AgentGrow

Get 5 warm Leads per week, on autopilot, using our AI Sales Assistant.
Hit your sales goals & beat quota.

CEO & Cofounder

Generating qualified meetings is harder than ever. Calls are flagged as spam. Emails too. And Sales people deserve to crush their quotas. 10x your Linkedin engagement and generate warm leads, all on autopilot. 

Try it free at www.getagentgrow.com

Founder

Collect IQ

pivot to AgentGrow.
It was the right decision: www.getagentgrow.com

Co-Founder

Census

VP of Sales

Fivetran

Early Seed stage hire. 2x promoted from IC to Director (2nd line) of 25 headcount sales org.
Built from scratch. Not inherited. 3x presidents club winner (Hawaii, Cabo, Belize). 75x revenue growth during tenure (T3D2). Driver, not a passenger.

AE > Manager > Director of Sales

3X a16z backed head of sales, turned founder building for sales people & revenue orgs. Building B2B pipeline has never been harder, and we’re fixing it with our AI Agents. 

If you’ve chatted with me recently on LinkedIn, you may have spoken to my AI prospecting assistant, and I hope you enjoyed the interaction. This is proof that our Agents can start conversations with your prospects. 

We offer a free tier at getagentgrow.com. use it to build pipeline on autopilot.

Hayk C.

Brendan Short

The Signal (.club)

• Separating the signal from the noise — a weekly newsletter on the future of GTM/tech (including AI, obvi)
• Subscribe now (it's free!): www.thesignal.club

Apollo.io

• I was booking ~1,800 meetings/quarter, fully automated (Apollo didn’t have SDRs)
• Read more here: https://www.apollo.io/magazine/how-apollo-tripled-meetings-booked-using-its-own-platform

Product-led sales ("AutoSDR")

Groundswell

• Here is what we learned building Groundswell for 2.5 years: https://www.thesignal.club/p/what-we-learned-building-groundswell
• Started off building in "product-led sales" and then expanded to, what I call, "signal-based selling" (using gen ai to find signals and generate next-best actions)
• Raised $1.6M from Village Global, GTMFund, Henry Schuck, Lars Nilsson, Shaan Puri, and other founders and executives from the world's leading PLG companies including Slack, DocuSign, Rippling, Snowflake, TripActions, Workato, and others
• Had the best co-founders I could ask for, Hari and Nick

Co-founder & CEO

GTMfund

• Limited Partner alongside great GTM leaders in the GTMFund

Limited Partner (LP)

Zoom Video Communications

• Consulted for Zoom starting in Dec 2019
• Joined full-time in 2020 as things got busy due to the pandemic (it was a wild time to be there)
• Led Operations and Enablement for the Global SDR Org (150-person team)

Operations & Enablement (Global SDR Team)

The Revenue Engine (Consultancy)

• While figuring out my next move, I took on some consulting and advising gigs to help B2B SaaS companies build scalable, predictable revenue engines
• I've been lucky to work with some incredible companies and people, including: TripActions, Zoom, Snapwire, WellHealth, LoanBase, Edvo, among others

Owner

OutboundWorks - ACQUIRED

• I joined OutboundWorks as VP Sales as part of their acquisition of my company, Hexa.ai
• We were building “Automated Sales Development”
• I led Sales Development, Sales, Marketing & Customer Success 
• The company was acquired in October 2019

VP Sales

Hexa (acquired by OutboundWorks)

• SaaS Product to help automate XDR work ("AI to replace SDRs" was a horrible tagline... but man, wish LLMs existed back in 2016 when we were working on this problem...)
• Acquired the technology of Brisk.io and merged it with Proleads.io
• Class 17 of The Alchemist Accelerator (6 month program; #1 Enterprise B2B Accelerator in the World)
• Raised $800k in funding
• Acquired for 7-figures in Feb 2018, by OutboundWorks (backed by True Ventures)

Wiser Solutions, Inc.

