🦾 From Model to Agent: let’s build our own Claw, live in C#

Hi! So, you’ve probably used a “claw” already. One of those CLI agents that plans, runs tools, remembers what it did, and more. Cool. But have you ever stopped to think about what’s actually going on inside one? 🤔 Turns out, a claw is really just an agent harness: a loop around a model, wired up with tools, planning, memory, approvals and observability.

elbruno.com

🧠 MagenticBrain Is Now Supported in ElBruno.LocalLLMs

TL;DR KnownModels.MagenticBrain is now ready for local .NET usage with ElBruno.LocalLLMs. ONNX package is available at: Original model source: This support is designed to power end-to-end agentic app experiences such as: Why this model is important (and what it is designed for) MagenticBrain is not just another general-purpose chat model. It is designed for agent orchestration…

elbruno.com

🚀 Fara 1.5-9B Is Now Fully Supported in ElBruno.LocalLLMs

TL;DR Fara1.5-9B now works end-to-end in C# with ElBruno.LocalLLMs. The validated multimodal ONNX package is published at: You can run image+text inference locally with LocalVisionChatClient and KnownModels.Fara15_9B. This closes the loop for end-to-end local agent experiences in: When Microsoft Research introduced MagenticLite, MagenticBrain, and Fara1.5, it made a strong case for practical local agentic experiences:

elbruno.com

🧠 Someone Asked Me to Add a 975B Model to a LocaLLMs, here’s Why we Can’t (Yet)

⚠️ This blog post was created with the help of AI tools. The geeky fun and the 🤖 in C# are 100% mine. TL;DR Someone asked me to add Inkling — Thinking Machines' shiny new open-weights model — to ElBruno.LocalLLMs. I did the evaluation, and the answer is: not for now. 🔴 Inkling is a 975B-parameter, Mixture-of-Experts, multimodal (text + image + audio) model.

elbruno.com

I built a weekly AI news digest with GitHub Agentic Workflows. Here is how it works.

This blog post was created with the help of AI tools. I used them to organize ideas and write a first draft, but the workflow, the code, the testing, and the 🤖 enthusiasm are mine. Hi! I like reading AI news. I do not like opening seven tabs, comparing five versions of the same announcement, and wondering whether the most important developer update was hidden under an article about a robot making coffee.

elbruno.com

Foundry Local Monitor — See every local AI model your machine is running with Foundry Local

Hi! If you have been playing with Foundry Local to run AI models on your own machine, you probably ran into the same thing I did: you never really know what is running. You load a model from the CLI. Your C# app loads another one through the SDK. A Python script spins up its own. A .NET Aspire sample launches a proxy.

elbruno.com

Run the Right AI Model for the Right Copilot Task — No Cloud Credits Wasted

Hi! Part 1 of the CopilotHarness series Big models are great for heavy thinking. But what about simple questions — "rename this variable", "write a short docstring", "what does this function do"? Those don't need GPT-5 across the internet. They can be answered instantly by a model running on your own machine, offline, for free. This post shows you how to wire GitHub Copilot in VS Code to local models using three minimal proxies — one for Ollama, one for Foundry Local, one for Azure OpenAI — and how to run all three together with a single command.

elbruno.com

Local-first AI Agents in C#: Foundry Local, MEAI, and Microsoft Agent Framework

Hi! If you are building local AI apps in C#, you quickly hit a practical gap: Foundry Local SDK is great for local/on-device inference. Microsoft.Extensions.AI and Microsoft Agent Framework expect an IChatClient. There is no first-party Foundry Local -> IChatClient bridge yet. That is exactly why I created this library Nuget: Repo: Sample: ElBruno.MAF.FoundryLocal/src/ElBruno.MAF.FoundryLocal.Console at main · elbruno/ElBruno.MAF.FoundryLocal…

elbruno.com

GitHub Copilot and tokens: how to keep using AI without burning your budget in three prompts (some personal lessons learned!)

Hi! For a long time, many of us used GitHub Copilot as if it were unlimited magic: autocomplete, chat, agent mode, code review, increasingly powerful models, massive context, and long-running sessions that sometimes felt like a pair-programming marathon. And it worked. Well, mostly. Now, with usage-based billing and AI Credits, many developers are seeing something that used to be mostly invisible: every AI interaction has a cost.

