant in plain English to build prospect lists, enrich buyer contacts, launch outreach sequences, and prep meetings, then have it actually execute the workflow rather than just summarize data. The company frames the CRM as the system of record and itself as the system of action, and the launch follows its recent Enterprise Forward Deployment announcement.

The distinction https://t.co/j9G9olW0LT is drawing, execution versus retrieval, is the real fault line forming in enterprise AI right now. An assistant that can answer questions about your pipeline is a nice feature. An assistant that can build the list, write the outreach, and start the sequence Monday is a different category of tool, and it only works if something behind the conversation actually holds the customer context to act on. Expect more vendors to compete on becoming that execution layer rather than another chat interface bolted onto a CRM.

AI made me faster at sales.
That turned out to be the least interesting part.

I work in business development, and I use AI almost every day for:
• Researching accounts
• Preparing for calls
• Writing outreach
• Summarising conversations
• Following up with prospects

Sometimes it gives me something genuinely useful.
Other times, it gives me a perfectly written email that I would never send.

The difference is usually context.

AI on its own doesn’t know:
• Someone from our team spoke to the company six months ago
• What the prospect cared about
• Why the conversation stopped
• What has changed since then
• Whether there’s a genuine reason to reconnect now

But when I started using AI alongside HubSpot and the other tools in my workflow, the picture became much clearer.

AI helps me work faster.
The context helps me decide who is worth contacting, what might matter to them and whether I have something relevant to say.

That distinction matters because my manager, Joshua Mathew, is not measuring success by the number of emails AI helps me produce.

It's more about whether those emails lead to conversations, meetings and qualified opportunities.

That’s why the thinking behind HubSpot’s new Agentic Customer Platform clicked for me.

It isn’t simply about adding another AI tool.
It’s about bringing customer data, business context, people and AI agents together, so the AI working with me knows more than what I typed into a prompt.

I work at HubSpot, so of course I’m biased.

But from my view:
AI without context can make us look busier.
AI with context has a much better chance of making us useful.

Has AI improved actual outcomes for your team yet, or mainly increased output?

Also, with Spider-Man all over my personal feed lately, this meme felt pretty apt.

Here are 3 must-run GTM plays in 2026. Clay released Workflows last week, so I built all 3 to see how far it goes.

It is a visual canvas where you wire the trigger, the logic, the agents, and data into one play. While a table is linear, a workflow can branch, apply conditional logic, and use code.

𝗦𝗶𝗴𝗻𝗮𝗹-𝗯𝗮𝘀𝗲𝗱 𝗼𝘂𝘁𝗿𝗲𝗮𝗰𝗵

An account enters your ICP audience, a signal fires, and the workflow scores fit, splits by tier, researches the account, picks the contact, assigns an owner and drafts the message.

Tier 1 goes out on all 3 channels. Tier 2 on LinkedIn and email. Tier 3 on email only.

𝗜𝗻𝗯𝗼𝘂𝗻𝗱 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗼𝗻

The moment a form lands, Clay enriches, scores fit, splits by tier and segment, assigns the best person on the team and drafts the reply.

Slack gets the notification, the rep gets the draft. The human stays in the loop, everything before them is done.

𝗔𝗕𝗠 𝗼𝗿𝗰𝗵𝗲𝘀𝘁𝗿𝗮𝘁𝗶𝗼𝗻

Ad spend and rep time go to top accounts only, and the tier decides how much you spend.

Tier 1 gets ads and a rep by phone or LinkedIn. Tier 2 gets ads plus an email and LinkedIn sequence. Tier 3 gets content nurture.

3 things I learned building these:

1. Double down on what is already working. Start by converting your best-performing tables into sleek workflows. One-click process - thanks, Clay!

2. Conditional nodes consume no credits and no actions. Only enrichment and AI work do. So branch freely, and put the expensive nodes as late in the play as you can.

3. You cannot build search into a workflow yet, so "find me the best 5 people at this account" is not a play today. The contacts have to already be in your audience.

What was the first play you built with Workflows?

The more I use AI in sales, the less I worry about it replacing me.
Today I was doing my usual B2B work: looking for new clients, checking companies, updating CRM, writing emails. AI was there for most of it. Research, drafts, summaries, ideas. Things that used to take hours now take minutes.

