I turn Startups > Scaleups. PMF and PLG. I write about it at growth-goals.com ✉️ - check it out

👋 I'm Andrew. I love fast-growing Startups. Ex-founder, small-time investor, and I write about Growth/PMF/OKRs.  

I've built high-growth companies in London and Silicon Valley. Over the years, I've sat on all sides of the table as a founder, investor, operator, and advisor. Currently, I have an AI and web3 bias, but I have been everywhere. 

During this journey, I created the Growth/OKR process Core & Explore™, which is now used by thousands of Startups and some large companies. 

Previously, I graduated 500 Startups; was an EIR at Seedcamp; led product and growth at my own Startup; mentored and advised VC funds; and helped behind the scenes at the founder community ICE.

Andrew Crump

I’m a SaaS operator with 15+ years of experience building and scaling GTM teams across Europe – from early-stage startups to growth-stage rocket ships.

Most recently, I was GM EMEA at Crossbeam, the leading Ecosystem-Led Growth (ELG) platform, where I helped SaaS companies speed up deal cycles, grow ACV, and win more through partnerships.

Before that, I led Handshake’s European expansion, setting up the GTM engine and driving adoption across leading universities and Fortune 500 employers.

Previously, I was Managing Director EMEA at Stack Overflow, where I launched the European business, scaled the team to 75+, and turned Stack Overflow Talent into a category leader. The company was later acquired by Prosus for $1.8B.

I’ve also founded and scaled two SaaS startups – Heresy, a sales diagnostics tool used by teams at GoCardless and Trello, and WePow, an early player in video interviewing (acquired by OutMatch).

I'm also an active angel investor and advisor, working closely with a handful of SaaS companies on their GTM strategy and international growth.

Dimitar Stanimiroff

AI isn’t just a technology story anymore.
It’s a geopolitical one.

In this conversation with Hung Lee, we dig into why:

• Greenland has suddenly become strategically critical
• Taiwan and TSMC sit at the heart of global power
•The US and China are fighting fundamentally different AI wars
• Energy, EVs and rare earths may matter more than algorithms

Check out the trailer below.

 🎧 Full episode drops today at 14:00 UK.

This is a wide-ranging conversation about power, incentives, systems, and the future world order.

Enjoy!

2x Founder 🏗️ | 3x 🦄 Operator | Angel investor 🚀

Somewhere between 2024 and 2025, especially in AI-native companies, a quiet semantic drift happened:

ARR → annualized run-rate → something more… aspirational.

The label stayed the same.
The epistemic status of the number did not.

Historically, ARR meant something very specific:
🔺 Contracted
🔺 Recurring
🔺 Normalised
🔺 Auditable
🔺 Boring...and that was the point.

Then #AI arrived.

Suddenly:
🔼 Value could be delivered in days, not quarters
🔼 Usage-based pricing made revenue spike overnight
🔼 Pilots started looking like “early subscriptions”

One strong month × 12 quietly became “ARR” 🤔

By late 2025, in some decks, “ARR” wasn’t even annualized anymore – it was modeled belief:

👉 Partial usage
👉 Assumed expansion
👉 Forward pricing
👉 “Once rolled out org-wide…”

At that point, we weren’t talking about revenue.
We were talking about a hypothesis with a dollar sign.

On the Heresy pod recently, Sam Jacobs added an important layer to this.
He made the point that VC incentives and operator incentives are not aligned and that this isn’t a moral judgment.

As he put it:

“Your incentives are different to Harry Stebbings and Jason Lemkin. They need to be in Databricks. You’re not going to be in Databricks.”

They’re not bad actors.
They’re playing a different game.

If your fund needs one Databricks to work, you must believe and tell founders that:

🔺This time is different
🔺These founders are special
🔺Normal rules don’t apply

Because the alternative is existential.

The problem is what Sam said next:

“I think no one is that special or different.”

And that’s where things get uncomfortable.

To justify valuations, expectations, and fundraising velocity, we’ve told a generation of AI founders that they’re exempt from gravity – just as we’re heading into what Cassie Young called the Gross Retention Apocalypse in AI.

Usage is easy to turn on.
It’s even easier to turn off.

AI doesn’t break the laws of customer behavior.
It just delays the bill.

This wasn’t fraud.
It was incentive-compatible optimism under asymmetric fear:

👉 Fear of missing the next platform shift
👉 Fear of applying old SaaS heuristics to new curves
👉 Fear of being too late – and too right

So rigor softened.
Language blurred.
And revenue quietly became narrative.

My working heuristic:

🔼 If it’s contractually committed → ARR
🔼 If it’s happening now but not locked in → annualised
🔼 If it depends on “ifs” → it’s not a metric, it’s a theory

AI does change things.
But it doesn’t change incentives.
And it definitely doesn’t change retention math.

I suspect 2026 will be the year we rediscover prefixes:
Actual ARR. Committed ARR. Realised ARR.

Same metric.
New scars.

What’s the future of GTM in the age of AI?

Are we about to see a material reduction in the number of BDRs and AEs? Does sales leadership remain a viable (or even attractive) career path?
👇

In the short video below, Sam shares his take on where this is heading and what it means for people building careers in GTM today.

I’m particularly keen to hear from GTM leaders, SDRs, and AEs:

- Where are you already seeing AI change how work gets done?
- Which parts of the role feel most at risk and which feel more valuable than ever?
- If you were early in your sales career today, what would you double down on?

Let’s pressure-test this together 👀

#gtm #ai #sales #pavilion

Every ChatGPT interaction ends with an upsell.

That’s not accidental.

Sam Jacobs breaks down OpenAI’s strategy:

👉 Be everywhere
👉 Spend aggressively
👉 Worry about profits later (much later)

With ~$1.3T in data centre commitments and billions in annual losses, this is a “win first, monetise later” play on an unprecedented scale.

Agreed?

#openAI #chatGPT #AI

The AI race isn’t just about who builds the best mode, it’s about what those models are for.

In this clip with Hung Lee, we unpack a growing divergence:

- 🇨🇳 China is optimising for applied AI - open models, tightly integrated into industry to drive efficiency.
 - 🇺🇸 The US is doubling down on frontier models - closed systems, chasing AGI.

Two different strategies, with two different endgames.

And very different implications for productivity, power, and economic leverage.

🎧 Full episode link in comments.

taplio

The Battle

Andrew Crump

Dimitar Stanimiroff

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taplio

The Battle

Andrew Crump

Dimitar Stanimiroff

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Dimitar Stanimiroff's LinkedIn Performance

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