Darren Schack

Anthropic's latest Claude AI model is taking human-AI interaction to a whole new level! 🖥️🤖 The new Claude 3.5 Sonnet can now use computers just like a human would - by looking at the screen, moving the cursor, clicking buttons, and typing text. This is a major leap forward in AI capabilities. Key features: Operates based on screenshots, emulating human computer use Can perform complex multi-step tasks across different applications Self-corrects and retries when encountering obstacles2 Accessible via API for developers to build with Why it's game-changing: This opens up incredible possibilities for AI assistance in data entry, form filling, software testing, and automating repetitive computer tasks13. Imagine having an AI assistant that can seamlessly work alongside you, handling tedious computer work while you focus on higher-level tasks. While still in beta, this technology demonstrates how AI is rapidly advancing toward more human-like interaction with digital interfaces. As it develops further, it could revolutionize how we work with computers and boost productivity across industries. The future of human-AI collaboration just got a lot more exciting! What do you think about this new capability? #AIInnovation #FutureOfWork Here is a video about it: https://lnkd.in/gh8aNYEu

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First story on what we have been up to at Augment. Much more to come! https://lnkd.in/gC6gbADA

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There's still time to participate in our 2025 State of Open Source Report. For everyone I know working with OSS take a few minutes to tell us what your organization is using and why. Here's a link to the survey: https://lnkd.in/gS_h-xYh Thanks for participating and helping us put together a great report!

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While there are certainly individual variations in skill and experience when discussing modern software development the story is much more nuanced than pure individual effort.  * software development is a team sport -- individual performance is heavily impacted by the system in which they are asked to operate in.  * we pair skill and experience to this model of understanding performance by expecting people to be able to influence and adapt in direct proportion to their seniority, aka the more senior you are the more responsible you are for the outcomes of your work, the less senior you are the more your manager and management chain are responsible.  * humans want to succeed, we're social animals who derive purpose from demonstrating skill, and working collectively. All of which is to say there is no way you have over 1000 people underperforming at your company without senior leadership deeply implicated in.  If nearly 10% of your company is failing, versus just having the market move against you, you need to fire the CEO.

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A theory of #softwareengineering effectiveness as the triad of business outcomes, developer productivity, and developer experience. 1. "Effective software organisations focus their investments on the right outcomes." 2. "Effective software organisations make fast and consistent progress toward their goals." 3. "Effective software organisations give engineers the support and tools they need t o feel engaged." WDYT? #technology #operatingmodel #devex #devops #valueengineering #value #engineeringmetrics #cto #cio

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My team and I built an AI agent that helps us debug our production issues. And now we're sharing some code for you to build your own 👩‍💻 I’ve talked to quite a few engineering teams that want to launch an agent for engineering teams to investigate and fix production issues faster. Because there’s no great reference architecture, template, or guide, it took me months of trial and error to get to a point I’m happy with. Now, my colleague Eric Abruzzese has written down several pro tips and steps on how to build an AI agent so you can learn from (and avoid) our mistakes. So what took us months could take you a few hours to do (if not less). In our 3-part series, we cover: 1. How to set up an application in Chainlit 2. How to connect your application to an LLM (in this case, gpt-4o) 3. How to make your Agent faster and add real-time “typing” (similar to ChatGPT) 4. How to give your Agent a personality and specialization 5. How to give your Agent the ability to search a collection of files 6. How to integrate your Agent with external tools (in this case, PagerDuty) Check out part 1 of the guide on our site (link in comments), and keep an eye out for part 2 coming soon (if you want a sneak peek, drop a comment and I'll send you the private Notion page 🕵️).

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Hey folks! I'd like to more formally introduce and talk about a few of the projects we're working on towards improving large-scale bioinformatics analyses (one of which was developed during St. Jude's KIDS24 Biohackathon)! If you're not aware, my team started a project called St. Jude Rust Labs (https://lnkd.in/eXY_9dJ8) where we're rewriting a more foundation for bioinformatics analysis in Rust. This cuts across more than just workflow execution, but, recently, we've been primarily focused on improving the experience of working with the Workflow Definition Language (WDL) at scale. To that end, we've released a number of projects, including: - We've written a complete lexer/parser for WDL v1.2 language (https://lnkd.in/eGWHSM2g). Anyone can use this foundation to build tools for WDL. - We've written a VSCode plugin that includes a language server protocol (LSP) for linting and validation directly in your editor (https://lnkd.in/euApG9tF). - And, announcing today, we've started down the road of writing our own WDL execution engine spread across the Crankshaft (https://lnkd.in/et_RFkA3) and Sprocket (https://lnkd.in/eUTuPE68) projects. Crankshaft was prototyped during the St. Jude Biohackathon last week—it's a _headless_ workflow execution engine, meaning that, in theory, others could come along and write drivers for Crankshaft built on NextFlow, CWL, Snakemake, etc. As I said earlier, our team is really focused on WDL specifically, so we're going to continue building out a "head unit" for Crankshaft using WDL. That being said, I would love to see other community projects popping up and using the core machinery for other workflow languages. Thanks to all of the individuals who participated on our Biohackathon team (Kevin Benton, suchitra chavan, Braden Everson, Andrew Frantz, Michael Gattas, Peter Huene, and John McGuigan)!

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Clear and rich information on RAG variations. I think this will be useful to most practitioners who have gone beyond the intro and demo workflows, and now need to consider how to refine their flows.

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These are the boring, yet impactful aspects of API operations I am here for--low-tech, economy impacting, real-world stuff like the API deprecation notice from the Department of Labor.

