This document explains how tech cycles affect market changes. This knowledge helps our planning and how we advise clients.

Technology cycles

Our structured approach to spotting tech trends and turning them into winning bets. From identifying early signals to building solutions that matter.

Market thesis

How we craft a market thesis

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Logs are like the footprints of your LLM, tracking every move it makes. We will look at how logging can help you see beneath the top layer of a system, which can help you troubleshoot problems and better understand the system behavior.

Logging

Our documented takes on technology waves that shape our direction. Each arc explores breakthrough technologies, explains why they matter, and captures our evolving perspective on building better software.

Our bets 🧙‍♂️

Our takes on the waves that shape us

LLM-generated market thesis documents following our five-step methodology. Think of this as our research workspace where we collect and analyze tech trends before crafting final versions for our arc series.

Market thesis raw analysis

The official Brainery build-log. We're detailing our process for creating a 'second brain' designed for continuous learning and insight generation. Covers motivation, system design, and practical data-to-wisdom strategies.

§ Brainery 🧠

Brainery build log

Understand the automated processes and tools that transform Markdown content into the published Memo website, ensuring content quality and consistency.

The Memo build and content quality pipeline

Learn about the automated deployment workflow for the Memo platform, powered by GitHub Actions for seamless publishing and integration.

Automating static site deployment

Learn how we use DuckDB as a flexible and efficient intermediary storage solution in the Memo content pipeline.

DuckDB as intermediary storage

An exploration of how Dwarves Foundation automates Markdown quality using modular linting, generative formatting, and cross-repo CI/CD integration.

Markdown lint

Technical architecture of the Memo platform: components, data flow, and technologies for processing, storing, and rendering content.

Memo architecture

Learn how we use Git submodules to link and manage multiple content repositories in the Memo platform.

Managing content with Git submodules

Explore how the Memo platform utilizes Arweave for permanent content storage and blockchain integration for NFT minting.

Onchain permanent storage

Implementing a URL redirect system for NextJS static memo pages to create SEO-friendly, shareable URLs while maintaining backward compatibility.

Redirect and Alias

Learn why we chose a static site architecture for the Memo platform and how Next.js facilitates dynamic page rendering and content processing.

Build a static site by choice

A detailed look into the mcp-playbook's internal code flow, data handling for chat logs and prompts, and interactions with GitHub repositories like prompt-db and prompt-log. This technical deep-dive helps developers understand the implementation details for debugging and extending functionality.

MCP playbook code flow

Exploring the motivations behind the MCP Playbook, its role in establishing a dynamic runbook, and new patterns for capturing AI-generated knowledge like chat logs and prompts.

AI knowledge automation

Exploring the tooling and process used by Dwarves to transform engineering outputs into published content (videos, blogs, podcasts, etc.) for our community.

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