Scott Addie

Join us for an interactive discussion on building real-world, non trivial applications with functional programming. 🎤 Speaker: Cameron Presley, Consultant & Microsoft MVP   🚀 Topic: Functional Domain Modeling   👨‍💻 Key Learnings: Practical challenges & solutions in Functional Programming, modeled through a Blackjack game. #FunctionalProgramming #TechTalk #SoftwareDevelopment #Innovation #DetroitTechWatch #DetroitTech

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The most valuable 5 minutes you can spend today is watching this demo of autonomous agents in Copilot Studio in Microsoft 365 Copilot. Take the remaining 90 seconds to think about your own work :) https://lnkd.in/gMSJPSux

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I have been telling everyone all week about this new video. In this video, I go over one of my favorite new features in Copilot Studio since Build 2024, Inputs for Topics. Most people don't know about this feature and the power it brings to Copilot Studio. So, make sure to watch this one! #copilot #copilotstudio #authoring #topics #power #conversationalai #gpt https://lnkd.in/emjgrjbW

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4 Things You Should Put in Your Daily Dev Log To harvest meaningful patterns from your dev log, you’ll need to capture the same things daily. I’ve been engineering software for 25 years, and I’ll share what I’ve routinely kept in mine. Your context is different, so your list will be also. Just make sure you capture the same things daily. Use this list as a skeleton to start from. It’s easier when you aren’t starting from a blank page! Pull Requests I keep track of every PR I submit, approve, or merge. Almost any work product I deliver or review flows through Git. My lists of PRs serve as a personal task-level kanban board of work in progress that I am connected to. These help me easily reconstruct a story of what I’ve done throughout the week. Personal Interactions I make note of every personal interaction I have, scheduled or otherwise. In addition to these notes, I keep a page for each person, and I link to that page from my daily notes. As I note patterns of interaction with a person, I’ll describe those patterns on their page. Over time I build a library of every person I’ve collaborated with and what we worked on together. Project Actions I keep a running narrative of the things I’m working on. I keep a section for each thing I’m working on. These might be at the product or story level - it just depends. Each time I hit a stopping point or interruption, I make a note of what I’ve been doing and what I plan to do next. Guess what I use to inform my daily standup updates? Perplexing Puzzles I make a note of everything that surprises me. These could be strange program behaviors, blockers, production issues - anything unexpected. As I review these periodically, I ask myself how I can use what I’ve learned to improve my mental models. Hopefully this list helps you get past the starting line. Do this faithfully for several months and see where it takes you!

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Software estimation and decomposition is more art than science. There are useful constructs, like Cyclomatic Complexity, lines-of-code estimations, etc; however, nothing beats experience. It's not unlike a potter knowing instinctively how long a piece will take, and understanding that 80% of their time will be on 20% of the details of the piece. AI can do much of the work; but there is artistry in the details. There's always a place for craftsmanship.

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Data conversion is a critical aspect when transitioning from the Federally Facilitated Marketplace (FFM) to a State-Based Marketplace (SBM) or when changing vendors. This process can often be challenging, but it's essential to ensure a seamless transition and maintain data integrity. Check out this insightful article by CITIZ3N that delves into the complexities and best practices of data conversion during these transitions. Whether you're in the midst of a switch or planning one, these insights are invaluable for a smooth and efficient process. At CITIZ3N, we understand the importance of making data conversion easier for our clients. Our in-house tools, built on the latest technologies, and our hands-on approach ensure that your transition is as seamless as possible. If you're looking for expert guidance and robust solutions, we're here to help! #DataConversion #SBM #FFM #TechSolutions #SaaS #GovTech

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Digging into JHipster 8.3.0 and found a bug in their recent adoption of the Spring Boot Parent (SBP). The tracking to SBP reduces maintenance friction in the JHipster Dependencies BOM and tracks closer to Spring’s own security patches. Yet, the SBP brings in Spring’s own configuration of Maven’s Resources Plugin that JHipster was largely managing for legacy reasons. The merged effective POM resulted in JHipster’s resources plugin filters failing to execute as expected when activing Spring Profiles via Maven’s own -P/--activate-profiles switch. Compounding the problem, and hiding the issue, was using JHipster’s service discovery support with spring-cloud-starter-bootstrap. The bootstrap configuration was ignored by SBP’s filtering and JHipster “worked.” What I love about OSS is being able to identify the problem and submit the fix and at the same time pull JHipster closer to Spring Boot. The PR was approved and merged this morning! 🎉 #jhipster #opensource #springboot