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Hey everyone, I am an investor and advisor to Katanemo.... They are reinventing the infrastructure primitives for GenAI and launched Arch - https://lnkd.in/gCrbbkEV - an intelligent prompt gateway. Give the project a look on Github, and star the project if it resonates

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There's a reason why SaaS observability is replacing the ELK stack. Think how cloud replaced on-prem, there are so many hidden costs! ELK has been the go-to for years, but it's become a real challenge to maintain since it requires more resources, and comes with higher costs, and increased complexity. By simplifying operations, enhancing insights and scaling effortlessly, SaaS allows teams to focus on delivering value instead of maintaining infrastructure. #SaaS #Transformation #Efficiency

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I just realized: we should start saying "build memoization" rather than "build caching." We aren't really talking about least-recently-used or time-to-live algorithms, we're talking about "don't bother recompiling this piece if none of its inputs changed." (It has been puzzling me that some people are so deeply fearful of "build cache" as a concept, and honestly I think it's mostly because most build systems have non-hermetic state scattered all over the place. Maybe a slightly more precise term for the type of caching we're concerned with would clarify the semantics in question.)

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An interesting, cool feature for Snowflake Cortex was just released last week and is called LLM Playground. You are now able to play with some feature and functionality and clearly see and compare results of things like: ✅ temperature, ✅ top_p or ✅ max_tokens ✅ Cortex Guard It's an interesting no-code tool that gives you the power to try models and settings. https://lnkd.in/gpZTjRiQ #snowflake #infostrux #datasuperhero #snowflake_advocate

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Project update! My application tracking extension is now doing fuzzier matching and injecting new information into LinkedIn (and other sites) to keep me from doubling up on applications. Next up: local storage and bulk import/export operations...

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Hey folks! Garrett Milster and I have only posted about Sacramento Labs once, so we figured it's time for an update 😊 **What is Sacramento Labs?** We’re a small team focused on launching software products that solve real-world problems. Think of us as a startup lab—constantly testing ideas, learning from feedback, and building tools that matter, and having an impact while doing it. **How do we decide what to build?** We like to build products that: -         Solve real-world problems in mostly ignored industries -         Are small, highly maintainable, and scalable codebases -         Make the world a better place directly, or by donating a percentage of profits to a relevant charity in that space You can learn more about our philosophy at sacramentolabs.com **What you can expect from us** We’ll be posting product ideas that are in various stages of our pipeline: Early Concept, Customer Development, In Progress, Launched, Scaling. We’d love to hear your feedback! **Our latest concept: Self-Hosted Security** Here’s the problem: - Businesses often use third-party URL shorteners to share internal tools, resources, or campaigns, but these services introduce serious risks. Enterprise companies like Google, Microsoft, and Stripe have built their own internal URL shorteners for this reason – but most businesses don’t have the resources to do that. - Phishing attacks are rampant, and links from external services can be spoofed or abused. - Branding and security controls are limited, leaving sensitive information exposed. - You can’t track link activity—who’s clicking what, when, or why. - When employees leave, their shared links still work, leaving potential vulnerabilities. Our proposed solution: Self-Hosted Security. It’s a plug-and-play solution for businesses to host their own branded URL shorteners with: - SSO for secure access tied to your company’s directory. - Link expirations to ensure old links don’t stay active indefinitely. - Audit logs to track activity and improve visibility into link usage. 📢 We need your input! Would this solve a problem for you? What features would make this indispensable? Check out the landing page and share your thoughts: selfhostedsecurity.com Want to chat? Email me at [email protected] 😊 💡 And here’s something we’re passionate about: a percentage of profits from Self-Hosted Security will go to the Electronic Frontier Foundation (EFF). Your feedback not only helps us create better solutions, but also contributes to making a positive impact. Thanks for being part of the journey!

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Want a preview of what I'm going to be talking about in my keynote for RubyConf? You can catch a glimpse of it here!

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🌟 From Raw Data to Behavioral Predictions—Effortlessly What if AI deployment didn’t require months of preparation? With BaseModel.ai now on the Snowflake Marketplace, you can transform behavioral data into predictions in just a few clicks. ✅ Rapid Deployment: Build and deploy models in a week.  ✅ Scalable Flexibility: Create multiple models for diverse use cases.  ✅ Privacy Guaranteed: Data never leaves the secure Snowflake environment. Say goodbye to complexity and hello to actionable insights. AI for behavioral data has never been this simple. 👉 Try BaseModel.ai Today  #AI #MachineLearning #BehavioralData #BaseModel #Snowflake #Synerise 

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Large Language Models (#LLMs) are evolving rapidly, and the demand for running them at scale is skyrocketing. #Ollama is stepping up to meet this need with its official container image on Docker Hub, excelling in local #deployments. However, there’s a catch for containerized environments: downloading #models requires the ollama serve command to be running within the #container. This extra step complicates automated deployments via #CI #CD #pipelines, making seamless model access challenging. To take your #model to production, it needs to be #container-ready—a feature Ollama has yet to fully support. The gap in #AIOps for smooth deployments gets blurred with the inference services available as an easy way to take it to production. Goal is to overcome obstacles and deliver solutions 😉 so here is to get you started on having your (O)#llama #production ready in a private #deployment from your #local to #cloud all in #oneshot . Enjoy Medium: https://lnkd.in/g9jqBQ8d dev.to: https://lnkd.in/gi_gGwam #AI #LLM #Ollama #llama3 #phi3 #mistral #S6overlay #AIOps #CI #CD #oneshot #container #docker #podmanEnjoy

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Honeycomb's storage engine, Retriever, is the key differentiator behind so much of our product. I sometimes get questions from other engineering leaders about why we didn't use x or y off-the-shelf technology or product instead. There are a number of reasons I could share, but one of the most important ones is that it's usually hard to evolve someone else's offering (even if OSS) as the constraints of your business change over time. This post from Hazel Edmands is such a fantastic deep dive into our most recent round of doing just that. https://lnkd.in/g9mvvHWW

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