Head of AI & Data strategy, Revolutionizing GovCon at Procurement Sciences

I help Aerospace & Defense organizations modernize without losing what makes them mission-critical.

With 15+ years in A&D at Lockheed Martin and GDIT, I know the terrain: complex programs, siloed systems, tight compliance, and the high stakes of delivering at scale. Now at Salesforce, I work with public sector leaders to align technology with mission outcomes — using tools like Data Cloud, Mulesoft, Tableau, and Slack to make transformation not just possible, but practical.

My edge? I speak your language — program lifecycle, cybersecurity, workforce upskilling, supply chain visibility — and bring solutions that fit the reality of your environment, not fantasy decks.

Proud husband to an Army veteran, and someone who’s built digital strategy from the inside out.

Let’s connect if you’re navigating digital transformation in Aerospace & Defense — and want a partner who gets both the mission and the margin.

Anthony Brown

Brendan Short

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. 🤘

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

Brendan Short 🌊

Kyle Norton's (CRO at Owner.com) sales team is 3-4x more productive per rep than competitors. Here are 11 things he says Revenue Leaders need to know about AI in 2026:

1. Being an "occasional user of AI" (eg: using ChatGPT a couple of times a day) is like being an occasional user of the internet. If you're not in these tools daily, you're already behind.

2. The new leadership skill stack: systems orchestration (managing humans + agents), depth beyond your core function, continuous improvement discipline, and change management for AI.

3. Fix your data before anything else. Nothing in AI works without clean data. Do not pass go, do not collect $200.

4. The 70/20/10 rule for building AI capability: 70% you and your team leveling up, 20% hiring expertise (usually in Rev Ops), 10% strategic consulting. You can't outsource transformation.

5. Use the 5P framework to prioritize AI use cases: Possibilities (what could AI improve?), Payoff (ROI if successful), Probability (likelihood it works), Perspiration (effort required), Prioritization (expected value ÷ effort).

6. Easy wins to start: CRM enrichment automation, support automation, inbound AI SDR. Get these working before chasing flashy stuff.

7. Adoption is everything. If reps feel like AI is replacing them, nothing gets traction. Early investments should make their jobs easier, not scarier.

8. Integration over addition. Don't add new surfaces. Push AI outputs to where reps already work (Salesforce, Slack). If you add one tool, take one away.

9. Be skeptical of vendors whose pitch is "how little work it requires." Stacking generative layers without deterministic structure = slop.

10. Spend at least as much time on cultural adoption as technical implementation. Don't deploy via Slack announcement. Slow-roll. Spotlight what works.

11. Personal investment matters. Kyle spends 10+ hours/week on AI — podcasts, Twitter, YouTube, tinkering. He still feels behind. That's the bar.

The gap between AI-native revenue leaders and everyone else is compounding daily. I've seen it first-hand. Kyle is goated. He's leading the way in how revenue leaders who lean into AI are getting an advantage. 

»»» Watch Kyle's full presentation from the AI x GTM Summit: https://lnkd.in/gqAA9nt6 

»»» Read my summary of his session: https://lnkd.in/g2_rkZ2v

brendan short

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

We ArE sO eArLy WiTh Ai

but for real, this is bonkers:

Salesforce bought Momentum last week. That's 10 acquisitions in 6 months, and nearly all of them are about filling holes in Agentforce.

Momentum is the interesting one. The idea is to take what people say on calls (eg: Zoom and Google Meet) and turn it into data that AI agents can use. Because right now, Agentforce only knows what a rep typed into Salesforce after the call (which, if you've ever managed a sales team, like me, you know less than half of the important information makes it into the CRM).

For the short-term investor narrative, this is great: "We're buying our way to a complete AI-native revenue stack" is exactly the kind of thing that gets an analyst to raise a price target. And it might work! Ten acquisitions that all fit together on a PowerPoint slide is a pretty compelling narrative.

The problem is that customers don't care about investor narratives/slides. They care about how a product will help them win. And the reality is, when a product makes ten acquisitions in six months, that means ten different engineering teams figuring out who reports to who. Ten code bases. Ten sets of gtm leaders jockeying for headcount. Ten product roadmaps that need to become one product roadmap, except nobody agrees on what that one roadmap should look like. The people who are best at navigating that kind of internal complexity are rarely the same people who built the original product.

Salesforce has run this exact experiment before. In 2022 they bought Troops.ai, a Slack-based tool that helped reps update their CRM without leaving Slack. Good product, real users, compelling pitch. A couple of years later, Salesforce killed it, migrated everyone to something called Slack Elevate, and Troops basically ceased to exist. The thesis was right. The execution wasn't.

I don't think this means Salesforce is making a mistake. That said, I do think that the nature of being a platform this large makes it almost impossible to ship fast and stay close to users after absorbing a smaller company. There are simply organizational physics at play. The gravity of a 70,000-person company bends everything toward internal consensus and away from the best interests of the end users.

Which is why I'm even more bullish on my friends over at Attention (Anis Bennaceur). Attention plays in the exact same space as Momentum. Same problem, same category of customer, same bet that conversation data is the context layer that makes AI agents useful. The difference is that Attention doesn't have to spend the next 18 months figuring out how to fit inside Salesforce. They get to keep doing the thing that made them good in the first place: talking to customers, shipping product, and not spending their Mondays in integration planning meetings. Momentum getting acquired actually validates the entire market Attention has been building in.

The question for revenue teams is pretty simple. Do you want a LEGO castle? Or an agile innovator still operating independently?

Writing The Signal (AI x GTM weekly newsletter) | Playing long-term games with long-term people 🫡

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