Techno Tim joins Adam to dive deep into the state of homelab’ing in 2026. Hardware is scarce and expensive due to the AI gold rush, but software has never been better. From unleashing Claude on your UDM Pro to building custom Proxmox CLIs, they explores how AI is transforming what’s possible in the homelab. Tim declares 2026 the “Year of Self-Hosted Software” while Adam reveals his homelab’s secret weapons: DNSHole (a Pi-hole replacement written in Rust) and PXM (a Proxmox automation CLI).

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Featuring:

• Techno Tim – Website, GitHub, LinkedIn, Mastodon, X
• Adam Stacoviak – Website, GitHub, LinkedIn, Mastodon, X

Show Notes:

People

• Techno Tim - Tim Stewart’s website, YouTube channel, and documentation hub
• Crosstalk Solutions - Chris’s channel, mentioned for building custom Ubiquiti API tools

Virtualization & Infrastructure

• Proxmox VE - Open-source virtualization platform for VMs and containers
• TrueNAS - Enterprise-grade open-source storage operating system built on ZFS
• HexOS - Consumer-friendly NAS OS built on TrueNAS (in development)
• Proxmox VE Helper Scripts - Community-maintained scripts for easy LXC and VM deployment

Self-Hosted Software

• Paperless-NGX - Self-hosted document management system with OCR
• Paperless-GPT - AI-powered enhancement for Paperless-NGX using LLMs
• Ollama - Run large language models locally on your own hardware
• Open WebUI - Self-hosted web interface for interacting with local LLMs
• Plex - Media server for organizing and streaming your personal media library
• Home Assistant - Open-source home automation platform
• Pi-hole - Network-wide ad blocking via DNS filtering

Document Intelligence & RAG

• Dockling - IBM’s open-source document parsing library for AI/RAG pipelines
• PaddleOCR - Multi-language OCR toolkit for document recognition

AI & Agents

• Claude - Anthropic’s AI assistant, used for homelab automation in this episode
• OpenCode - Open-source AI coding agent (mentioned as potential homelab tool)
• Model Context Protocol (MCP) - Protocol for connecting AI models to external tools and data

Networking

• Ubiquiti - Enterprise networking gear popular with homelabbers (UDM Pro, UniFi)
• Tailscale - Zero-config VPN for secure networking between devices

Container & Orchestration

• Docker - Container platform for packaging and running applications
• Kubernetes - Container orchestration for managing containerized workloads
• Fly.io - Platform for running containers close to users globally

Monitoring & Observability

• Grafana - Open-source analytics and visualization platform
• Prometheus - Open-source monitoring and alerting toolkit

Security & Authentication

• Bitwarden - Open-source password manager (self-hostable)
• Authelia - Open-source authentication and authorization server

Databases

• MariaDB - Community-developed fork of MySQL
• Redis - In-memory data store for caching and messaging
• PostgreSQL - Advanced open-source relational database

Hardware Mentioned

• Intel Optane - Ultra-low latency storage drives (discontinued but prized for ZFS special vdevs)
• NVIDIA GeForce RTX 3090 - GPU used for Plex transcoding and local AI inference

Concepts & Techniques

• ZFS Special Vdevs - ZFS feature for accelerating metadata and small file operations
• PCIe Bifurcation - Splitting a PCIe slot to support multiple NVMe drives
• Medallion Architecture - Bronze/Silver/Gold data lake pattern discussed for document ETL

Something missing or broken? PRs welcome!

This week on the GeekWire Podcast: Newly unsealed court documents reveal the behind-the-scenes history of Microsoft and OpenAI, including a surprise: Amazon Web Services was OpenAI’s original partner. We tell the story behind the story, explaining how it all came to light.

Plus, Microsoft CEO Satya Nadella debuts a new AI catchphrase at Davos, startup CEO Dave Clark stirs controversy with his “wildly productive weekend,” Elon Musk talks aliens, and the latest on Seattle-area physical AI startups, including Overland AI and AIM Intelligent Machines.

Subscribe to GeekWire in Apple Podcasts, Spotify, or wherever you listen.

With GeekWire co-founders John Cook and Todd Bishop; edited by Curt Milton.

Aspire, Microsoft’s open source, cloud native development platform, now supports JavaScript, TypeScript, Python, and Java as first-class citizens.

