# RISC-V Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/risc-v
> Markdown URL: https://aitinkerers.org/technologies/risc-v.md
> Technology record last updated: 2026-02-24T06:28:36Z
> Generated: 2026-09-21T15:41:59Z

RISC-V is the open-standard Instruction Set Architecture (ISA) that eliminates proprietary licensing fees to enable custom silicon innovation.

Managed by RISC-V International (a Swiss-based non-profit), this modular architecture allows developers to build everything from low-power microcontrollers to high-performance data center processors. It supports 32, 64, and 128-bit address spaces. Industry giants like NVIDIA and Western Digital already ship millions of RISC-V cores annually. The design relies on a small base ISA (fewer than 50 instructions) supplemented by specialized extensions: such as 'V' for vector processing or 'C' for compressed instructions. This flexibility lets engineers optimize hardware for specific workloads (AI, IoT, or automotive) without the restrictive costs or vendor lock-in associated with ARM or x86.

- Official technology site: https://riscv.org
- Public AI Tinkerers demos and talks: 1
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Building a Persistent Memory & Stateful Second Brain AI Agent](https://dhaka.aitinkerers.org/talks/rsvp_kSMaLnvvGGg)

Demonstrating context engineering in practice through Slatekore - an open-source starter kit that gives Gemini CLI persistent memory using Obsidian as the storage layer. 1. State Management Without Infrastructure How to use the file system as persistent state - your Obsidian vault becomes both the agent's memory and its knowledge base. No databases, no vector stores, no MLOps. 2. Context Engineering for Agent Behavior Crafting system prompts (GEMINI.md) and workflow files that define agent capabilities, constraints, and multi-step reasoning patterns. The prompt is the agent's configuration. 3. Tool Use Through Natural Interfaces Connecting the agent to real actions: creating files, managing tasks, building knowledge graphs - all through natural language commands backed by structured templates. Watch a stateful agent capture research, recall context from previous sessions, update its knowledge graph, and execute project workflows - without any model training or fine-tuning.

- Event context: AI Tinkerers Dhaka 2nd Meetup: Dhaka Builds with AI! — 2026-02-07 — Dhaka
- Public talk page: https://dhaka.aitinkerers.org/talks/rsvp_kSMaLnvvGGg

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