Edd Mann

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Edd Mann

Edd Mann

@edd_mann

developer, building things - 🎙️ https://t.co/1G7Rk4OeyX

Kent, UK Katılım Mayıs 2011
341 Takip Edilen491 Takipçiler
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Edd Mann
Edd Mann@edd_mann·
i built a game boy emulator in #php over the weekend - mostly from my phone, with the help of #claude’s remote agents. 🤯 here’s how it went 👇
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Edd Mann
Edd Mann@edd_mann·
inspired by the pokemon journey @Dimillian has been on with PokeSwift, it got me excited to explore an idea i had a while back. introducing PokeHeath, a mashup of Pokémon Red and Apple HealthKit. What you did yesterday affects how the game plays today. github.com/eddmann/pokehe…
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TJ
TJ@heytjmiller·
Iris is now available for early access! It's a self-hosted AI assistant that actually remembers you — persistent semantic memory, proactive messages, shell commands, task delegation, and agent skills. Built on Laravel + Prism PHP. 👇🏻
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Edd Mann
Edd Mann@edd_mann·
Ep. 19: From Linguistics to Large Language Models with Chris Brousseau i've been wanting to do an episode that really digs into what #LLMs actually are under the hood, and Chris's journey from linguistics into ML made this the perfect conversation to do it 👇 🎧 compiledconversations.com/19/ we start with how a graduate seminar on python and machine translation in 2017 pulled chris from linguistics and translation into NLP. studying how humans create meaning in language for years turns out to be the perfect background for understanding where LLMs shine and where they completely fall apart. from there we go deep on the fundamentals - transformers, tokenization, embeddings, context windows, the training pipeline from self-supervised learning through RLHF to fine-tuning. he's deployed billion-parameter models at mastercard and jp morgan chase, and co-authored LLMs in Production (which i'm a huge fan of). we dig into the gap between demos and production systems, and the operational challenges that make deploying at scale uniquely hard. we wrap up exploring the shift from prompt engineering to context engineering, agents and code-based tool calling, and why bridging linguistics and computer science could unlock the next wave of progress. full episode: 🎧 compiledconversations.com/19/
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Matthieu Napoli
Matthieu Napoli@matthieunapoli·
@edd_mann ohhhh super interesting! Yes going through GitHub is slower than I'd like, and reviewing in PhpStorm is less practical to talk with the AI agent. I discussed with @pronskiy about this, this could be a nice PhpStorm plugin too 🤔
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Matthieu Napoli
Matthieu Napoli@matthieunapoli·
My current AI coding workflow: 1. plan with Claude Code -> create GitHub issue 2. new session: `/work #122` (+ I review the code locally) 3. `/pr` creates a PR 4. Claude reviews in GitHub Action and adds inline comments 5. I review the diff + comments (mark some as resolved) 6. `/address-pr-review` -> CC will review each open comment and either fix or post a reply saying why it's stupid 7. goto 4 until ready to merge Most of these are Claude slash-commands/skills. Except 1: I built a dedicated app for designing and planning with Claude. I should find time to post a whole blog post about this.
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Andrew Cairns
Andrew Cairns@andrewcairns·
Fantastic discussion between @ShawnMcCool and @edd_mann on Event Sourcing and related topics such as Domain-Driven Design, CQRS, Event-Driven Architecture, etc. Great to listen to a conversation that goes deep and discusses the complex stuff, not just the surface entry level.
Edd Mann@edd_mann

really excited to finally get this episode published 🎉 Ep. 17: Event Sourcing with Shawn McCool @ShawnMcCool shares how event sourcing fundamentally changed the way he thinks about modeling software systems. if you've ever felt stuck in the "way we've always done it" mindset, this one's for you 👇 🎧 compiledconversations.com/17/ we trace shawn's journey from discovering domain events while working on laravel.io back in 2012, through creating Event Sourcery, to now building payment processing systems. what started as curiosity about DDD turned into a completely different approach to building software. the core insight: events aren't just for messaging or streaming - they become the actual source of your model state. we dig into how this differs from event-driven architectures and why capturing intent matters more than capturing data changes. shawn shares a practical pattern that eliminates entire classes of versioning and data retention headaches: design your aggregates to exhaust quickly. at his current company, event streams naturally terminate within 30 minutes. no long-lived aggregates means no painful migrations, no GDPR nightmares. we also explore the relationship between event sourcing and CQRS, testing strategies, and why DDD isn't really a methodology - it's a pursuit of understanding your domain. full episode: 🎧 compiledconversations.com/17/

