AI strategy is now a central political question, following the release of the AI Action Plan. In 3 months at dAGI Summit, we’ll discuss how society will function in the post-AGI era. The future of AI won’t be owned by a few. It’s being built by those creating open models, autonomous agents, and decentralized infrastructure. Join a one-day gathering of builders, researchers, and founders shaping the open AI economy. Hear from top voices across leading AI and tech organizations. The program covers the key building blocks of an open future: – Open-Source AI: Creating transparent, accessible models. – Decentralized AI Systems: Resilient, censorship-resistant compute and data layers. – Multi-Agent Coordination: Platforms for complex autonomous agent networks. – AI-Native Economies: Building open, transparent, inclusive economic systems. – Cybernetic Systems: AI with feedback loops for local, adaptive coordination. If you believe AGI should not be locked behind corporate walls, this summit is for you. Join us and be the change. 📍 San Francisco • 🗓 October 24 Hosted by @cyberFund_ + @delphi_labs

AI is making economy intent-driven: UI Business logic Integrations Data access Pricing All becomes dependent on the user task and shapes as you go.

Find myself running 2-3 instances of Claude Code at the same time recently. New kind of product & engineering management -- being a shepherd for agents.

This is the sign that crypto is still not being taken seriously

VC-subsidized tokens are something web3 and AI have in common

My dev and VC research workflow has shifted quite a bit over the past month. I barely use Cursor agent anymore - just autocomplete. Most tasks are handled by Claude Code, usually with 2 or more agents running in parallel. Here’s a typical project flow: - Gemini 2.5 Deep Research for digging into the problem background, analyzing 100+ pages and articles on the topic, and writing a full report - Grok-4 for deep conceptual work - mapping out the problem space, writing the PRD or a requirements doc with expected outcomes - Taskmaster (screenshot) for project planning - breaking a big project into 20–50 tasks - Creating and /docs - the most important step in my view: holds the core philosophy and working principles of the project (for code, every rule and edge case; for research, all constraints and methods); /docs holds detailed AI-generated instructions for every major step - If the task is easy to parallelize, I use something like claude-flow to spin up a swarm or hivemind of dozens of agents working simultaneously - After every significant milestone - a GitHub commit, like a save point in a video game - Claude tokens usually run out (my $100/month plan isn’t enough anymore), but you can plug Claude Code into Kimi via Groq

this is most definitely a test

Startup pitching events are surprisingly popular in Lisbon with mostly European companies pitching

AI to replace your whole marketing team, check out the demos

Soham is just a test before AI-coworkers will become majority of co-workers at every company