Michael McCormick

~40% of Frec’s customers are engineers working in tech, many of whom expect frequent and large capital gains. They also prefer to self-manage their money, which makes Frec an ideal platform. Meet Evan: an engineering leader who upgraded from investing in ETFs to direct indexing. Direct indexing appealed to Evan because it offers comparable returns to his ETFs while saving him money on advisory and ETF fees. “ETFs are true and tested, and giving folks a different way of investing in the market while saving more money is really appealing.” He’s used many other robo-advisors and other fintech tools, but “Frec seems to maximize tax loss harvesting opportunities better than any other product that I’ve used.” He also likes Frec's transparent fee structure.  “I feel like with a lot of other companies, that’s muddled in with the cost of investments,” he told us, “and you don’t really know how much you’re paying or how much you’re not saving as a result. I think Frec does a really good job of laying all of that out and giving you a true understanding of the cost of these investment products.” Read more about his Frec journey here ⬇

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My peers were in disbelief when I said I made an EVM Indexer and made it run for free on Vercel. Can't blame them. Vercel transforms your source to Severless Runtimes, with a limited response time, throttled resource utilization (https://lnkd.in/gNVw6DrN), and require external trigger for execution But, it's possible, if you pair Vercel with this amazing product - Inngest (https://www.inngest.com/) and Supabase. Use Inngest Crons to schedule your tiggers and Inggest Severless Queue to chunk the execution in sequence so that you can circumvent the resource & time limits. I got started with this Medium article, and tweaked to fit my needs. I beleive it'll be a good starting point if you're interested: https://lnkd.in/gnHDmYwJ #vercel #edge #nextjs #supabase #inngest #evm #solidity #thegraph #javascript #typescript

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AI is innovating a variety of industries across the US and Agriculture is no exception. 🐄 My new friend, Catie McVey, has created a new "Agtech" startup that uses patented 3D Modeling and Machine Learning algorithms to evaluate the health of cows by looking at specific characteristics such as hoof morphology and facial characteristics. Working with her to architect how to get source data from "The Stockyards" to "The Cloud" has been a lot of fun. I am constantly discovering new ways AI can make an impact in industries from legal, to healthcare and now agriculture! Read more about Catie's journey on RIoT - Internet of Things' blog #AI #software #agtech

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SOC 2 is not a perfect reflection of a company’s security posture. But, it’s still one of the most common ways companies assess vendors. We recently launched a tool that automatically analyses arbitrary SOC 2 reports within 30s and surfaces everything that security & GRC teams care to find. DM me if you want to give it a spin 🛩️ #soc2 #tprm

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Congrats to the Datadog engineering team for releasing the private beta of their on-call product today. We know first hand how difficult it is to build! I guess I need to update this blog post now? https://lnkd.in/edct4mgA

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Does the state of your metadata matter for AI preparedness? TL;DL: Yes. But I still encourage you to listen to this insightful podcast episode from the Traction Complete team interviewing our very own Michael Bogan and Rob Acker.

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Last week, we re-released the Vanta API for customers in REST. I'm excited about a lot of our ships, and I'm *really* into the move to REST. I say this as one of the folks who chose GraphQL initially 🙃 . Back in 2017-2018, GraphQL seemed like the future, and so we built on it. While it has some nice properties (e.g. lowering the stakes of changes), it never really took off, and most engineers are more comfortable with REST. Good intentions, wrong technology bet in retrospect. If you're shipping, you'll get some of your technology bets wrong, and all you can do is acknowledge reality ("our customers prefer to work in REST") and build. Huge kudos to Jan Castor and Mikaela Gilbert for leading the project at Vanta. By our count, at least 17 other engineers at Vanta contributed endpoints, architecture, and documentation to this release. (Never win alone!) Now, with our REST API, customers can: * Automate processes in Vanta to minimize clicks and human error. Examples include auto-uploading documents or policies, bulk assigning owners to resources, or bulk offloading employees. * Programmatically extract information from Vanta into external reports that aggregate data from multiple systems. For example, you can automatically export test status information from Vanta and Trust Center viewer data to a Business Intelligence tool to help power enterprise-wide compliance dashboards. * Build custom integrations so Vanta can run automated tests against systems the platform does not already integrate with, including on-premise or custom applications. * 🔜 Automatically initiate external workflows to improve your security posture through fast remediation of security gaps. For instance if a critical test in Vanta fails, an external workflow or script that monitors this test can automatically initiate remediation.

