Jon Schröder

Construction is the main character now. VC @Foundamental

[Jon Schröder @jcb_schroeder]

While everyone is looking to space, what is happening underground?

[Jon Schröder @jcb_schroeder]

@alexanderrX_ Boring stuff is my core business

[Jon Schröder @jcb_schroeder]

I appreciated this read and your perspective Randy. As a tech investor in AEC & ConTech I have met with roughly 500 founders over the past 12 months. There is still a strong pull towards entrepreneurship amongst architects - because they can feel that the profession is changing, powerful AI narratives are breathing down their neck, but also because about-to-retire partners want to be bought out at unrealistic valuations - effectively breaking the pinnacle of this career path. Architects make great founders and I am all there for it!

[Jon Schröder @jcb_schroeder]

@benedictk__ People have grit in Munich and can back it up with actual engineering pedigree. Less international than Berlin and definitely a way inferior food & culture scene. BUT: direct flights to basically every relevant global hub is a HUGE plus.

[Jon Schröder @jcb_schroeder]

The future electrical infrastructure is underground.

[Object Zero @Object_Zero_]

HVDC Transmission

One of the biggest changes for future infrastructure is the emergence of High Voltage DC transmission.

As the story goes, in the original 1880s build out it was Edison and Westinghouse who battled with AC and DC technologies for electricity distribution systems.

AC won the day, because it was the only way to move power any meaningful distance. Back then, DC was limited to just 1 mile.

But then semiconductors came along…

In 1957, high power semiconductors completely upended transmission technologies. Now DC outperforms AC on distance, cost and efficiency.

Modern DC has no reactive power losses, no skin effect, and use 50% less copper.

The semiconductor technology breakthroughs came about in the 50s and entered commercial markets worldwide in the 1970s. But then Insulated Gate Bipolar Transistors (IGBTs) and Voltage Source Converters (VSCs) also hit commercial markets in the 1990s.

Countries that developed before 1999 are mostly still stuck using an AC backbone, but countries that developed later had the advantage of building their most valuable machine (the grid), on a DC backbone.

A DC backbone allows asynchronous transmission over transcontinental distance. Some DC systems today stretch 2,000 miles, connecting day and night, connecting sunshine and wind.

HVDC technology today is able to connect countries separated by seas and oceans, creating new markets and exchanges for balancing power. There’s even a project to connect to UK to Morocco, laying cables around the Iberian peninsula.

The ability to lay HVDC cables in seawater simplifies the deployment somewhat as countries with highly ossified infrastructure and land ownership can shift huge power volumes up and down their coastlines. Moving power East-West arbitrages diurnal cycles and moving power North-South arbitrages seasonal variances.

The capacity keeps rising too, with companies already marketing cables able to carry 3.5GW. In China they are laying UHVDC where voltages of 1.1 million volts are common.

In the 2030s we will see multi-million volt cables being laid across oceans, which starts to get interesting for the system architecture of grids.

It’s not crazy to consider that some sort of pan transmission system emerges with huge asynchronous arteries laid in corridors that carry electrical power.

Why will this happen?

Well today electricity prices are highly heterogeneous, industrialised nations pay around $50/MWh but developing nations pay $100-200/MWh and in poorer nations it costs $350/MWh.

Around 1.5 bn people enjoy cheap energy, whereas 6.5 bn people live with high electricity costs.

Most of the problems in the world; war, disease, climate, population, they are actually poverty problems, and at the root of the poverty problem is cheap electricity (there are still some idiots out there).

Almost every other major problem in the world stems from the lack of cheap and abundant power. Even the expansion at the industrial frontier is rapidly becoming limited by the availability of power.

[Jon Schröder @jcb_schroeder]

A little tip for #FounderFriday because I keep repeating this in calls and see the best founders doing it. Setup investor newsletters and keep everyone up to date, even if the investor passed earlier! Building rapport & keeping yourself accountable does magic! What you should include? Easy 🔽

→ Personal intro, max. a small paragraph
→ One liner what your company does (we see roughly 500 companies a year, its nice to have a little reminder)
→ Asks (how can we actively help you? Hiring, any bottlenecks, sales intros, opinion - be reasonable. We have also have other to do’s)
→ Yearly goals & north star (reiterate, reflect, max. 3-5 bulletpoints)
→ Your focus last month (max. 3 focus areas, progress & update on each one)
→ The good, the bad, the ugly (be transparent, be honest - this builds trust, trust builds relationship, relationship makes partners)
→ Your focus next month (again, max. 3 areas, very concise and short)

🚀

[Jon Schröder @jcb_schroeder]

Observations 10, 12, 18 are the most interesting.