• 1st full-time employee (started as SDR then AE then Manager)
• Was there from ~$15k MRR to $10M ARR 
• Personally closed $1M+ in first full year selling - online retailers, brands & manufacturers (mid-market and enterprise)
• Built and managed the Sales Team (SDRs, AEs, Sales Engineering, and Sales Ops)
• Wiser was acquired for 8-figures in September 2016

Head Of Sales

Avista Solutions, Inc. - now part of D+H

• Cold-calling from a cubicle from 9-5
• Avista Solutions was acquired by D+H, for $40M (45 employees, in business for 4.5 years)
• I left after Avista was acquired by D+H (cubicle life wasn’t for me)

SDR (before the title existed)

Playing long-term games w/ long-term people ✨ Building Groundswell

Currently writing about the future of gtm/tech, at The Signal. Subscribe now (it’s free): www.TheSignal.club 

I’ve worked at a couple of startups ($0-$10M), a couple of big companies (Zoom Video, Apollo.io), and I’ve started a couple of venture-backed SaaS companies (Hexa.ai, Groundswell).

I’ve been an SDR, AE, Head of Sales, SDR/Ops Leader, and CEO. Jack of all trades, master of none, perhaps. 

I like learning and building. 🤘

Writer

• Separating the signal from the noise—a weekly newsletter on all things GTM tech

Brendan Short 🌊

Sumble is the most interesting GTM technology I’ve come across this year (no joke). Their bread and butter is providing the best tech stack data in the world (via job descriptions, which is clever). But they also can help GTM teams find “rich data” and signals that help present a *unique insight* which is how the best teams/reps in the world are breaking through the noise right now. Here’s what I find incredibly compelling about Sumble:

1/ Tech stack data

This is their sweet spot. If you’re looking to see what companies use Snowflake,  Rippling, whatever - they have it. They pull it from job descriptions. You can do creative things once you have this information (reliably). You can click in and see exactly where Sumble found {technology you care about}, and it’ll show you the actual job post/source.

2/ Identifying internal projects

They’re applying ML to their dataset to generate something they call “Projects.” Things like: Cloud Cost Optimization, Cloud/Data Infrastructure Migration, Design System Migration, Frontend Migration, GenAI, Microservices Migration, Security Infrastructure Modernization.

If you want to know which companies are currently working on one of these projects, it's a no-brainer.

3/ You’ll see the value in under 3 minutes

I’ve shown Sumble to dozens of people this year, and there’s always an aha moment very quickly (even non-technical folks get it immediately). It’s magical to see a product that is so powerful and simple.

It provides immediate context to the reps on who to contact and why.

4/ People data

Once you find a company that’s a fit (based off tech stack, project, or other firmographic data), you can drill into teams and people. Again, they’re a legit ML team (the founders previously sold their company to Google), so they’re doing a lot of technical work to pull this off.

5/ Signals

I’m a fan of signals. :) And they have signals that can notify reps (via CRM or Slack) based on their dataset. Things like: new tech mentioned in JDs, job changers, etc.

6/ Keyword search on JDs

You can search for keywords within job descriptions. So if you’re looking for “Sales Engagement Platform” or whatever, you can find it. The bottleneck is creativity, not technical.

7/ Examples of how I’ve used Sumble this year:

- Companies using Pytorch/Tensorflow w/ 1+ ML/AI Eng
- 5-25 data engineers actively hiring for data engineers + using Snowflake/Databricks/Redshift/BigQuery
- Companies actively hiring for specific titles based on *keyword* (not captured in other tools)
- B2C companies w/ 1+ {specific title} in the US hiring in the last 6 months
- People search for certain teams using SalesLoft/Gong/Outreach/Clay
+ I'll put a few more in the comments

PS: they just added an API!

I convinced Anthony and Abhishek to partner with me/The Signal, because I like the product so much. Thanks for trusting me to help spread the word!