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I can hardly believe it, but there’re only 2 posts and 1 week left to join in on my 30 Days 100 Demos Challenge… I'm thrilled for you to learn about: 🧠 The intelligent approach to diverse hiring in C. Guz's demo of Join OCTO Labs 🚏 Sean Leenhouts’s sage-like guidance of prospects through his demos of Foundation 🪄 The wizardry behind DMA (Donna Michelle) Anderson’s demo of Korgi Here’re those details one. last. time. Scheduling link in the comments 👇 I want to learn from the best folks in the demo game: 100 demos in the month of June. Are you (or do you know) an AE, SE, builder, or founder who gives a great demo? I’d love to learn from you! In exchange for 30 minutes, you’ll get: + $25 gift card to your favorite coffee shop or donation to charity of your choice + Publicity for you and your app in a weekly blog post alongside other amazing startups to my followers on LinkedIn (all about how great you are, this isn’t a critique session) Thanks for your support! #gotomarket #sales #b2b #SaaS #demos #GTM #startups #founders

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Thanks Joanne Chen and Jaya G. from Foundation Capital for the nod! Great to be in the cohort of top notch AI companies. Observability data is untapped goldmine of information, but when the time comes (in the middle of incident), it still requires "expert" skills to find the needle in the haystack. We at Deductive AI are democratizing the expertise to everyone in the organization.

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🌟Happy new and (hopefully) spring month!🌷 I was fortunate to attend Postgres Day in windy Chicago this past weekend, and I had no idea what to expect but I think that made my brain more open to the content. For those who may or may not know, PostgreSQL - or Postgres, is a free, powerful, and open-source object-oriented database management system with a community actively involved in its development. Postgres is used by analysts, developers, database architects/administrators, and so on, and has incredible capabilities. As a junior analyst, I was intimidated by the experience and expert-level technical know-how in the room. But instead of shrinking into a corner, I decided to try and fill my knowledge gap. Here's a snippet of some interesting sessions I attended: 🤖 Postgres with OpenAI: Building & Monetizing Generative AI Plugins What do you get when you mix a database, JAVA, and an LLM? If your answer was "no idea", let's be friends. I don't consider myself much of an app or backend developer by any means, however, this interactive session by Denis Magda empowered me to feel like I could develop an app connected to a database, and integrate it into an LLM (GPT-4 for example), with the potential of turning it into a lucrative Gen-AI plugin. 🗺 Map of Amazing Postgres Extensions I definitely didn't know about If you thought Postgres was only good for SQL and databases, think again. While that is at its core, Postgres has numerous extensions that add to its functionality and provide user extendability. Claire Giordano wonderfully presented these extensions as a mind map split by category. As a visual learner, this helped a lot in understanding what the extensions do, if/when you'd need them. I also learned about Citus, an extension that scales Postgres by distributing data & queries. There's a separate conference for it called "POSETTE" and I'm eager to learn more. 👱🏻‍♀️ Trying to be Barbie in Ken's Mojo Dojo Casa House I knew immediately what this session was about, but that's also because I've seen the Barbie movie. So if you haven't, take this as a sign because Karen Jex and Stacey Haysler (bada** women by the way) use this movie to mirror and present important statistics related to trends of women in tech. It was disappointing, but not surprising, to see how many women enter (and leave) the tech industry, and how women, POC, and other diversities are treated while they are in tech. This session made me emotional and I'm super grateful to Karen and Stacey for creating a space to shed some tears and rant. As a whole, I'm very grateful for this experience, the connections, and the knowledge shared. Special mentions to Henrietta Dombrovskaya for organizing the event and having a warm and welcoming presence the whole time. Autumn Nash Thank you for posting about the event and the free ticket (clearly not all heroes wear capes)😊 Looking forward to attending more conferences, networking, and professional growth in 2024! #postgresql

