Federico Martelli

I'm Federico we raised €5M in 36 hours, the fastest pre-seed in Europe and joined Forbes 30 Under 30 Europe 2026 shortly after I'm starting on X to share what I've been building and what I've learned along the way but first, a bit about me 27, Italian, CEO of Forgis, based in Zurich 4 months after founding, we had 5 term sheets from international funds won the ABB Startup Challenge against hundreds of startups and got deployed inside Fortune 500 plants all while obsessing over one question: why is the West handing its industrial base to China, and what can actually be done about it I've been writing about this on LinkedIn for the past year 10,000 followers, 800K monthly impressions turns out a lot of people in manufacturing, automation and deep tech care about this stuff I'm here to build the same thing on X expect real insights on manufacturing, industrial AI, robotics, reshoring and the geopolitics of production no fluff, no startup motivation content just first principles thinking from someone actually building in this space if that's your world, follow along

@yasser_elsaid_ taste as bottleneck is real. when execution commoditizes, aesthetic and directional judgment becomes the scarce input.

my contrarian first-principles take after 1 month in sf: - taste is the new bottleneck - being high agency is orthogonal to credentials - the only non-trivial leverage left is shifting the overton window stochastically via the irl connection economy.

@JoshBobrowsky agents as professional services firms rather than managed employees is the right mental model shift. the accountability layer changes everything.

Here are some predictions I see in the next 24 months 1. We start to see agents fully perform services. Think of this less like hiring an employee you manage and more like hiring a professional company that completes the job 2. Agents will get more personal, you will have a relationship with your agents, they will know you, you will know them 3. People will still use email but behind the scenes a massive amount of the emails will be written and read by agents with a slight human in the middle 4. More jobs will be created because everyone will be able to code

@shangenflow becoming your own best case study before selling to others is the most underused credibility strategy in services

WORST THINGS AGENCY OWNERS DO IN 2026: - Copy someone else's funnel because it looks like it works - Consume 10 podcasts a week and never execute on a single idea - Help clients build audiences while your own profile has nothing on it - Box yourself into one skill because some YouTube video told you to - Wait for someone else to believe in you before you start BEST THINGS AGENCY OWNERS DO IN 2026: - Become your own number one client before you serve anyone else - Post content today, not next week, not when you feel ready - Chase better clients than the ones you already have - Build new skills even when the ones you have are still working - Self-audit every single day and ask what you need to be doing to grow further

@BrianLaManna_ voice to transcript to structured output is the right workflow for turning vision into clarity. brain dump first, edit second.

I have a massive vision for Closed Won Club but really struggled with articulating a concise value prop for it. Boiling it down to 4 sentences or a short elevator pitch. Every time I tried to write it I got writer’s block. Wasted hours. Finally turned to AI. Turned on voice on ChatGPT & spoke for 5 minutes on everything I want Closed Won Club to become. Used that transcript & prompted it to create a concise & compelling elevator pitch and value prop based on that dump. Then went into editor mode to refine. Unbelievable result.

@GJarrosson compressed idea-to-execution cycles raise the floor for every batch. the ambient competitive pressure compounds the output.

Every new YC batch breaks the record of the last one. It's a compounding system. AI has collapsed the time between idea and execution. Founders ship faster, validate faster, and walk into Demo Day with numbers that would've taken 2 years to hit in 2021. That speed raises the ambient bar inside the batch. Everyone sees what's possible. Nobody wants to be the slowest in the room. The pressure cooker gets more pressure. The outcomes get bigger. YC isn't just keeping up with the AI era. It's being turbocharged by it. The next few years will be its best yet.

@JustJake weekly constraint identification and elimination is the only operating cadence that actually compounds

On Sunday, find the biggest thing blocking the company During the week, demolishing that obstacle Repeat until death or IPO

@E_Bruxxx the chip on the shoulder and the obsession with a specific problem are the two most durable starting conditions. everything else can be learned.

Reasons to start a company: > believe world should look different & bold enough to act > identified problem & ruthless obsession on building solution > control over personal upside > chip on shoulder / misunderstood

@TechWithMatteo problem clarity was always the bottleneck. AI just made it impossible to hide behind execution complexity anymore.

the more i use ai for coding the more i realize the skill isn't prompting. it's knowing what problem you're actually trying to solve before you type anything. the tool just makes that clarity more expensive to skip.

@KrishXCodes unsolicited work built from genuine curiosity is the most credible signal of capability. portfolios don't lie.

Best career decision I made wasn't learning a new framework. It was spending enough time building something I was curious about. Nobody asked me to build it. Nobody was waiting for it. But that project became the reason I got hired. Curiosity > strategy when you're starting out.