elbruno.com

MAI-Image-2.5 support in ElBruno.Text2Image and the t2i CLI 🚀

Hi! Microsoft Build brought a wave of new AI model announcements, and one of the fun ones for image generation is MAI-Image-2.5. So, of course, I had to add support for it in my .NET image generation library and CLI tool 😅 The latest version of ElBruno.Text2Image now supports: MAI-Image-2.5 MAI-Image-2.5-Flash This means you can generate images using the new MAI models from a .NET app or directly from the terminal with the…

elbruno.com

VS Code 1.122 Makes BYOK Easier

One of the most interesting announcements in the recent VS Code 1.122 release is that Bring Your Own Key (BYOK) models can now be used without signing in to GitHub. VS Code now supports BYOK scenarios, including chat, tools, and MCP integrations, without requiring GitHub authentication, making enterprise, offline, and air-gapped workflows much easier to support. I originally came across this update thanks to a tweet from Pierce Boggan:

elbruno.com

Building Cross-Framework Agents with MAF, A2A, NVIDIA NeMo, and Aspire

Hi! What happens when a Python-based AI agent and a .NET-based AI agent need to work together? That is the idea behind MAF-A2A-NVIDIA-NemoAgents ( a reference app that shows how to combine NVIDIA NeMo Agent Toolkit, Microsoft Agent Framework, Agent-to-Agent communication, and Aspire into one multi-agent workflow. The repo describes itself as a production-ready sample that demonstrates NVIDIA NeMo Agent Toolkit + Microsoft Agent Framework with A2A communication, orchestrated with Aspire.

elbruno.com

GitHub Copilot CLI + SQUAD + GPT-5.5 BYOK: Better Engineering, Same Hard Truth

TL;DR This was the final ElBruno.NetAgent experiment: GitHub Copilot CLI + SQUAD using Azure OpenAI GPT-5.5 BYOK against the same app-building challenge I previously tried with CPU-only local models, GPU local models, and GPT-5-mini. The good news: GPT-5.5 was clearly better at staying inside phase boundaries, following safety rules, reducing broad stabilization loops, and working with strict quality gates. Once I switched to economy-mode prompts, the flow became much more disciplined: usually one implementation agent, one reviewer, short loops, and no wild repo-wide rewrites.

elbruno.com

GitHub Copilot CLI + GPT-5-mini BYOK: The Code Was Cheap, the Quality Gates Were Expensive

TL;DR This is part 3 of my GitHub Copilot CLI + BYOK experiment series. After testing local models on CPU and GPU, I moved the same experiment to Azure OpenAI using GPT-5-mini through BYOK. Same repo, same goal, same safety constraints — but this time with a cloud model that made SQUAD practical again. And that was the first big win.

elbruno.com

From Pet Projects to +20 Open Source NuGet Packages, Thanks to GitHub Copilot 🚀

Hi! Some of these started as small pet projects. IE: a quick helper for a demo, a tiny tool for a conference, a library to avoid repeating the same code again and again, or one of those “I’ll just build this in one evening” ideas that somehow becomes a real thing. And now, thanks to GitHub Copilot, many of these experiments are becoming open source, free NuGet packages that I hope are useful to everyone.

elbruno.com

Running GitHub Copilot CLI Offline with Local Models: GPU Edition

TL;DR After my first CPU-only experiment with GitHub Copilot CLI and local models, I wanted to try the same idea again, but this time with a GPU-powered setup. The first experiment proved that running GitHub Copilot CLI offline with local models was technically possible. This second experiment showed something more interesting: With the right model, GPU acceleration, small bounded phases, and strict human checkpoints, local agentic coding can become practical enough to move a real .NET project forward.

elbruno.com

Running GitHub Copilot CLI Offline with Local Models: A CPU-Only Reality Check

TL;DR I tested GitHub Copilot CLI running offline with local models on a CPU-only Microsoft Dev Box. The short version: Ollama worked for basic offline prompts, but struggled with long-context agentic workflows and tool execution on CPU-only hardware. LM Studio worked better as the local OpenAI-compatible provider. google/gemma-4-e2b successfully executed Copilot CLI PowerShell tools. 32K and 64K context were the practical sweet spot for guided development.

elbruno.com

OllamaMonitor — Monitor Your Local Ollama Runtime from the Windows Tray

Hi! If you're running Ollama locally on Windows—whether you're tinkering with LLMs, building local AI demos, or just curious about the overhead of large models—you've probably wondered: Is it still running? How much CPU is it chewing? Did that model load? Welcome to ElBruno.OllamaMonitor. It's a no-frills system tray app that sits in your Windows notification area and tells you, at a glance, exactly what your local Ollama instance is doing.

elbruno.com

AspireMonitor: Stop bouncing between your Aspire dashboard and your code.