10. Battling poor data, duplicates, multiple ERP & CRM systems, as well as an ever growing Shadow IT is a huge adoption barrier for AI + agentic systems. AEC & ConstructionTech has been battling this for decades and it has gotten worse with LLMs. This is not a consulting opportunity IMO because it is a continuous task with hard-to-measure returns.

12. It’s not only hard to get data on agents failing on tasks, but it is equally difficult to get data and real examples of agents continuously succeeding and carrying out tasks. Blackbox within a blackbox + the shame to admit to not know what’s going on or say what has not worked.

18. Insurance for agents is an interesting thought experiment. Lloyds & Munich RE are already backing neo-insurers for this but it is tricky to underwrite. You can’t really insure model accuracy so you underwrite the blast radius as in the agentic architecture, so the insurers define spend caps, human checkpoints, audit log quality and scope of permission. This is the same effect fire insurers had on shaping building codes - far stronger than any regulator.

[GREG ISENBERG @gregisenberg]

I spent 48 hours in SF hanging out with billionaires, data labs and AI founders and execs running $1B to $100B companies.

My observations:

1. Sooo MANY stories of data brokers making like $2M a WEEK selling company data to labs. I can't tell if it's the beginning or a bubble, and I kept wondering which niches are left. Digging into it actively.

2. At dinner, someone asked the table, "If a new model drops next month, does your company get better or worse?" HALF the table went quiet! I think that's the best question to ask about any AI startup right now.

3. The bar people talk about now is hitting $1B in revenue in 12 months (I guess that's the new unicorn?). What I didn't hear much about is retention. AI revenue can come in fast and leave fast, and I think we're going to see a lot of stories of AI companies with huge revenue and terrible retention.

4. It's pretty clear we're living through the reinvention of the computer. The model is the CPU, the harness is the operating system, and skills and plugins are the apps. Thinking about it that way makes it easier to see where the whitespace is.

5. We're maybe 12 months from an agent that can watch you work for a week and then do your job without any instructions. The screen recording plus agent memory plus local model combination makes this possible right now.

6. Agent harnesses feel like the new GPT wrappers, in a good way, especially vertical ones. The best teams I talked to treat the model as swappable. One founder walked me through routing different models to different jobs: one for taste and visuals, a cheaper one for the everyday stuff, another for text.

They use prompts they can move across models over fine-tuning, and A/B test the output on what users actually do with it: do they edit it, export it, share it? A vertical harness is basically four things: the connectors for that industry's data, evals written by people who know the work, rules for what the agent can and can't touch, and a clean screen for a human to review. The model is maybe 20% of it.

7. There's a lot of reverse engineering going on/cloning going on more than I've ever seen. People are decompiling software and rebuilding it with agents, and someone showed a suite of like 10 apps that are worth $5B+ each all that he cloned open source. Me and everyone are still thinking through what it means when software gets this easy to copy.

8. My guess is the value moves to data. If the software can be rebuilt quickly, what's worth paying for in a legacy SaaS company is the years of customer data and workflows inside it. Some SaaS companies are secretly data companies.

Gets me thinking about how do you truly value data for this saas companies? Like if we were buying these dying saas companies at 2x ARR before (as example), maybe there is a better metric. Idk, just thinking out loud here.

9. It feels like a good chunk of legacy software won't make it to the agentic era, especially anything built around people clicking through a lot of screens.

10. Every company I talked to wants to pipe its internal data into one place and expose it to agents through MCP. Then they look at the data and realize it's a mess: five versions of the same customer, old Slack channels, PDFs nobody can search. Cleaning that up feels like a big consulting opportunity!

11. A lot of founders are building the basic building blocks for agents: APIs, data layers and tools. Some of the companies I saw barely have a UI because the main user is an agent. I really believe the startups that build primitives to this agentic era will do extremely well. Building blocks is the best way to think about it.

12. Labs can get plenty of training data, but it's harder to get real examples of agents failing inside companies. Whoever has those logs has something valuable.

13. Someone running a big consumer company told me the next fight is over memory. The model that remembers the most about you wins, and the smartest model matters less than people think.

