Oskar Bruening

The Stoke Space team in Seattle has built a rocket company faster than many people can build software. Morgan Beller breaks down how this is helping them capture a huge opportunity: https://lnkd.in/gc5jv2-c 

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There is a lot of grandiose thinking around AI right now with plenty of VC essays and manifestos but we thought we'd get practical at Balderton 🙂 If you're at a company that wants to use AI, understanding what rules and regulations might affect you is incredibly complicated to understand. A shifting political landscape and constantly evolving understanding of the technology has given rise to a spiders-web of rules and frameworks. And the problem is even if you solve it today, you then have to stay on top of it every quarter as things keep changing. 🤯 Balderton's new Founder's Guide to AI Policy and Regulation solves this problem. Simply key in what you're doing and where you're doing it and the product summarises all of the key things you need to watch out for so you can quickly check you are in compliance. Need to dig deeper? The site also gives you links to underlying sources and expertise to go further! 🚀

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The newest issue of The Pragmatic Engineer found a surprise uptick in eng hiring in the typically slow summer season - I'm curious to see how the macro environment impacts this uptick as we head into the fall, but I remain hopeful. I asked Gemini to give me the tldr of the article to share with my team (sorry, Gergely Orosz) and found it missed one of the most interesting pieces of the article. Gemini's highlights - Unexpected surge: Tech recruitment has seen an unusual spike in June and July, contrary to typical trends. Increased demand: Startups, especially AI-focused ones, are driving the hiring uptick. Global phenomenon: This trend isn't just limited to the US; Europe is also experiencing increased recruitment activity. Reasons for hiring: Companies are backfilling positions, investing in growth due to improved financials, and responding to increased VC funding. Challenges remain: While the job market is improving, finding qualified candidates and offering competitive compensation remains difficult for many companies. What I found most interesting - The nature of the backfills: the article finds that a lot of new headcount are actually backfills of folks that were "over-slashed" during rounds of layoffs. Not entirely surprising with the "trim the fat" and "rebuild lean" mentality, but interesting nonetheless. Either way, the uptick is encouraging (and don't always rely on Gemini's tldrs). #hiring #startups #VCbacked #softwareengineering

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I spoke with Eric Ignasik and Michael Sols from The Software House about dealing with silos at work. 🎙️ We discussed how Technology Managers can help their engineers gain deep operational expertise and take full responsibility for product/feature delivery. The best practices I described in this interview come straight from Payhawk. It doesn’t mean they can simply be copied — but they might be inspiring to some. Happy reading 👋🏼 ➡️ hubs.ly/Q02xn9j-0 #softwaredevelopment #cto #softwaredelivery

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Venture Capital Contact Compilation. Explore a detailed list of 1,250+ VC firms, 7,400+ professionals in the VC space (including partners and principals), and 6,400 email contacts. https://payhip.com/b/cs7UQ #startup #startups #vc #venturecapital #investmentbanking #privateequity #managementconsulting #b2b #founders #entrepreneurs

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Attention founders or founders in the making. Michael Ho always has great insight on a lot of topics. Check out this one on navigating from Seed to Series A.

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~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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This tactic, in which A.I. companies promise wild new features and deliver a half-baked product, is becoming a trend that is bound to confuse and frustrate people. The $700 Ai Pin, a talking lapel pin from the start-up Humane, which is funded by OpenAI’s chief executive, Sam Altman, was universally panned because it overheated and spat out nonsense. Meta also recently added to its apps an A.I. chatbot that did a poor job at most of its advertised tasks, like web searches for plane tickets. Companies are releasing A.I. products in a premature state partly because they want people to use the technology to help them learn how to improve it. With artificial intelligence, companies are giving a preview of a potential future, demonstrating technologies that are being developed and working only in limited, controlled conditions. A mature, reliable product might arrive — or might not. The lesson to learn from all this is that we, as consumers, should resist the hype and take a slow, cautious approach to A.I. We shouldn’t be spending much cash on any underbaked tech until we see proof that the tools work as advertised. From New York Times, The New ChatGPT Offers a Lesson in A.I. Hype https://lnkd.in/dgD_tYne

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Is this the end of embeddings? Hear from Josh and Tashrish on the pros and cons of using embeddings-based RAG for document data extraction and our experiments with switching to completions-only RAG.