Hi! dotnet tool install --global ElBruno.AspireMonitor aspiremon What it is AspireMonitor is a Windows tray app that puts your Aspire AppHost status one click away. No browser tabs. No switching context. Click the tray icon, see what's running, Start/Stop your app, or pin the resources you actually care about in a compact mini window. Why it exists If you use Aspire, you know the dashboard is useful—but you don't want a browser tab open all day.

elbruno.com

🕛 ClockTray v1.0.0: Meet the CLI-Enabled Clock Tool for Windows

Hi! usually hide my taskbar clock while recording videos, and after doing that dance one too many times, I had one goal: save a few clicks. Then yesterday, during a GitHub Copilot CLI session (watch it here), I decided to pick up the ClockTray app and turn it into a CLI tool. And... here we are. 🚀

elbruno.com

🚀 Big Update: GPT-Image Models + AI Agent Skills

Hi! Two weeks ago, I shipped t2i — a terminal-first CLI for text-to-image generation. Today I'm excited to announce two major additions that make t2i even more powerful: GPT-Image-1.5 and GPT-Image-2 support — Microsoft's DALL-E 3 and next-gen models via Azure OpenAI AI agent skill integration — Teach GitHub Copilot and Claude Code to use t2i automatically TL;DR New models:

elbruno.com

🚀 Meet t2i — The ElBruno.Text2Image CLI

Hi! I just shipped t2i, a terminal-first CLI tool for ElBruno.Text2Image. Generate images from your shell in two commands — no UI, no browser, just a simple cli interface to image generation from the cloud. This is the Lite edition (cloud-only, ~2.4 MB on NuGet) — perfect for CI/CD pipelines, deployment scripts, batch jobs, and developers who live in the terminal.

elbruno.com

🗺️ AOT-Friendly DTO Mapping in .NET

Hi! So, I've been away from any scenario that involves and needs data mapping, until I get to OpenClawNet. So I got to the point that I need to map my entities to DTOs? I read this a lot >> runtime reflection doesn't play nice with AOT and trimming. 😅 So I SQUAD myselft and built: 👉 ElBruno.AotMapper A Roslyn source-generator library that creates all your mapping code…

elbruno.com

🖼️ MAI-Image-2 Just Dropped — And .NET Support Is Already Here

Hi! When Microsoft announced MAI-Image-2, I immediately thought: "I need to add this to ElBruno.Text2Image. Today." So I did. 😄 MAI-Image-2 is Microsoft's new image generation model on Microsoft Foundry — high-quality generation, a synchronous API (no polling!), a 32K character prompt limit, and flexible dimensions. And it's already supported in ElBruno.Text2Image with the same clean interface you already know.

elbruno.com

🚀 Bing Open-Sources New Embedding Models — Now Available in C# with LocalEmbeddings.Harrier

The Microsoft Bing Search team just dropped something big: 👉 They’ve open-sourced a new set of high-quality embedding models, designed to be competitive with state-of-the-art approaches — and ready to run in modern AI workflows. And here’s the fun part 👇 You can already use these models from C#/.NET. 🤖 From Announcement to .NET in Minutes I integrated these new models into a C# library:

elbruno.com

I Built a .NET 10 Knowledge Graph Builder (Inspired by Karpathy)

Hi! Earlier this year, Andrej Karpathy tweeted about using LLMs as "knowledge compilers" — a mind-bending idea: instead of asking an LLM questions, feed it raw data (papers, code, images) and let it automatically build a structured, navigable knowledge base. No RAG. No vector databases. Just pure understanding compiled into a graph. Then I saw @socialwithaayan showcase graphify — a Python tool that does exactly this for codebases.

elbruno.com

📝 Convert Anything to Markdown in .NET — Meet ElBruno.MarkItDotNet

Hi! You know that feeling when you're building an AI pipeline or a RAG workflow and you realize: "Wait… I need to turn all these PDFs, Word docs, HTML pages, and random files into something my LLM can actually eat"? 😅 Yeah, me too. That's exactly why I built: 👉 ElBruno.MarkItDotNet A .NET library that converts files to clean Markdown. Think of it as the 

elbruno.com

🌟 Gemma 4 Is Here — And My C# Library Is (Almost) Ready

Hi! So Google just dropped Gemma 4 — their most capable open model family yet — and I couldn't resist. I spent a good chunk of time digging into the architecture, trying to convert models, hitting walls, finding workarounds, and hitting more walls. Here's where things stand with ElBruno.LocalLLMs. Spoiler: the library is ready for Gemma 4. The ONNX runtime...

elbruno.com

🚀 Build QR Codes in .NET FAST with ElBruno.QRCodeGenerator

Hi! I needed a quick way to generate QR codes in .NET—no heavy dependencies, no complex setup, just something that works and that’s exactly why I built: 👉 ElBruno.QRCodeGenerator An open-source, lightweight library to generate QR codes in multiple formats: 🖥️ ASCII (perfect for CLI tools) 🖼️ Images (PNG/SVG) 🔗 Payloads (WiFi, URL, email, vCard) 🎬 Watch the video…

elbruno.com

Stop Wasting Tokens: Smart Tool Routing for LLMs with MCPToolRouter

Hi! Today I want to share something that's been hearing a couple of times: You know when you're building an AI agent or working with LLMs, and you have dozens (or hundreds) of tools available? What do you do? Send ALL of them to the LLM every single time, right? Yeah, me too. And it's expensive. I had as a pet project for a while, so I decided to finish it, and start to give a real try.

elbruno.com