Discover how our two-week MVP harnesses AI-driven, real-time voice processing to streamline interviews, reduce bias, and accelerate hiring success

Building MVP for AI-driven interview platform

An in-depth look at Dwarves' monthly Project Reports system - a lean, efficient system that transforms communication data into actionable intelligence for Operations teams. This case study explores how we orchestrate multiple data streams into comprehensive project insights while maintaining enterprise-grade security and cost efficiency.

Project reports system: a case study

A case study exploring how we built an AI-powered travel assistant using Ruby and AWS Bedrock, demonstrating how choosing the right tools over popular choices led to a more robust and maintainable solution. This study examines our approach to integrating AI capabilities within existing Ruby infrastructure while maintaining enterprise security standards.

AI-powered Ruby travel assistant

A deep dive into building a robust transfer tracking syste m for Binance accounts, transforming disconnected transaction logs into meaningful fund flow narratives through SQL and data analysis

Building better Binance transfer tracking

This article provides an overview of the importance of tracking Bitcoin-Altcoin performance indicators in a trading strategy known as Hedge, and explains how to visualize this data effectively. It also demonstrates how to render a chart for this strategy using Matplotlib and Seaborn

Tracking Bitcoin-altcoin performance indicators in BTC hedging strategy

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

This page outlines how developers can connect to and utilize Brainery's extensive knowledge base and AI-driven capabilities. By integrating a straightforward MCP configuration, you can seamlessly access powerful insights directly within your existing development tools and workflows.

Access the brainery

An overview of Brainery's architecture, detailing how it ingests, processes, and transforms data from diverse sources into a dynamic knowledge base.

Architecture

What’s the point of being human if AI thinks for us? Explore how emotions, creativity, relationships, and purpose make humanity unique in an AI-driven world.

The point of being human if AI can think?

How data flows through Brainery's second brain system, from Discord, Memo Blog, and GitHub sources to TimescaleDB via MCP, with an LLM-powered interface for natural language queries.

Data flow in Brainery

A migration-less, append-only database design using TimescaleDB's hypertables and continuous aggregates to capture observational data and detect emerging patterns through LLM analysis.

Database design and philosophy

Exploring the core motivations and principles behind building a personal knowledge management system, a true second brain.

Continual learning DIKW pyramid

Discover the human edge in empathy, creativity, intuition, and purpose, where we surpass AI. Learn practical solutions to overcome challenges like AI reliance and isolation to thrive in a tech-driven world.

Human edge in AI world

Explore how we solved the catastrophic forgetting problem in LLMs by building an external knowledge system that mimics learning through context manipulation, without touching the model's parameters.

Build a brain that never forgets

This post explains the multi-stage process of transforming raw data into structured information, and then synthesizing that information into persistent insight and knowledge within a true second brain, leveraging tools like TimescaleDB and LLMs.

Promoting raw data to insight

See how Brainery changes your reading game, helping you learn more and find new things to read, all in a smart loop.

Reading after brainery

Does using AI make you pretend to know? Learn how a second brain helps you truly understand by curating and connecting knowledge, not just querying AI.

Does AI make you pretend to know?

A Request for Comments (RFC) detailing a comprehensive specification for implementing OAuth 2.1 authorization within the Model Context Protocol (MCP) when using Server-Sent Events (SSE) as the transport mechanism, ensuring vendor-neutral security for AI-to-tool communication.

MCP authorization over SSE

RFC proposing a novel approach to track concept evolution using TimescaleDB with pgvector/pgvectorscale, enabling historical semantic analysis and preventing catastrophic forgetting in continual learning systems.

Append-only concept embedding log

Building systems that actually learn and get smarter over time is hard, facing challenges with traditional databases and LLMs. This post outlines an approach to building a true second brain that continuously learns, generates insight, and remembers it through an append-only log and flexible data structures.

Building use-cases

Discover why a personal second brain is still valuable in the AI era. Learn how it curates knowledge, sparks creativity, and complements LLMs for deeper insights.

Why build a second brain when AI can think for us?

Explore the system design behind scalable AI agents, featuring modular architecture, streaming responses, and automated task scheduling for social platforms.

Building an AI-powered agent system with OpenRouter SDK and Web3 technologies

A technical case study detailing the implementation of an AI chatbot agent in a project management platform. Learn how the team leveraged LangChain, LangGraph, and GPT-4 to build a multi-agent system using the supervisor-worker pattern.

Building chatbot agent to streamline project management

A technical case study for implementing centralized monitoring for a trading platform using Grafana and Prometheus, focusing on real-time alerts, data integrity, and resource optimization to prevent financial losses.

Setup centralized monitoring system for Hedge Foundation trading platform

Guide to building a research-first tech company and community by turning ideas into impact, building a trusted brand, and fostering growth.

Build a research-first tech company

Explains the core concept of profitability for a company in simple terms, revenue must exceed costs for sustainable growth.

Profitable: make more money than you spend

Explains how connecting cutting-edge research with practical application drives innovation, provides solutions, and creates impact.

Research to Value: Turn ideas into products or impact

Discusses how to build a company that thrives long-term through resilience, community, and continuous innovation.

Sustainable: Stay strong over time

This article shares a workflow for making slide decks with Overleaf and ChatGPT. It solves issues like slow content creation using ChatGPT and formats with Overleaf’s themes. It includes examples, tips, and a Dify automation for engineers.

