# Effect Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/effect
> Markdown URL: https://aitinkerers.org/technologies/effect.md
> Technology record last updated: 2026-03-01T05:24:33Z
> Generated: 2026-09-22T03:52:22Z

Effect AI is a decentralized protocol: it connects human workers, AI models, and compute power for scalable, real-time artificial intelligence execution.

This is Effect AI (The Effect Network), a decentralized P2P network built for high-demand AI tasks. We’ve unified people, models, and compute into a single capability network for scalable, real-time AI execution. The protocol utilizes three core elements: The Effect Worker (for human-driven tasks and low-friction payouts), The Effect Staking (for securing the network and sharing protocol rewards), and a decentralized AI marketplace for models and compute. Our focus is on unlocking composable AI infrastructure, ensuring a secure, transparent, and efficient system for all participants: build, earn, and scale with EFFECT.

- Official technology site: https://effect.ai
- Public AI Tinkerers demos and talks: 2
- Result page: 1 of 1

## Recent Public Talks and Demos

### [How we built a complete financial product in 3 weeks from 0](https://valencia.aitinkerers.org/talks/rsvp_96ioMlRX_TU)

Early January my co founder showed me a Google Sheets with raw financial data that he used to track the markets and find early market opportunities in the best leading industries. He was able to find golden opportunities but it required a lot of tedious work, and was limited to a couple of industries. That's why we decided to automate the core idea and scale it to 130 industries spanning more than 5300 stocks. Three weeks later, the core features are ready, and we have feedback from seasoned financial analyst praising the quality of the extracted data and user experience of Zensei.

- Event context: AI Tinkerers Valencia February Meetup — 2026-02-17 — Valencia
- Public talk page: https://valencia.aitinkerers.org/talks/rsvp_96ioMlRX_TU

### [Lessons learned in building a MCP server for flashcards](https://milan.aitinkerers.org/talks/rsvp_FWbK9bmPHnM)

We recently built and launched an MCP server for rember.com that let's you create spaced repetition flashcards from you LM chats. Building a MCP server is easy, building a great one is hard. In this demo we share a few lessons learned along the way, including: prompt engineering for the tool description, strategic use of the tool call response, and testing. The MCP server is open source, and the demo will be supported with code.

- Event context: AI Tinkerers Milan - May 8, 2025 — 2025-05-08 — Milan
- Public talk page: https://milan.aitinkerers.org/talks/rsvp_FWbK9bmPHnM

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