Go try them for free and see the value for yourself → https://lnkd.in/gZBzxdu5

brendan short

Dec 17: AI x GTM Summit, by The Signal | Exploring the future GTM playbook → Writing The Signal | Playing long-term games with long-term people 🫡

In my 13 years in B2B SaaS GTM, I’ve never seen a technology adopted as fast as AI (or as impactful). But, there’s a lot of vaporware. Rox is one of the most impressive teams I’ve seen building in the GTM tech space—here’s why:

1/ The team is cracked

Everything is downstream of that talent (and drive). Ishan, the CEO/Co-founder, previously sold his startup to New Relic for 8-figures and led Growth there for 3 years. He has deep domain expertise.

They’ve built one of the strongest AI eng teams in Silicon Valley. And now they’re assembling a top-tier enterprise GTM team.

2/ Wave # 2 of AI adoption: GTM

Coding and CS drove AI adoption wave # 1. We’re in wave # 2, and GTM is part of this second wave. Every executive feels the pressure to transform with AI, and boards want to see ROI fast. Rox supercharges reps with deeper account context than was ever possible pre-AI.

3/ CRM → data warehouse

Enterprise GTM data is moving from Salesforce to data warehouses. I saw this firsthand, building Groundswell (product usage data lives in the DW, not the CRM). This shift is accelerating. The GTM stack is being rebuilt around the DW, and Rox is building warehouse-native for this new reality.

4/ Targeting the Global 2,000

This is different from every other company in the space. As a result, they can go to a CIO with a clear message of deploying “pre-built agents with enterprise security.” It’s a bold bet that will pay off big if they can crack that market.

5/ Real adoption of Revenue Agents

MIT’s study showed 95% of AI experiments have failed. AI is hard to deploy today. This is why Rox has built an in-house team of Palantir-style FDEs plus McKinsey-style growth strategists to implement Rox deeply into the workflows of teams they work with (usage is real with 400B+ tokens per month). Lemkin has talked about this extensively—the best agents need to be deployed for you, by the customer.

6/ The UI paradigm shift

Anyone who works out of Salesforce knows the pain of the UI. The future is agentic. And that means an entirely different UI/UX for reps to work out of (again, built on the warehouse, not just the crm). Rox makes legacy SaaS systems effectively invisible in the agent era. Less clicking, more selling.

7/  The intelligence layer

I describe the Revenue ‘brain’ as a place that can figure out which companies/people to reach out to, and how. The only way you can do this is if you have access to *all* of the data:

- unstructured data (emails, transcripts, etc.)
- structured data (salesforce, contacts, opportunities)
- private warehouse data (product usage data, time series data, etc) 
- public data (like signals)

This is a very technically difficult product to architect, while also integrating agents into the workflow.

I’m a fan of the team at Rox, and bullish on where they’re going.

They have a free product, so you can sign up (especially if you're in the Global 2,000) and see for yourself what all the hype is about :) rox.com/signup

Who are the best GTM x AI practitioners (with a focus on Pipe Gen)? 

No vendors please :) 

I want to talk with people who have deployed AI into production. Real use cases. Can be building their own tooling, or using third-party tools. 

Tag someone who has shipped something dope this year.

Doing a bit of research for a little event for The Signal... more on that soon (subscribe to get updated first: www.TheSignal.club)

Exploring the future GTM playbook → Writing The Signal | Playing long-term games with long-term people 🫡

Generic "signals" will become commoditized. "Niche/specific" signals will become the alpha and have staying power. These signals should indicate the right *timing* to reach out to a prospect. Here are 20 examples:

1. Warehouse robotics / 3PL automation
Signal: New fulfillment center announced (Workflow design phase → ideal timing for automation decisions)
Source: Press releases, careers page, job descriptions

2. API security
Signal: Public API docs show a major version bump (New surface area → expanding security debt immediately)
Source: API docs, GitHub commits