Create slides with Overleaf and ChatGPT

Implementing a Golang-based visualization for crypto market performance indicators, focusing on Bitcoin vs Altcoin dynamics and trading strategy effectiveness through interactive charts and data analysis

Visualizing crypto market performance: BTC-Alt dynamic indicators in Golang

A guide to implementing data archival and recovery strategies for high-volume transactional application.

Building a data archive and recovery strategy for high-volume trading system

Discover how a trading platform mitigated database access risks, enhanced security, and ensured data integrity through role-based access control, network isolation, MFA, and robust logging. Learn about the strategies and tools, like Teleport, that transformed operational efficiency and reinforced client trust.

Database hardening for a trading platform

Build a MCP client for Discord

A comprehensive guide on improving cryptocurrency transfer logging systems to provide better transparency and traceability for users and developers.

Transfer mapping: enhancing loggers for better transparency

Implementing Binance Futures PNL Analysis page with Phoenix LiveView to optimize development efficiency. This approach reduces the need for separate frontend and backend resources while enabling faster real-time data updates through WebSocket connections and server-side rendering.

Implement Binance Futures PNL analysis page by Phoenix LiveView

Memo is our knowledge base, capturing collective learnings and activities. This build log documents the technical journey of creating and maintaining the platform.

§ Memo 📝

Memo 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

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

Memo profiles

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

Redirect and Alias

Discover how a unified Makefile simplifies the development workflow for the Memo platform, standardizing toolchain and speeding up common tasks.

Streamline development with a single Makefile

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

How do we migrate normal table to timescale table to optimized data storage

Migrate regular tables into TimescaleDB hypertables to improve query performance

§ How we build our monitoring system

A practical guide to building monitoring systems that actually work. We share our approach to making smart decisions about what to monitor, how to collect data, and when to add complexity.

Approach to building monitoring

Hard-learned lessons from building monitoring systems in production. We share common mistakes to avoid and practical strategies for growing your monitoring capabilities over time.

Monitoring best practices

Understanding the building blocks of effective system monitoring. We break down synthetic monitoring, instrumentation, logging, and tracing to help you build observability into your applications.

Monitoring components

How to connect metrics, logs, and traces for faster debugging. We explain the investigation flow and practical strategies for correlating data across your monitoring stack.

Correlation layer

Practical implementation guidance for setting up comprehensive monitoring across all aspects of your system - from infrastructure to code quality and team performance.

Implementation guide for monitoring systems

A comprehensive prompt template to get tailored metrics recommendations for any system. Use this with ChatGPT, Claude, or other LLMs to design monitoring that actually matters.

LLM prompt for metrics planning

A practical guide to choosing the right metrics for system health monitoring. We cut through the noise to focus on metrics that directly impact your users and business.

Which metrics actually matter

Understanding when to use trace_id versus request_id, and how to implement correlation that actually helps during incidents. We explore practical patterns for different system scales.

Trace IDs and request IDs that work

Understanding when to invest in comprehensive monitoring versus keeping it simple. We explore how system scale, user impact, and team resources should drive your monitoring decisions.

Does monitoring scale with your system?

Exploring when synthetic monitoring alone makes sense and how to maximize its value when you can't instrument your systems or need to keep teams separate.

Can you rely mostly on synthetic monitoring?

Discover the technical strategies behind optimizing a Binance trading platform, reducing initial load times to under 1 second for enhanced trader productivity.

Optimizing initial load time for a trading platform

Designing the UI for a blockchain-based hedge fund platform like Hedge Foundation is not just about creating a visually appealing interface. The real challenge lies in ensuring that complex financial data is presented in an intuitive, understandable way that helps users make quick investment decisions. Optimizing the UI plays a crucial role in allowing investors to access accurate data without feeling overwhelmed by excessive information.

Hedge Foundation - optimizing UI for effective investment experience

A technical exploration of implementing the data snapshot pattern for efficient historical data persistence

Implementing data snapshot pattern to persist historical data

An index and introduction to the mcp-playbook server documentation series, covering its purpose, setup, and operational flows.

Understanding and using the MCP playbook

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.

MCP Playbook: Automating Knowledge from AI Interactions to a Living Runbook

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.

MCP playbook code and data flow

How data flows through the MCP Playbook server, from MCP client requests to tool execution and interactions with the file system and GitHub.

Data flow in MCP Playbook

A step-by-step tutorial on configuring and running the mcp-playbook server, including GitHub token creation and using npx.

Setting up the MCP playbook server

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

Content publication tooling

A technical case study of creating an automated system that downloads videos, processes audio, and generates transcripts using AI services like Groq and OpenAI.

Building data pipeline for OGIF transcriber

A detailed look at how we rebuilt historical trading PnL data through an efficient data pipeline approach, transforming a complex problem into a maintainable solution.

Reconstructing historical trading PnL: a data pipeline approach

Discover how Dwarves Foundation uses Upptime and GitHub Actions for transparent public uptime monitoring while securely keeping tabs on internal services.

Secure and transparent uptime monitoring with Upptime and GitHub secrets

§ How to vibe

A guide to effective planning in software development, winning with AI-assisted workflows.

Updates > Build log