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Edd Mann
Edd Mann@edd_mann·
Ep. 18: Architecture Modernization with Nick Tune i've been a fan of Nick's books, writing and talks for many years, so it was great to be able to have a conversation about all things architecture modernisation with him 👇 🎧 compiledconversations.com/18/ we start by reframing legacy systems - they're not failures, they're successful products being asked to solve problems they weren't designed for. Nick introduces his four-pillar framework covering business strategy, design discovery, architecture, and execution. one key concept is "Death Valley" - the dangerous hybrid state during migration where you're running old and new systems in parallel, keeping data stores in sync. it's where most modernisation efforts fail if you don't plan for it. we dig into socio-technical alignment - how domain models drift from business language over time, and Conway's Law in action where team structure shapes (and misshapes) your architecture. Nick explains how Architecture Modernization Enabling Teams (AMET) help bridge these gaps. we end with how AI tools like Claude Code are transforming this work - from code analysis and refactoring to generating living documentation. Nick shares his approach to guardrails: linting, test coverage, complexity limits for AI agents, and running multi-agent workflows in parallel. full episode: 🎧 compiledconversations.com/18/
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Shawn McCool
Shawn McCool@ShawnMcCool·
I had the please to speak with @edd_mann about event sourcing lessons learned from 10 years of production and a bunch of related patterns and concerns that have surrounded this architectural choice. I'm glad that we were able to cover a lot of non-introductory material here.
Edd Mann@edd_mann

really excited to finally get this episode published 🎉 Ep. 17: Event Sourcing with Shawn McCool @ShawnMcCool shares how event sourcing fundamentally changed the way he thinks about modeling software systems. if you've ever felt stuck in the "way we've always done it" mindset, this one's for you 👇 🎧 compiledconversations.com/17/ we trace shawn's journey from discovering domain events while working on laravel.io back in 2012, through creating Event Sourcery, to now building payment processing systems. what started as curiosity about DDD turned into a completely different approach to building software. the core insight: events aren't just for messaging or streaming - they become the actual source of your model state. we dig into how this differs from event-driven architectures and why capturing intent matters more than capturing data changes. shawn shares a practical pattern that eliminates entire classes of versioning and data retention headaches: design your aggregates to exhaust quickly. at his current company, event streams naturally terminate within 30 minutes. no long-lived aggregates means no painful migrations, no GDPR nightmares. we also explore the relationship between event sourcing and CQRS, testing strategies, and why DDD isn't really a methodology - it's a pursuit of understanding your domain. full episode: 🎧 compiledconversations.com/17/

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Edd Mann
Edd Mann@edd_mann·
@ShawnMcCool thanks for taking the time to come on the show again, was a great chat - where as you said we got to talk about a lot of different areas 🙏😊
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Edd Mann
Edd Mann@edd_mann·
@michaeldyrynda really enjoyed the video! we are in such an interesting time to be able to pick up and explore new tech/langs and solve more problems.
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Michael Dyrynda
Michael Dyrynda@michaeldyrynda·
You can check out Arbor on GitHub! Was a fun little exploration into steering tools with a language I've not written anything in, to see how far I could get. github.com/michaeldyrynda…
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Michael Dyrynda
Michael Dyrynda@michaeldyrynda·
I used AI to build a (git) worktree management tool in Go! Let me show you through what it does and how it might prove useful in your agentic workflows (at least until the tools build it all in for you!) This is more an exploration of building with AI than the tool itself.
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Ashley Hindle
Ashley Hindle@ashleyhindle·
Codex and I have been building a TUI library called Pat for PHP 🫶 Got the core elements, z-index stacking, diffing, performance all in place. Now need more elements, nicer designs, better DX 👌 One day!
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Edd Mann
Edd Mann@edd_mann·
i've been impressed with what claude can design on the frontend using the frontend design skill. single file landing pages ftw! this is the landing page i've put together for buns. credit cGPT for the logo. eddmann.com/buns/
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Thorsten Ball
Thorsten Ball@thorstenball·
"Is GitHub dead?" Recorded a spontaneous little video with thoughts on the future of developer tooling
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Edd Mann
Edd Mann@edd_mann·
after adding sandboxing to phpx yesterday, gave buns the same treatment this morning - buns is an inline deps runner for ts/js, and now scripts can run in fully isolated environments with filesystem, network, and resource limits. uses native os primitives (sandbox-exec on macos, bubblewrap/nsjail on linux) with a proxy layer for selective network access. inspired by @anthropic's sandbox-runtime 🔒 eddmann.com/buns/ github.com/eddmann/buns
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Edd Mann
Edd Mann@edd_mann·
just spent the last half hour improving my release changelog workflow to follow keepachangelog.com - set up a revised github workflow + a claude skill to handle it. the fun part: made the changes in one project, then got #claude to understand the pattern and apply it (with subtle contextual tweaks) to 7 other projects. one-shot learning, batch automation 🤯
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