Leon J.

We help manufacturers find demand before it surfaces. Building this at Amplifa. DM 'playbook' if you're in industrial GTM.

[Leon J. @leonjhermann]

@nrmehta bootstrap and grow venture-scale

[Leon J. @leonjhermann]

@runaway_vol The future isn't software vs. hardware. It's AI + engineering.

Few countries are better positioned than Germany when atoms matter again.

[Leon J. @leonjhermann]

It's AI that finds demand before competitors even see it.

That's a harder problem than anything on this slide.

And almost nobody is working on it. (3/3)

[Leon J. @leonjhermann]

Unpopular take: this playbook will destroy any manufacturer that copies it.

Anthropic gets 54% of enterprise logos through self-serve because buyers already worship the brand.

Manufacturing is the opposite universe.

Nobody is self-serving a €400K turbine assembly. (1/3)

[Jason ✨👾SaaStr.Ai✨ Lemkin @jasonlk]

54% of Anthropic's new enterprise logos in 2026 came through self-serve.

Self-serve enterprise. Real ACV. Real terms of service. No AE in the loop.

Anthropic's Head of Industries Eleanor Dorfman walked through at SaaStr AI 2026 last week how they rebuilt the entire sales org in 30 days after Claude Opus 4.6 broke their demand curve in December.

👉The constraint: couldn't 3x or 4x the sales team fast enough without lowering the recruiting bar.

The thesis: don't buy a new stack. Thread Claude through the one you already have.

What they kept:

1⃣ Clay for enrichment
2⃣LeanData for routing
3⃣ @salesforce as system of record
4⃣@Gong_io for call coaching
5⃣Ironclad for contracts
6⃣@slackhq for everything else

What they added: Claude as the connective tissue between all six.

The four moves:

1/ Killed the PLG vs SLG orthodoxy. Launched enterprise self-serve in January. Intercom Fin guides the buyer through the journey. Now 54% of new enterprise logos.

2/ Threaded Claude through the existing stack. Every AE starts the day with a "morning brief" Skill that pulls context from Gmail, Gong, Slack, Salesforce, @intercom, Greenhouse.

3/ Made Slack the front door for every support function. Slack ticket in, Jira ticket out. Claude triages and resolves inline if it matches precedent. Escalates with full context if not.

4/ Codified what the best reps do as Skills. Every new rep gets a sales plug-in with 5 Skills: morning brief, call prep, customer follow-up, competitive intel, create-an-asset.

Anthropic didn't replace anything. They invested in the stack they already had and let Claude be the seam between everything.

Most companies will spend 2026 evaluating AI-native sales platforms. But Anthropic did it with its current stack + Claude.

Almost none of it required new software.

[Leon J. @leonjhermann]

The US is reshoring production but can't find people to sell it. Europe has overcapacity and China eating margins on products that sold themselves for 30 years.Same crisis. Both sides. The inbound era is done.What manufacturing actually needs isn't better lead forms. (2/3)

[Leon J. @leonjhermann]

@sminocha_ How we apply it: Fixed pricing for outcomes + optimized COGS at software margins in token consumption (model routing, prompt reuse rate, own data, and others)...

[Leon J. @leonjhermann]

@sflorimm Europe has ASML
Europe has Airbus
Europe has Siemens
Europe has Zeiss
Europe has Rheinmetall

Europe doesn't build the models.
Europe builds the machines that run them.

Different game.

[Leon J. @leonjhermann]

9/ Trust beats innovation.

Industry adopts AI only
when risk remains controllable.

Explainability > black boxes.
Human-in-the-loop > full autonomy.

[Leon J. @leonjhermann]

2026 won’t be a vision year for industrial sales.
It will be a decision year.

10 topics industrial sales should think about now (Thread)

[Leon J. @leonjhermann]

8/ Data beats models.

Most AI initiatives fail not because of algorithms,
but because of poor data foundations.

In 2026, data capability becomes a buying criterion.

[Leon J. @leonjhermann]

AI isn’t “over.”
But the free ride is.
Scaling isn’t giving us the same jumps anymore.
More compute ≠ more intelligence.

The game shifts:
• smarter inference > bigger models
• specialization > horizontal scale
• real feedback > synthetic data
• personal AI > cloud AI

[Leon J. @leonjhermann]

@rabois cohorts

[Leon J. @leonjhermann]

7/
We don’t build AI SDRs.
We build outcome machines.
You bring the human.
We bring the systems that scale it.
If you’re an SME trying to grow without going broke on tech…

DM me. I’ll show you how.

[Leon J. @leonjhermann]

Everyone’s drooling over the “$200K SDR.”

10 AI agents.
$5M+ pipeline.
24/7 follow-ups.
That’s cool… for like 12 people.
For the rest? It’s a trap.

Let me explain 👇