“With Aspire 13, JavaScript and TypeScript developers get to join the party — and I’m not talking about some half-baked afterthought integration,” wrote Microsoft Senior Software Engineer David Pine on Microsoft’s developer blog. “This is first-class, full-featured support for orchestrating your JavaScript apps in distributed systems.”

The tool was previously called .Net Aspire, but .Net has been dropped since Aspire is a polyglot.

The code-first orchestration platform is used to build, debug, and deploy distributed applications, such as cloud native apps or microservices.

Aspire provides a set of curated components and tooling, including a developer dashboard. Its goal is to simplify starting, building, and running cloud native applications.

Pine explains how to run JavaScript code in three different scenarios, including Node and Vite.

Rust 1.93.0 upgrades musl C library

Rust released version 1.93.0 this week. The big news here is that it upgrades the version of the musl C library used when building certain Linux apps.

This ”should make portable Linux binaries that do networking more reliable, particularly in the face of large DNS records and recursive nameservers,” according to the Rust blog about version 1.93.0.

That translates into apps that will be more stable when running in Kubernetes, Docker, or complex cloud environments where DNS records are large and complex.

If you have a previous version of Rust installed via rustup, you can update to 1.93.0 with:

$ rustup update stable

A hackathon for useful applications

Are you working on a side project that’s especially useful and an actual application — not just a demo?

If so, you might want to submit it to the Proof of Usefulness Hackathon, which runs each month until June 5. It’s “a global developer competition that rewards one thing and one thing only: Real-world usefulness,” according to HackerNoon.

What’s interesting about this hackathon is that it will offer monthly rewards and recognition for more than 40 winners over the next six months. Every two months, there will be major software prize cycles for top startups. There’s also $1,500 worth of inventory for each participant.

The hackathon is open to individual developers and budding startups. It provides access to free tools that help you build and promote something meaningful.

While any technology is welcome, the bigger prizes will go to AI and machine learning (ML) projects that use the sponsor technologies. This week, the site explained how to enter the event, which is a bit of a process.

The event is sponsored by HackerNoon, Bright Data, Neo4j, Storyblok, and Algolia.

Benchmark AI models your way

Kaggle, a Google-owned online AI developer community, recently launched a new feature that lets you create custom benchmarks for evaluating AI models.
The feature is called Community Benchmarks for its Benchmarks platform. It can be used to design, run, and share the custom AI model benchmarks.

Here’s why it matters: AI is evolving so rapidly that it’s become difficult to evaluate model performances, according to a blog post by Michael Aaron, a Kaggle software engineer, and Megan Risdal, a product lead for Kaggle.

“Not long ago, a single accuracy score on a static dataset was enough to determine model quality,” Aaron and Risdal write. “But today, as LLMs evolve into reasoning agents that collaborate, write code, and use tools, those static metrics and simple evaluations are no longer sufficient.”

Among the features of Community Benchmarks:

• Custom task construction lets developers define tasks for code execution, tool use, and multiturn conversations using the new kaggle-benchmarks SDK.
• State-of-the-art model access to run custom benchmarks against models from Google, Anthropic, and DeepSeek for free, within a quota.
• Audit-ready reproducibility means the framework captures full inputs, outputs, and model interactions, replacing anecdotal testing with verifiable data.
• Dynamic leaderboards so developers can group multiple tasks into a single benchmark to generate comparative rankings across a suite of leading models.

The Kaggle Benchmarks repo has examples of prebuilt tasks.

The post Distributed apps platform Aspire supports JavaScript, Python appeared first on The New Stack.

Download full source code.

I was recently talking with a friend about the factory and strategy patterns, how they could be used together. He was familiar with the factory, but not the strategy.

The factory lets you create the kind of object you want on the fly without explicitly calling new on a concrete class. The strategy pattern lets you execute some method defined in an interface without knowing which implementation is actually going to be used. These two patterns complement each other very well.

I gave the example of a messaging client that can send messages. Each message has some text content and a destination. All three need to be handled differently, especially voice, which would require some text to speech processing. The messaging client uses a factory to create the correct type of messaging service to send the message with. The factory looks at the message type to return the appropriate service - SMS, email, or voice, but only returns an interface (the strategy).

The messaging client is completely decoupled from the messaging services; it only knows about the messaging service interface, allowing new services to be added without needing to alter the client application.

The code is pretty simple to understand, so I won’t go through it here. Have a look at the full source code, which is attached.

Download full source code.