3. Sales compensation & planning
Signal: Job posts mention “new FY comp/territories” (Comp redesign underway → high organizational pain)
Source: Job descriptions

4. AI QA for contact centers
Signal: Support page adds phone or chat channel (Volume spike + multi-channel complexity → QA automation need)
Source: Support page crawl

5. Accessibility compliance
Signal: New accessibility footer appears, boilerplate content (Legal pressure surfaced → remediation required)
Source: Website footer change detection

6. Usage-based billing
Signal: Pricing page adds “usage-based pricing (beta)” or similar (Metering/billing complexity rising → need for usage infrastructure)
Source: Pricing page diff

7. Privacy / DSAR automation
Signal: Privacy policy page’s last updated date is within 30 days (New privacy workflow or regulatory pressure emerging)
Source: Website change detection

8. ESG / sustainability reporting
Signal: ESG/CSR report updated recently (Entering ongoing reporting cadence → tools needed to scale)
Source: Investor relations page

9. Expense management
Signal: Employee handbook updated with new stipends/budget sections (New spend categories → need for controls/visibility)
Source: Public handbook PDFs

10. Consent & preference centers
Signal: Email footer switches to “Manage Preferences” (Growing privacy + marketing pressure → need for consent management)
Source: Marketing email footers

11. CDP / data routing
Signal: Multiple new martech tags appear recently (Stack expanding → rising data identity and plumbing issues)
Source: BuiltWith, tag managers

12. AI enablement / sales enablement
Signal: Product changelog shows new AI Assistant/Copilot (Sales team needs updated messaging + enablement immediately)
Source: Product changelogs

13. FinOps / cloud cost optimization
Signal: Company adds 2nd region or cloud provider (Cost/governance complexity spikes → FinOps needed now)
Source: Engineering blog, technologies detected in job descriptions

14. Travel Company
Signal: HQ move or office relocation announced (Operational changes → need for new systems and workflows)
Source: LinkedIn posts, press releases

15. Incident management
Signal: Status page shows spike in incidents (Reliability regression → push for incident tooling)
Source: Status page logs

...I ran out of room. The last 5 are in the comments. 

PS: Much more on this topic coming to The Signal readers' inboxes soon 👀

Generic Signals are getting commoditized. Niche Signals are the new alpha. Here's what it means if you're building an AI-native GTM org today:

First, signal-based selling remains the most effective approach for GTM teams today. Much better than cold outbound (which doesn't work like it used to). 

Signal-based selling helps teams/reps find the prospects who are MOST LIKELY to take a sales meeting if you reach out this week.

Generic signals—like funding raised, hiring roles, etc.—are quickly becoming commoditized because everyone has access to the same data from the same providers. And prospects can smell the automation from a mile away.

(Operationalizing these signals is still hard to do, btw. So, I think there's at least another year for companies to use generic signals to get ahead of their competitors.)

But, just like back in 2016, it was novel to have Outreach or SalesLoft use “personalization tokens” in an email to inject {first_name}, {title}, {company}, or {industry}. Today, it’s obvious to a reader that a machine, not a human, wrote those.

The same thing will happen with generic signals. In 2026, I suspect that when a prospect sees a cold email that is based on {their new job}, {a website visit}, or {some other generic signal}, they’ll know that a machine (AI), not a human, found this signal and wrote this message.

But, not all signals are created equal.

Enter: "The great signal divide."

The next wave of alpha will be niche, specific signals that indicate the right timing to reach out have real staying power. And that’s exactly where the best tools are differentiating themselves (Sumble is one example).

→ Alpha
 
The alpha is in the creative, thoughtful experiments that only you can set up. And in choosing vendors who can surface signals that aren’t available everywhere else.

→ The more niche/specific, the better

I’ve noticed that the absolute best signals are ones so good that AI—or myself, as an external advisor/consultant—cannot come up with them. They have to come from within the company (almost always from either the founder directly or the top sales rep).

