🌊 GTM Engineer

High-signal research for early-stage founders.

👋 Hello! I’m Ivan. I share research from the top 1% of founders and investors—helping founders navigate tech trends, scale startups, and raise capital.

Each month, I tackle founder-focused questions (send them here!).

Join 17K+ early-stage founders surfing tech waves:

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Summary

1. 🌊 How to setup an AI GTM tech stack

2. 🌊 Sales Tech Market

3. 🌊 State of AI Voice Agents

4. 🌊 AI Market Crash

5. 🌊 OpenAI Deep Research

6. 🌊 YC’s Request For Startups

7. 🌊 Chasing heat

8. 🌊 Great Reads

9. 💵 Iberian Deals

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🌊 How to setup an AI GTM tech stack

Spent an hour with Fivos Aresti (Head of Growth at ColdIQ) to unpack the key lessons from scaling GTM with AI tools for early-stage startups:

Here’s the tl-dr:

1. Manual Before Automation: Don’t overinvest in fancy tools early. Start with cold outreach via Gmail and LinkedIn. Founder-led content > Paid ads (especially pre-product-market fit).

2. Prioritize Channels Wisely: Early-stage startups should (generally) focus on:

   1. Outbound: Low-cost, high-impact. Start here.

   2. Inbound & SEO: Builds long-term compounding growth.

   3. Content: Founder-led content builds trust + leads. Work on spotting underpriced attention (i.e. today, Linkedin).

3. Data Enrichment = Your Secret Weapon: Use tools like Genesy, Clay and Apollo to scale personalization and automate research—turning basic outreach into super-targeted campaigns.

4. Protect Your Domain’s Reputation: Always use a secondary domain for cold outreach to avoid spam filters and maintain your primary email's deliverability.

5. GTM Engineer: The Role of the Future: This hybrid role will become standard—managing tech tools, automating outreach, and optimizing channel performance.

6. Build Your Personal Brand: LinkedIn isn’t too saturated. If you post consistently and add value, inbound leads and credibility follow. Your network is your unfair advantage.

P.s. if you want to support your boy, subscribe to the pod!

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🌊 Sales Tech Market Map ($30B+)

Source

I found a great breakdown on the state of GTM tech stack by

Aakash Gupta

.

Tl:dr + my favorite insights from the article:

• The sales tech market is massive—$30B+.

• AI is fundamentally reshaping sales workflows, not just improving efficiency.

• The best sales tools don’t replace people, they amplify top performers. Completely agree on this, its about human + machine.

• AI-Native > AI Add-On → Tools built around AI (Gong) outperform those bolting it on. Check-out Sunny Huang on how to best leverage data for sales there.

• Workflow Integration > New Destination → Winning tools blend into existing workflows.

• Vertical Focus > Horizontal Platform → Specialized solutions (i.e. Affinity.co for VCs, I can attest to that) are beating one-size-fits-all approaches.

• AI is transforming prospecting (hyper-targeted leads), conversation intelligence (real-time coaching), and revenue optimization (forecasting + dynamic pricing).

• The sales stack is moving from disconnected tools to fully orchestrated revenue engines. Which is awesome, but I wonder how long it'll still take for non-techie "circles" to adopt these.

My 2 cents:

• Winners probably won’t just provide AI but integrate it into workflows, making it "invisible" yet indispensable.

• The best companies won’t compete on just having a better model but on becoming the default tool sales teams rely on daily.

• There's a moat in becoming becoming the tool sales people instinctively use.

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🌊 State of AI Voice Agents

A16z published a very interesting analysis on the State of AI Voice Agents.

Tl-dr: Why Voice is an Interesting Category for AI Startups

• Voice is the most frequent and information-dense form of communication → AI makes it programmable for the first time, unlocking new applications.

• AI-powered voice agents replace human labor → They are cheaper, faster, and more reliable, often outperforming humans in customer service, scheduling, and transactions.

• 24/7 business availability → AI agents remove the 1:1 constraint of human work hours, allowing businesses to serve customers anytime, anywhere.

• Consumers will likely interact with AI through voice first → It could become the primary way users engage with AI assistants, virtual companions, or learning tools.

• Democratization of services → AI voice agents make previously inaccessible services (e.g., coaching, language learning) available to more people.

• Massive platform shift → AI voice tech is moving from infrastructure to applications, meaning now is the time for startups to build products leveraging this shift.

• Voice is the wedge, not the product → The real opportunity isn’t just voice-based AI products but platforms that use voice as an entry point to unlock larger markets.

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🌊 AI Market Crash

Source

The AI market crashed (a little) last week.

What happened, in simple terms:

• DeepSeek built a GPT-4-level model for just $5.6M, using H800 chips—a huge cost drop.

• This proves China can compete at the frontier despite U.S. chip bans.

• Investors panicked, realizing AI models are getting cheaper, faster than expected.

What it means for big tech:

• 𝗠𝗲𝘁𝗮: Cheaper AI fuels their consumer AI products

• 𝗔𝗽𝗽𝗹𝗲: More efficient models improve on-device AI

• 𝗔𝗪𝗦: Doesn’t need its own model, powers infrastructure

• 𝗚𝗼𝗼𝗴𝗹𝗲: Open-source make search competitors bigger

• 𝗡𝘃𝗶𝗱𝗶𝗮: AI efficiency lowers GPU demand, but reasoning models still need compute.

What it means for you / startups:

• Models will likely get commoditised. The real moat is becoming the tool people instinctively use.

• Right now, AI hype is all about the next big model. Long-term success is about adoption, distribution, and trust.

• These events suggest the biggest winners won’t just be model builders— but apps solving real problems.

P.s. Highly recommend Stratechery’s breakdown of this:

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🌊 YC Request For Startups: Spring 25

YC's latest request for startups mentions AI 15+ times.