@jakecastilloooo compounding isn't visible until it pays out. every rep before the breakthrough was just invisible preparation.

People look at Cal AI and see 18 months. The real number is 10 years. Every job I worked, every hobby, every random side project. All of it stacked. I didn't know any of it was preparation at the time.

@jaredsuniverse distributing before you're ready forces the feedback loop that makes the product actually worth distributing

@deangraziosi first principles applied to revenue. every overcomplicated business model started by ignoring this sequence.

If you’re broke, don’t overcomplicate it. Find a problem. Solve it for someone. Get paid. Repeat.

@DeoArlo the distance between ambition and outcome is entirely filled by execution. nothing else closes that gap.

Ambition is cheap, grit is built. Ideas are cheap, execution is everything

@NiP73 replacing judgment with output generation and calling it efficiency is how you pay twice for the same capability

Here's a pattern I keep seeing: companies fire 3 people, hire an AI tool for $500/month, then 6 months later hire those people back as consultants at 2x the rate because the AI tool generated output but zero judgment. The math on this is brutal and nobody is tracking it publicly. Someone should.

@geoffreywoo pattern matching on the last cycle is how most capital misses the next one. weird and lean is the new signal.

observation: the next generation of seed winners wont look more polished. theyll look weirder, leaner, and more machine-amplified. small teams, violent iteration speed, ugly internals, absurd output. a lot of legacy VCs are about to confuse unfamiliarity with risk and miss another cycle for the exact same reason.

@lukas_m_ziegler open sourcing down to the BOM level is how you actually lower the barrier. everything else is just calling it open source.

100% open-source robotic arm! 🦾 Seeed Studio released reBot-DevArm, a robotic arm project lowering the barrier to learning robotics... or how people call it these days: physical AI. Everything is open-sourced. Hardware blueprints include sheet metal and 3D printed parts. Detailed BOM covers every screw with purchase links. Software and algorithms include Python SDK, ROS1/2, Isaac Sim, and LeRobot. Let's have a look at robot specs. So it has 1.5 kg payload, 650 mm max reach, 4.5 kg weight, and less than 0.2 mm repeatability with 6 DoF plus gripper. This is true open source for robotics. When every screw, CAD file, motor driver, and algorithm is freely available, desktop robotic arms become accessible to students, researchers, and developers worldwide. ‼️ Start your career in robotics today: github.com/Seeed-Projects… ~~ ♻️ Join the weekly robotics newsletter, and never miss any news → ziegler.substack.com

@NikolausWest experiment cycle time is the real competitive variable in robot learning. anything that compresses the loop from data change to training run is a structural advantage.

If you’re serious about robot learning you (unfortunately) need to know about video compression. Camera streams dominate data volumes for most datasets at 90+% even when compressed. Video is more complicated to deal with but the size wins are too big to give up. The unit of compression is a Group Of Pictures (GOP). In the simplest case (what you should use in robotics), GOPs start with a keyframe (I-frame) that is followed by several delta frames (P-frames). Delta frames only need to encode the difference to the previous frame which is where the compression win comes from. That means to decode frame 15 of a 30-frame GOP you need to feed all the preceding frames in the GOP to the decoder to get out that one frame. The GOP controls the tradeoff between random access and compression. Why does this matter for robot learning? Because while training, dataloader performance is dominated by fetching and decoding video. To build a streaming dataloader (you need this for large datasets) it needs to take GOPs into consideration when fetching data for a time step. It’s hard enough to build a dataloader that doesn’t starve your GPUs that most teams forgo flexibility. That means researchers at most of the best funded robotics efforts currently wait around for large export jobs before training can start after each change to the dataset mix or the wrong hyperparameter. This situation obviously won’t last since they all know that experiment cycle times is a key lever to fast progress and the competitive pressure is enormous. If you want to compete in this space you need both flexibility and performance.

@anchoraadvisory adding headcount to a broken system is just scaling the dysfunction. constraint identification before resource allocation every time.

If your business feels chaotic, don't hire more people. Map your four constraints first: 1. Sales 2. Models 3. Systems 4. Marketing Every growing business has the same issue. They throw resources at the symptom, not the source. Find the one thing that's slowing everything else down. Fix that first. Everything else gets easier.

@togro42 absolutely

@fel1de speed is europe's problem cuz we europeans unfortunately rarely recognize failure as a lesson, but as a track record - a succeed or be forgotten mindset. this leads to caution, which slows us down.

Europe doesn't have a technology problem it has a speed problem rigor gets confused with caution slow gets called "methodical" careful gets called "strategic" meanwhile the deployment decisions that actually matter are being made in Shenzhen on a Tuesday while we're still in the committee meeting

@OnatAksaray 100%

@fel1de europe needs to increase the speed of implementation