→ 1st party signals

It’s also worth noting that some of these signals will be 1st party data. These signals, by definition, cannot become commoditized because they are your own company’s IP.

→ AI / agentic workflows

Yes, many of these niche/specific signals require AI workflows or “agent runs” to identify at scale, autonomously. You should be asking what works manually, then scaling it with an automated or agentic workflow (or combination).

Conclusion

The signal-based selling market is splitting into two tiers: commodity signals that everyone has access to, and niche, timing-focused signals that create real competitive advantage.

Thoughtful, creative, taste-driven go-to-market is the future. Teams that proactively deliver real value to their prospects.

Read more in my latest blog post on The Signal:

Open article: Generic Signals Are Getting Commoditized. Niche Signals Are the New Alpha. by thesignal.club

Generic Signals Are Getting Commoditized. Niche Signals Are the New Alpha.

Who is doing AI for outbound on $50K+ B2B SaaS products (Series C+ — eg: has the complexity of 20+ sellers)? 

^ That’s the real turing test of if AI outbound works
(not selling event tickets—no offense to jason/saastr)

SaaStr AI London is Dec 1-2!! See You There!!

AI Agents work in GTM today.  We've got 6+ in production now.  They work for sales, they work for outbound, they work for marketing.  But ... 

They don't work well without a lot of training.  That means they don't really work well as self-serve products and at low price points.  For now at least.

Most of the vendors taking off have effective ACVs of $50k-$100k+.  That lets them use FDEs and other resources to help train the AI agents for the customers, often over an extended period.

And that works well -- today.  If you train the AI agents well.

What's next?

Doing this >well< for small customers and self-serve.  It's a real challenge.  But it's one we're excited to see play out.

I asked my intern (Claude) to analyze my LinkedIn connections. 

Here's what they just sent me:

Fun to clearly see the data behind a network.

It's unrealistic to "give an old school team new school systems." These tech stack infographics are misleading. 

This tech stack is for high-volume, fully automated outbound. This is the stack a centralized team/member (eg: RevOps, Growth, or a GTM Engineer) would run *on behalf of* reps. 

Enterprise companies are not downgrading from Salesforce to HubSpot (or Attio, etc.). They're not swapping Outreach/SalesLoft for Instantly/Smartlead (there's literally not a UI/way to multi-thread in them). They're not plugging in HeyReach and automating a ton of actions (at the risk of getting their LinkedIn accounts shut down). Replacing ZoomInfo for Ocean? These are completely apples and oranges.  

Just because new tools are available does not mean you should buy all of them. 

It's much more nuanced than that. 

Some of these new tools are REALLY valuable, but only in the right context. Think about using them for a new/different motion (not replacing your existing motion with them, in most cases). 

PS - I'm slowly distilling my (agnostic) opinions about the evolving stack on a new website — check it out at ProspectingStack.com.

Co-Founder @ Workflows.io | Growth playbooks using AI

Sales team setups 2020 vs 2025

The truth is that the job of BDRs & AEs never changed.

Their objective is still the same.

But tech changed one thing:

→ Volume 

An old school BDR could do:

• 50 dials/day manually researched
• 10 personalized emails/day
• 2-3 demos booked/week

A new school BDR in 2025:
• 200 calls/day
• 50 hyper-personalized emails
• 7-8 demos booked/week

And this was made possible ONLY with proper GTM engineering.


Here's the tech stack changes I'm seeing:

CRM: Salesforce → HubSpot
(no need for a CRM admin to make changes)

TAM Sourcing: ZoomInfo → Ocean.io
(find any company on the web)

Data Handling: Excel → Clay
(AI spreadsheet with APIs)

Global Email Coverage: Apollo → Findymail
(better coverage & validation & price)

Global Phone Coverage: Cognism → BetterContact
(best-in-class waterfall enrichment provider)

Email Campaigns: Mail Merge → Instantly.ai
(no comments here)

DM Campaigns: Sales Nav → HeyReach.io
(automating signal-based plays)

Call Recording: Manual Notes → Sybill
(AI notetakers are a must-have in 2025)

Give an old school team new school systems.