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Every senior-level engineer needs an 'AI Gilfoyle' 🤖 Building software is even harder if you are a new-comer to a large codebase. There hundreds of questions you have to ask before getting familiar with the landscape. That's why we built Fume Slack app for Teams. Fume has context over all of your codebases and can answer the hardest of questions over Slack. You just have to ask a question and @tag Fume. It's that easy! It saves the time for your BEST engineers while making onboarding much faster 👟 Go to fumedev.com and try Fume today!

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Are you working with #Llama3 in #Healthcare? Today John Snow Labs open-sourced this fine-tuned model, which is now the #1 #OpenSource model on the #Medical #LLM leaderboard: https://lnkd.in/gtwXeACW #healthcareai #healthai #ai #generativeai #datascience #largelanguagemodels #research

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According to a new benchmark I created, GPT-4o is great at using the information in its context window compared to other LLMs. Needle in a needlestack creates a prompt with 100-1000s of limericks and then asks a question about one of the limericks at a specific location. Until GPT-4o, no LLM was very good at it. Check out 4o vs Turbo in the graph below. You can learn more about NIAN here: https://nian.llmonpy.ai/

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We're shipping a lot here at Schematic, take a look at what went live this month. https://lnkd.in/ejmxiyi2 Highlights:  💲 Stripe integration: Sync billing data from Stripe and map it to company profiles in Schematic 🔌 SDK update: Caching, event buffering, and offline support for Go, Python, and Node.js ✨ UX improvements: Feature usage sidebar and bulk entitlements adding 🪵 Audit log: View, search, and filter updates to a company's features access, troubleshoot issues, and track changes for compliance 👥 Team permissions: Invite teammates and specify what permissions they have within Schematic

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In less than 24hrs Open Source CEO is dropping it's newest piece: The Four Type Of Managers & How To Manage Them. What are the four manager archetypes. How to identify your managers. Why you need to treat them differently. And loads more. If you are interested in getting it straight in your inbox sign up at the link below. https://lnkd.in/ey9sMDhJ

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All CDPs inherently come with a "split-brain" problem. They say there are two hard problems in computer science - cache invalidation and naming things. I say there is a third - Keeping System A in sync with System B. Ironically, Customer Data Platforms need to keep their customer data in sync with twenty other systems. What's the alternative, you might ask? Build all SaaS applications directly on the unified customer data in your CDP or data warehouse? That's easier said than done. None of the leading advertising platforms, nor the majority of B2B SaaS solutions, will ever be built directly on top of your single source of truth. On the contrary, every data-intensive B2C SaaS should—and indeed must—be rebuilt directly on top of your unified customer layer. Troubleshooting data inconsistencies across such platforms with your CDP is an impossible task.

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Unapologetically Technical's newest episode is now live! In this episode of Unapologetically Technical, I interview Hubert Dulay the author of Streaming Data Mesh and Developer Advocate at StarTree. We talked about his early experience with web backends like CORBA and SOAP and how those prepared him for data work. He shares his advice for those with web development skills to transition into data and what it's like for a person leaving a company after a long tenure there. We discuss his time at Cloudera and Confluent and how the data industry has changed over time. We talk about his recent experience with Flink and StarTree. We go in-depth into streaming data mesh, covering what it is and how to create real-time data products. We discuss the ways teams can create joined or enriched data products across domains. We round out the discussion with some tips on how to get data mesh adoption. Watch the full episode here:

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It’s THIS article (the second one in the post below): https://lnkd.in/dEdPxy62

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