Haun Ventures X Antidote

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About

GM, my name is Axel. I am currently Regional Lead for Western Europe at Coinbase, and I have been building and investing in tech for over half a decade.

This place is my personal space where I store thoughts and experiments. You can reach me on the socials below.

Tech 2030

Tech is the most intellectually interesting industry in the world. It is the one category that rewards continuous curiosity and optimism at an outsized scale.

Tech is a cyclical industry, driven by macroeconomic forces and technological disruption. Usually, highs are pushed by a singular catalyst.

I believe right now might be the most interesting and dynamic environment ever for tech. This is because we are not witnessing one singular technological disruption, but rather three major technologies that will work together to reboot the entire tech stack and completely redefine the digital economy. I call it the [V I P] framework.

Value Layer:
Blockchains

The financial operating system gets rebooted on blockchains as the largest open and interoperable financial stack. Every asset will live on this shared stack, which unlocks a global network with more human and AI participants. In turn, new markets are created that unlock new opportunities. The flywheel of new assets, new markets, and new users has a compounding effect that expands digital GDP massively.

We have witnessed the first waves with tokens, stablecoins, and money markets, but sooner or later, every asset will live on blockchain rails.

Interface Layer:
Augmented reality

Augmented Reality and spatial computing will fundamentally change how we interact with the digital world. Interfaces are no longer restricted to a limited two-dimensional screen canvas. They expand to spaces and positions. They can attach to information that is anchored in the physical space. They can add another layer or alter the physical world.

The best practices for interfaces have to be rediscovered for every application, whether B2B SaaS or a social network. What does a PowerPoint look like in this new paradigm? This unlocks opportunities for new entrants that disrupt incumbents that adopt this new computing platform more slowly.

Productivity Layer:
AI

Throughout history, work has continuously shifted from laborious, nuisance activities to more abstract, conceptual tasks. The first shift occurred during the Industrial Revolution, where machines increasingly outsourced physical labor.

Artificial Intelligence is the ultimate evolution of this. Work in the future will look much more like the work of CEOs of larger corporations: designing systems, orchestrating work, and delegating tasks.

Every productive task and action will be fulfilled by AI agents, whether in the digital (agents) or physical (robots) world. What remains are humans who provide the vector.

Compounding Effects

These technologies do not work in isolation, but compound with each other and unlock new use cases. For instance:

CE 1: Agents moving value on-chain

CE 2: Data collection through human POV

CE 3: AI agents that guide you through the physical world

...

CE n: Digital collectibles gain value as AR allows humans to wear them in the physical world.

VC.ai

In the year 2026, VC cannot be done the same way it was in 2020. Agentic loops have become so powerful that they can replace junior VCs in many of the critical functions: sourcing, thesis building, and even first-pass analysis. Eventually, more and more AUM will be directly or indirectly managed by agents. I think being at the forefront here can produce significant alpha.

The skill set to build this requires both technical understanding and VC experience to connect the dots and set up an agentic harness that can separate signal from noise without oversight.

This agentic VC setup, at its current level, already completely changes how I research topics and gain an understanding of tech trends. This agentic system is 24/7 on the hunt for new alpha.

Architecture

Fundamentally, this agentic system works on four layers: Data, Thesis, Evidence, and Opportunities. These layers are connected and have feedback loops that can refine each other. All of this works continuously and 24/7.

The agentic system is powered by Obsidian and a Hermes agent harness that runs several subagents.

Data

The agentic system continuously monitors high-value data sources across the web, including social media, academic research, and high-signal podcasts and YouTube shows. It studies articles, opinions, and scientific papers. Initially seeded by a human-curated list, it quickly identifies its own data sources and expands the network of data sources to monitor.

Human-AI loops strengthen this mechanism to ensure a high-dimensional dataset that remains high-signal.

It scrapes this dataset continuously and constantly filters for high-quality data points and humans.

Thesis

Theses are the fundamental primitives of the agentic VC setup. They form before categories are formed and chase narratives that might be 3-5 years from maturity. Unlike static memos that only capture a moment in time, they are living and fluid concepts that are constantly maintained and refined by the agentic system.

Each thesis is continuously refined through supporting arguments, counter indicators, and signals to watch in order to provide an expert-level current read and conviction level on each thesis. Just like with human analysts, seniors can provide feedback to steer and refine the direction of research the agentic system is taking.

The agentic VC uses these lessons to refine its methodology and suggest its own theses.

Evidence

Evidence points are the main data points for agentic theses. They are early, unstructured, anecdotal proof points that suggest the validity of a thesis. As such, their predictive power develops through their cumulative mass.

The agentic system filters the data stream and matches evidence points to each thesis. Evidence can occur in various formats: an academic paper that potentially removes a technological bottleneck, builders experimenting with an interesting MVP, high-profile investors writing about points touching the thesis, or new startups forming around a thesis. They can appear in different formats and across different channels.

Individual evidence points can vary in weight and can even be counterpoints that question or reshape the thesis.

Theses

Theses are the fundamental intellectual primitives. Explore a number of theses I had. Each thesis is automatically created and maintained by my VC.ai system.

Scroll through the theses and click on one to explore the evidence VC.ai has gathered behind each thesis.

Agentic Dopamine01

Augmented Reality as the future interface layer02

One-person billion-dollar companies03

Agentic VCs04

Decentralized pre-training05

Long Europe06

University will be disrupted07

Consumer robotics08

Human enhancement will become a mainstream performance market09

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DATA

THESIS

EVIDENCE

OPPORTUNITIES

BRAIN

About

Tech 2030

Value Layer:
Blockchains

Interface Layer:
Augmented reality

Productivity Layer:
AI

Compounding Effects

VC.ai

Architecture

Data

Thesis

Evidence

Thesis

Theses

Agentic Dopamine