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The PlainID Policy Simulator is one of the best ways to test PlainID AuthZ policies and continues to be a one of my favorite webinars to have developed. #plainid #nostalgia

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3rd time is a charm! This is the 3rd significant release (multi-month effort) we have had in the past 3 days in Azure Architecture Center - we added image handling guidance to our Designing and developing a RAG solution guide (https://lnkd.in/gBrp6g3p). Our first release discussed the complex considerations you must take into account when designing and evaluating a RAG solution taking a scientific approach. We covered the following phases: - Preparation phase - where you determine your solution domain, perform document analysis, gather representative test documents, and gather test queries - Chunking phase - where you learn about the economics of chunking, understand the different approaches to chunking, and learn how the document structure helps you determine what approach to take - Chunk enrichment phase - where you learn how to clean chunks to support closeness matches and augment chunks with metadata that can be used in search - Embedding phase - where you learn about the importance of the embedding model, you learn guidance on how to choose an embedding model, and learn how to evaluate the models - Information retrieval phase - where you create a search index, understand the various search options like vector, full text, hybrid, and manual multiple and how to evaluate those searches. - Large language model end-to-end evaluation phase - where you learn how to evaluate the system from end-to-end This release enhances this guidance by overlaying guidance on how to handle images across those phases. We cover, among other things: - How to determine what images are valuable and what to ignore - How to determine how you are going to process the images such as using a language model to generate a text description and chunk that text, pass surrounding text along with the image to the language model or not, or pass the image itself to a multi-modal model - Cost management strategies when working with language models for images such as using a classifier to determine if there is value to process the image and caching All of this guidance is sourced from real-world customer engagements by our finest data scientists and engineers. As part of those engagements, our teams have built two open-sourced RAG solutions in use by many of our customers: - The RAG Experiment Accelerator (https://lnkd.in/gYMi7rNS) - RAG with Vision Application Framework (https://lnkd.in/gqEcygDk). Shout out to the amazing engineers and data scientists that helped add vision guidance: - Mahdi Setayesh - Ritesh M. - Soubhi Hadri - Paul Butler Hats off to Chad Kittel ([email protected]) for his guidance and leadership with this effort! CC: Chris Duarte, Martin Ekuan, Luke Nyswonger, Steve Sweetman, Dennis E., Craig Guyer, Nitin Mehrotra, Dom Allen, Ben Brauer, Jose Daniel Contreras, Dan Massey, Lara Rubbelke

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Microsoft #Ignite is just around the corner (Nov 19-22) and you do NOT want to miss it. Whether you’re into #AI, #cloud, or the future of work, we’ve got you covered.   It’s more than just a conference – it’s the tech world’s biggest #AI treasure hunt for insights on modernizing apps, safeguarding #data, and boosting productivity. Dive in and learn: https://lnkd.in/g37JpnED   #MSFTAdvocate #MSIgnite

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Is this a design problem or an implementation problem? My AI is literally laughing at me...I hooked this joker to my home automation system. To those who can't see it - In the last interaction he says "Back to this bird valve". This means he has access to the context the whole time, he's just choosing to ignore it for some reason? #AI #ML #CrushItForMike

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Great post from Dale Lane: Demonstrating some of the first tools to support AsyncAPI v3, and how they can help accelerate your event-driven projects. AsyncAPI version 3 was released in December 2023. In this post, I want to highlight some of the adoption of this new version of the specification, by sharing some of the things that you can do with AsyncAPI v3 documents. I'll demonstrate this with: https://lnkd.in/d6jps8kK

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Have a look at the article I wrote on React state management in Cevo's blog space. https://lnkd.in/gvw_gBNn

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We never really recommended Xamarin, but it had a good run. There are certainly several options on what to switch to, check out this article by my friend Ryan that goes through some of them, with the pros and cons of each.

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Today I am releasing a new video that shows how to leverage the Copilot Studio Kit to automate testing of your custom copilot. This is a massively powerful tool provided by our amazing PowerCAT Team at Microsoft. #power #powercat #test #copilot #copilotstudio #dataverse https://lnkd.in/eDpt4Qk7

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Get a behind-the-scenes look at why Salesforce designed Einstein Copilot with primitive components. Taking a modular design approach lets the AI assistant respond with varying formats. Get the full story.

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