Source: YC Spring 2025 Request for startups

Good insight into future tech waves:

My 2 cents:

• Models are starting to become commoditized.

• Distribution, trust, and UX are starting to emerge as real moats.

• Owning workflows / mindshare is on the rise.

• AI is shifting from model innovation → infrastructure optimization.

• Vertical AI agents could replace SaaS in many categories.

• AI-native platforms can outscale AI-enabled retrofits.

• Inference costs are the next major bottleneck.

On building moats:

This statement from @levie on X at Box resonated:

"If, on the other hand, the layer above the intelligence requires a heavy degree of critical business logic, workflows, proprietary customer data, integrations in other systems, or deep industry or line-of-business expertise, then there’s likely more of a moat over overtime. Even having highly specialized implementation and services capabilities can be a very useful advantage in the world of AI."

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🌊 OpenAI Drops Deep Research

Big impact on knowledge workers. Tl-dr:

• Instead of instant responses, it takes 5-30 minutes to conduct multi-step research. But for good "reason" ;)

• Browses the web, extracts data (tables, PDFs, images), and generates fully cited reports.

• Works like an analyst—asking clarifying questions before diving in.

• Built on OpenAI’s upcoming O3 model, trained for reasoning + retrieval.

• Outperforms humans on complex knowledge tasks (and scores 26.6% on Humanity’s Last Exam).

• Best hallucination-resistant OpenAI model so far, but still needs source checks.

Why it matters:

• This moves AI closer to being a real knowledge worker (and why you are seeing "agents everywhere" right now, even when you discount the hype).

• Its pretty amazing how instead of just regurgitating facts, it can plan, adapt, and synthesize new insights over time.

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🌊 Chasing Heat

Despite all the current AI hype -

Rex Woodbury

published a great reminder to “Play It Cool” - on the importance of Chasing Heat vs. Being Contrarian in Venture Capital.

A good reminder to keep critical and independent thinking present:

Source

8 "Sleeping" tech waves, overshadowed by the AI noise that I’m excited about:

1. 𝗔𝘂𝘁𝗼𝗻𝗼𝗺𝗼𝘂𝘀 𝗥𝗼𝗯𝗼𝘁𝗶𝗰𝘀: In dynamic environments like construction, agriculture, or disaster response.

2. 𝗘𝗱𝘂𝗰𝗮𝘁𝗶𝗼𝗻: Personalized and immersive learning, internationalization, and language adaptation.

3. 𝗦𝗽𝗮𝗰𝗲 𝗘𝘅𝗽𝗹𝗼𝗿𝗮𝘁𝗶𝗼𝗻: Mining, autonomous infrastructure, and telepresence exploration.

4. 𝗘𝗻𝗲𝗿𝗴𝘆: Smart grids, dynamic management, advanced materials, and self-repairing infrastructure.

5. 𝗕𝗶𝗼𝘁𝗲𝗰𝗵 / 𝗛𝗲𝗮𝗹𝘁𝗵𝗰𝗮𝗿𝗲: New drug discovery, prosthetics, cognitive tools, and personalized medicine.

6. 𝗟𝗼𝗻𝗲𝗹𝗶𝗻𝗲𝘀𝘀 𝗘𝗽𝗶𝗱𝗲𝗺𝗶𝗰: solutions for meaningful social interactions, virtual companionship, and community-building in hybrid spaces (physical / digital).

7. 𝗪𝗲𝗹𝗹𝗻𝗲𝘀𝘀: AI-enabled tools for stress management, personalized mental health therapies, sleep optimization, digital detoxes, and neuroadaptive well-being solutions.

8. Human-computer interaction: AR/VR/XR as a potential AI interface + everything that touches human-computer interaction enhancements. Check-out Meta Ray-Ban’s glasses (I actually think this is underrated).

Source

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🌊 Other Great Reads

• Moving beyond founder-led sales by

  Kyle Poyar

• AI as Electricity by

  Eric Flaningam

• Sales Tech Market Map 2025: The $30B Industry Breakdown by

  Aakash Gupta

• AI voice agents report by a16z

• State of Venture 2024 by AngelList

• YC Spring 2025 Request for startups by Y combinator.

• Aaron Levie from Box on AI moats

• Ark invest 2024 ideas

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💵 Iberian Deals

You love startups and want to enjoy a Spanish lifestyle?

Come join the Spanish startup ecosystem.

Here’s a list of recently funded startups:

• TravelPerk (business travel platform) raised €190M

• Quibim (AI-powered medical imaging) raised €47.6M

• H2SITE (on-site hydrogen production) raised €36M

• Mundimoto (motorcycle leasing) raised €21.1M

• Wooptix (semiconductor metrology) raised €10M+

• Crescenta (PE & VC platform) raised €7M

• Zynap (AI-powered cybersecurity) raised €5.7M

• Genesy (AI for sales) raised €5M

• Weecover (embedded insurance) raised €4.2M

• Redegal (digital services) raised €3.8M

• Sycai Medical (AI for healthcare) raised €3M

• Kanguro (last-mile logistics) raised €2M

• Brickken (tokenization of assets) raised $2.5M

• Kymatio - Activate Human Firewalls raised €1.85M

• xNova International (saas) raised €1M

• FisioReact (at-home healthcare) raised €1M

• Robinsun (€600K, solar energy)

• Caleida (€500K, AI-driven marketing)

• Peimi (€415K, SaaS for sales compensation)

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Source

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About Me:

I write write a newsletter for early-stage founders and invest in startups (€200K-2M). Previously, I built products at Facebook, helped scale Bloomreach ($2B+), and bootstrapped Revenue Squared. I also love to surf and practice BJJ.