And I love that. I have absolutely no nostalgia for spending three hours doing something AI can now do in ten minutes. 
After 20+ years in B2B sales, I’ve learned that people come back when they trust you and know they can rely on you. No perfect email or presentation can replace that.
Relationships are still built over a cup of coffee. Or, in Finland, sometimes in the sauna 😅
AI can make me faster, better prepared, and probably more organized than I naturally deserve to be.
But it can’t build 20 years of reputation for me!
And strangely enough, the more AI we have around us, the more I think we start to value something very old-fashioned: a real conversation with another human being.
So no, I’m not afraid of AI replacing me.

And you? Are you worried that AI might replace you one day?.

I use AI tools daily to find leads and capture meeting notes, but I never use them to mass generate emails or DMs.

These tools are great for almost every phase of the sales process.

But I think most people can spot AI slop miles away, which usually results in an instant lost of trust.

My strategy is to let AI help me with things like desk research, but when it comes to the actual human interaction, I just do it myself.

Perhaps AI will get better at copying my personal writing style and thinking, but until then, I’ll just do this part manually.

I pulled ~1,000 accounts that show propensity to utilize LaunchDarkly.

My next step was NOT to unleash AI SDRs and bombard those 1,000 accounts with brute force pretending to be “personalization at scale.”

Instead, I went through multiple rounds of custom AI prompts to narrow the list down to 50 accounts.

Then, finished with some manual review and assigned the much smaller list of accounts to AEs to begin outreach.

We set 5 quality meetings within 2 days of assignment.

And then improved systems for surfacing accounts to remove the manual prompting process altogether.

I’ve yet to see anyone have success with the approach of “load up the AI Spam Cannon and blast every potential lead.”

So instead of using AI to go wide as fast as possible, I’m using AI to get narrow as fast as possible. And then trusting my AEs to use creativity + humanity to break through the noise and earn meetings in our narrowed focus accounts.

If you’d like a glimpse of how I use AI in my sales org, you can grab a starter prompt guide here: https://lnkd.in/gKpSUNtj

When account information, intent data, partner context, and buyer engagement all live in different systems, revenue teams have to piece together the story before they know how to engage. By the time they have the full picture, the moment has passed or a competitor has gotten there first.

When signals are fragmented across tools, revenue professionals lose time assembling the picture. When that picture is incomplete, the actions they take are less precise. On the other hand, if that context shows up where teams already work, they can prioritize faster, engage the right people sooner, and take the next best steps with more confidence.

The Gong ecosystem is built to close that gap by bringing key data and signals into the same place reps already work. That's why we're excited to now offer 400+ integrations through the Gong Collective, spanning the CRM, data, and foundational AI tools revenue teams already run on.

I have a Google Sheet that fills up with new leads whenever they come in for our product. I run a separate chat connected to Bright Data for search, Google Sheets, and Gmail. It looks up extra information on each lead, fills in the missing fields, and drafts a personalized email saved directly into Gmail.

Not long ago I’d have done a good chunk of this by hand. Now I hand over most of the clicking to AI. I still read every draft before it goes out and sometimes do adjustments. Nothing sends without me.

Do you use AI to run your sales team's outbound?

I'll die on this hill:

I use AI for:

• Buyer profile research (background, niche, role tenure)
• Signal detection across LinkedIn
• Lead scoring against ICP fit
• Reply triage and conversation state classification

Not everything, though:

Sales teams that fully rely on AI to write every message are the ones with 2% reply rates.
We send thousands of DMs across our team.
Voice consistency at scale needs automation.

I don't use AI for:

• The actual opener phrasing
• The first reply to a curious prospect
• Earning trust on the first message
• Spotting which conversations are worth my reps' time
• Firing off generic "I hope this finds you well" DMs

Don't run a sales team like a script - the relevance layer still needs a human brain on it.

AI can help the sales process. But it can also hinder it.

I think we've all been guilty of this.
Start a chat with AI.
Get some good info.
Then use it.

Without checking it first.

I love using AI to support the sales process. It's helping me conduct research.

Build my point of view before I reach out.

But there's a non-negotiable step in my process.
The manual one.
Cross-check the information. Make sure it's accurate.

Then adjust accordingly.

Because the moment a buyer spots something that's wrong, you don't just lose the point.

You lose the trust.

And trust is the one thing AI can't rebuild for you.