That's where magic happens.

I’ve been playing around with Gemini 3 and it’s insane. 

Would be ironic if OpenAI become the Yahoo of AI era, crushed by Google — again.

Google just woke up.

And OpenAI is feeling the heat.

A leaked internal memo from Sam Altman just surfaced.

The OpenAI CEO admits Google's AI progress could "create some temporary economic headwinds."

Here's what's happening:

→ OpenAI's revenue growth could slow to single digits by 2026
→ They're projecting a $74 billion operating loss by 2028
→ Gemini 3 Pro now leads GPT-5.1 in reasoning and coding tasks

Altman's own words: "Google has been doing excellent work recently in every aspect."

This is a massive shift.

For 3 years, OpenAI had peacetime dominance.

Now it’s a wartime scenario.

OpenAI is scrambling with social-infused features like Sora 2 App and group chats in ChatGPT in an effort to push top-line revenue and seek virality.

Meanwhile, Google's been quietly building:

→ Gemini 3 for reasoning
→ Nano Banana Pro for images
→ Veo 3.1 for video
→ TPUs powering everything

The real insight here:

• Google wasn't the first search engine
• Many came and went before it
• What matters is being the last mover

Owning the "stack" from chip to chatbot creates the only real enduring moat.

My takeaway:

Frontier LLMs are rapidly commoditising.

OpenAI pioneered the technology, but it can't defend margins when competitors match its capability.

I recently switched my new default model from GPT-5.1 to Gemini 3 “Fast” mode for general Q&A tasks because of its speed.

The sleeping giant has woken up.

And the AI race just got a whole lot more interesting.

Follow me Alex Banks for daily AI highlights and insights.

I cover the most important AI developments each week in my newsletter.

Subscribe here: https://lnkd.in/ePSZP6KF

The Narrative Company | Executive Narrative & Influence Strategy

Something big is shifting on X. And almost nobody is talking about it.

Companies aren’t just hiring engineers or PMs anymore.

They’re hiring distribution power.

X brought in Nikita Bier
Cursor brought in Ben Lang
Google brought in Logan Kilpatrick
Cognition brought in swyx ​
Coinbase brought in Alex A.
Anthropic offered $250k+ for this exact skill set

And look at Sam Altman and Satya Nadella. The precision of their posts tells you someone deeply understands this platform.

Understanding the X algorithm is becoming a real skill. And companies know it.

Why are companies doing this?

Because distribution on X now determines:

• narrative
• talent flow
• demand
• investor attention
• product adoption
• cultural relevance

It’s happening on LinkedIn too, but X is still the center of gravity for AI.

The companies that win distribution don’t just grow faster.
They shape the whole conversation.

If you understand X, you understand leverage.

the cold email king saying ai should write cold emails is a turning point 👀

Struggling to book meetings? Getting ghosted? Want to sell without pushing, convincing, or begging? Read this profile.

Salespeople shouldn’t write cold emails.

AI should.

Salespeople should make cold calls.

Why?

Cold email isn’t a human sport anymore.
It’s a computational one.

AI can write faster.
Test faster.
Personalize deeper.
Analyze patterns instantly.
Send at scale without losing tone.

And unlike humans, it never gets tired, emotional, insecure, or trapped in the “should I say this or that?” spiral.

Cold calling, though, that’s human territory.
Tone.
Timing.
Curiosity.
Detachment.
Listening.
All the subtle signals machines can’t feel.

So let AI own cold email.
It’s simply better at it.
And let SDRs do what humans do best:
Talk.
Read emotion.
Navigate uncertainty.
Turn strangers into conversations.

AI for cold emails.
SDRs for cold calls.

What do you think?

taplio

The Battle

Hayk C.

Brendan Short 🌊

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