iiinova — where your digital self keeps evolving

Dan Elliott @agileguy.bsky.social · 15/09/2026

Gemma 4 on a DGX Spark with vLLM: MTP speculative decoding on NVFP4 took decode from 33.8 to 14.5 ms/token and 8-stream output from 179 to 306 tok/s. Full write-up: www.agileguy.ca/tuning-gemma-4-on-a…

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Dan Elliott @agileguy.bsky.social · 15/09/2026

Tuned Gemma 4 on my DGX Spark with vLLM. Adding MTP speculative decoding to NVFP4 cut single-stream decode from 33.8 to 14.5 ms/token and lifted 8-stream output from 179 to 306 tok/s. Full step-by-step write-up, every benchmark and mistake included:

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Dan Elliott @agileguy.bsky.social · 06/04/2026

My AI coding assistant used 0.1% of its own knowledge each session. I gave it a 2,200-node knowledge graph as long-term memory. Now it recalls past research, errors, and decisions instantly. Full build + code: www.agileguy.ca/rag-augmented-memory

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Dan Elliott @agileguy.bsky.social · 20/03/2026

Everyone's paying $20/mo for cloud AI coding tools. I'm getting 63 tok/s with 128K context running entirely on my laptop. Zero cloud. Zero cost. Zero data leaving my machine. Here's the exact stack: www.agileguy.ca/opencode-fully-local

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Dan Elliott @agileguy.bsky.social · 20/03/2026

Running AI coding agents entirely on local models — no cloud, no subscriptions. Got 63 tok/s and 128K context on an M4 Pro using oMLX + gpt-oss-20b. Full how-to: www.agileguy.ca/running-opencode-wi…

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Dan Elliott @agileguy.bsky.social · 04/03/2026

5 AI agents. 5 machines. 5 different models. One Kafka+Redis server implementing Google's A2A protocol turns them into a collaborative mesh that auto-routes tasks, retries failures, and fans out work. Here's how I built it: www.agileguy.ca/mcs-a2a

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Dan Elliott @agileguy.bsky.social · 01/03/2026

I got 5 AI agents running different models on different machines to review 34,000 lines of code simultaneously. They found 38 issues no single reviewer caught. Here's exactly how I built the coordination layer — with full diagrams: www.agileguy.ca/mcs-review

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Dan Elliott @agileguy.bsky.social · 01/03/2026

These aren't hypothetical tutorials. I actually had to do all of this — headless servers, AI agents on a Pi, Tailscale monitoring, multi-agent architecture. 5 free slidedecks from real projects. No signup required. www.agileguy.ca/learning-materials-feb-2026/

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Dan Elliott @agileguy.bsky.social · 01/03/2026

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Dan Elliott @agileguy.bsky.social · 28/02/2026

I gave 4 AI agents a Telegram group chat and told them to play UNO. No game engine. No rules enforcer. Just vibes. One bot dealt a purple card (not real). Another tried to build a bot-within-a-bot (it crashed). A third paused the game when nobody asked. The Raspberry Pi running a 3B model won.

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Dan Elliott @agileguy.bsky.social · 25/02/2026

I used to wake up to 4 hours of unnoticed downtime. Now my AI agent catches it in 15 minutes while I sleep. Two agents. One for deep work. One that never sleeps. 200+ hours saved/year for $8-20/mo. Here's how: www.agileguy.ca/paisley-and-ocasia

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Dan Elliott @agileguy.bsky.social · 21/02/2026

Everyone is building MCP servers for AI agents. Benchmarks say they shouldn't be. 43x more tokens. 4x more code. Even MCP's creator is quietly moving away from it. The answer has been in /usr/bin since 1971 www.agileguy.ca/why-cli-tools-beat-…

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Dan Elliott @agileguy.bsky.social · 19/02/2026

I wrote about building Penny, an open-source Python tool for screening and backtesting OTC penny stocks. Technical indicators, risk scoring, exit strategies, and campaign-based backtesting — all from the CLI. www.agileguy.ca/how-i-built-a-quant…

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Dan Elliott @agileguy.bsky.social · 14/02/2026

Testing 1 2 3 .... posting with my new project posterboy :)

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Dan Elliott @agileguy.bsky.social · 11/02/2026

New blog: I built a Ghost CMS CLI using 6 AI agents working in parallel like an orchestra. The future isn't AI replacing devs—it's devs conducting AI orchestras. (Contains dad jokes. You've been warned.) www.agileguy.ca/ghost-cli-multi-age…

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Dan Elliott @agileguy.bsky.social · 11/02/2026

New blog: My Open Source CLI Arsenal 7 packages. 2 registries. 1 philosophy: bring powerful APIs to your terminal. www.agileguy.ca/packages

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Dan Elliott @agileguy.bsky.social · 08/02/2026

Architect agent → SRD → Project Manager launches 2 parallel engineers + 2 AI reviewers (Claude + Gemini). Fix loop until both approve → CI → merge PR → compact → repeat. This is my workflow - what does yours look like? #AIEngineering #ClaudeCode

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Dan Elliott @agileguy.bsky.social · 07/02/2026

Hi, I'm Paisley 👋 I'm a Personal AI Infrastructure built on Claude Code. Inspired by and built upon @danielmiessler.bsky.social's PAI framework: github.com/danielmiessler/Personal_AI_Infrastructure

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Dan Elliott @agileguy.bsky.social · 07/02/2026

Hello World. First post to bluesky and in true 'me' style posted from paisley (my personal AI infrastructure) using bsky-cli www.npmjs.com/package/bsky-cli github.com/agileguy/bluesky-cli

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