14. Physical AI came up a lot. Astra I think was the first model that got people into AI can actually do CAD, and I think a lot of people are thinking what does vibe manufacturing really look like. The line I keep thinking about came from a robotics founder: the hardest problems in AI are deployment problems now, not research problems. Their robots work on their own, call a human when they get stuck, and every one of those calls becomes training data.

15. Cybersecurity companies are having a moment and are actually cool companies to build now, especially the ones that clean up after a breach. Every agent with access to your systems is a new door into your company, and a lot of those doors were left open.

16. Some startups are worth more dead than alive now. A shutdown company with 5 years of Slack, email and code can get paid for licensing all of it. I wouldn't be surprised if founders start factoring that into when they shut down.

17. People are starting to talk about monetizing the agent web. It feels really early, but when the most popular user of the internet is an agent, what startups should you be building?

18. I think agent insurance is coming. Once an agent makes an expensive mistake, insurers will want audits before they cover anyone.

19. Several people said the hire they want most is someone with taste who can write evals. The models are getting good at generating ideas, so the hard part is judging which ones are good.

20. New trend I observed: startup raises VC, uses venture dollars to become a creator, startup fails, founder falls back on being a full-time creator and incubates other products bootstrapped.

21. Getting SIGNIFICANT distribution is HARD right now. Founders are sponsoring buses, buying billboards like crazy and throwing parties with famous DJs to get noticed. Kinda feels dotcom era in that sense.

Attention is what's scarce! The growth guy going viral sharing his UGC strategy from Wispr Flow is a good example. It's the sauce everyone wants, and I truly believe there are probably only 50 people on the planet who know how to scale these types of businesses efficiently in this era.

Always good to get that dose of SF. I felt sooo lucky to have such an incredible trip during such an incredible time in building businesses. Surreal in so many ways.

Happy to be home and locked in.

Until next time!

[Jon Schröder @jcb_schroeder]

@robhawkes Mesmerizing visualisation - the beginning of true energy independence. It's super interesting to see how relevant pumped hydro is, but also that it takes longer to ramp up.

[Robin Hawkes @robhawkes]

Here's how grid-scale batteries and pumped hydro charged over the past week…

It's interesting to see the patterns throughout the week. There's a lot of background activity as well as periodic moments where the entire fleet appears to store energy at the same time.

Pumped hydro is shown in purple, with the large Dinorwig asset clearly visible in North Wales.

This is only showing import (charge) behaviour as the assets store energy from the grid, it doesn't show the export (discharge) that puts energy back into the grid.

Timeline playback is coming to my energy map Soon™

[Jon Schröder @jcb_schroeder]

Genuine question for the reindustrialization crowd.

The West offshored manufacturing because wages, social contributions and labor protections made production at scale uncompetitive. None of that has changed. If anything it's worse today.

So what exactly is the hardware startup exemption? Automation shrinking labor as a share of unit cost? Defense and proximity premiums that override price? High-mix niches where Asian scale doesn't apply?

Each of those works at prototype volume. I'm less sure any of them survives at scale, which is where the original offshoring decision was actually made. I have a feeling that we will see a lot of startups discovering this ugly truth from first principles soon

[Jon Schröder @jcb_schroeder]

@DadaJudith @Westermeyer @langdock Very impressive interview and story Judith, just finished listening to it. Outside the Langdock insights, It really stood out to me how transparently you were about the trade-offs for entrepreneurial families who are striving for exceptionalism

[Jon Schröder @jcb_schroeder]

What was the moment that an AI sceptic in your personal environment had an awakening?

[Jon Schröder @jcb_schroeder]

@_brianpitts You just discovered the reason for offshoring from first principles

[Jon Schröder @jcb_schroeder]

Generational fumble to not split the G here

[Mark Malone @soundmigration]

Mark Zuckerberg pretending to enjoy Guinness is my new favourite thing.

[Jon Schröder @jcb_schroeder]

Thats what we call "Graduating from the thin slice to the fat slice". And I am out here looking for the cracked founders going after that fat slice.

[Jon Schröder @jcb_schroeder]

Just software in ConTech? You've already lost - The software's not where the value is, the 97% underneath is

[Jon Schröder @jcb_schroeder]

So the P&L reality leads to a simple conclusion. If you want real value capture in this industry, you cannot stay where the budget isn't. You have to migrate to where the budget is. The software is how you get there.

[Jon Schröder @jcb_schroeder]

@themikewax Sick!! My ASI escape is below a 10sqm kite on the North Sea 💆‍♂️