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Triangle startup ecosystem - first thanks for the incredible generosity that you showed over the last 2wks to help folks impacted by Helene. Here's a last update on our Hurricane Helene relief efforts with a final 'how can you help' ask. The TL;DR - our nascent effort has matured and morphed into the WCEN. The most urgent need has moved from supplies to funding the teams out on the ground that need specialty items like gas, oxygen tanks, starlinks, etc. There's a gofundme, this is a certified 501(c)(3) here-> https://lnkd.in/e4NdxuW8 What is the WCEN you ask?!.... o There were several operating groups that were able to grassroots consolidate efforts under the Western Carolina Emergency Network (WCEN) umbrella and they have a website up that is improving every day: https://lnkd.in/ePYP6_JJ o WCEN's goal is to provide services to survivors until temporary infrastructure can be re-built. There are over 1m people in Western NC without shelter and basic necessities. o WCEN is providing: -> Reconnaissance -> Search + Rescue ( + Recovery) -> Rapid Supply Response / Air Support -> Medical Care o WCEN has these network partners: -> Operation Airdrop Inc- Air support including planes and helicopters -> Carolina Calvary - Coordinator for Operation Airdrop -> Razor Nation - ATV support -> Restoration Church @restoration church - Josh Brown and Ryan Honeycutt- supply collection sites and delivery -> Apex Defense - Search and Rescue, Security -> Lincoln County Airport - Pilot coordinator -> AJ - Heavy Lift Drone support -> GSDF team - C&C logistics, Special Forces team coordinator -> Reagan Madison Inc. team- Back office, infrastructure, and fundraising,FOB coordination (Crystal Suazo, CPA - who looped this together and we connected with here on LI!) -> WRTE, Inc - Legal, tax, fiduciary support -> Christina Marie Noel - Christina Noel + volunteers - Strategic marketing & communications -> United National Weather Team - Medical support with ATV abilities if anyone, especially corps would like to donate $, volunteers, trucks, etc. please contact William McGuire (on the ground items), Rebecca Ross / Jess Porta (Triangle-based corp donations/logistics). We're getting the last truck of items at Raleigh Founded out and future donations should be made at: Electric Supply Co 207 Bickett Blvd Raleigh NC, 27608 Want more ideas on how to have an impact? https://lnkd.in/euNxS8kd Thanks again everyone!

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Great AI agent-based conversations at Neon's dinner yesterday. Paving the way for a world full of agents means re-thinking some core infrastructure layers: - Neon is actively exploring new use cases to better support agents. Database per tenant to spin up a DB in milliseconds opens up new possibilities. - We're pushing hard on knowledge graphs to better constrain where and what we should investigate in production systems. - Daniel Mason @ Anon is solving identity for agents. - Agent-to-agent communication will be a thing, like we have APIs today. Can our SRE agent co-ordinate with your PM agent to get things done?

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AI memory is fundamental for conversational AI and AI agents. It is critical for building personalized experiences and improving reasoning. Check out Letta’s course to understand how to use AI memory to enhance the customization and quality of your AI app.

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👩‍🚀 Fellow Tech People, we're exploring moving away from our custom API/websocket LLM interfacing at LEAGUES in favor of ELL. 🤔 The potential for streamlined API interactions, simplified prompt management, and reusable functions is really appealing. That said, I’m reaching out to the community: has anyone implemented ELL in production yet? I'm curious if ELL is the way to go for long-term scalability and maintenance reduction when interacting with LLMs. And what about Langchain—why choose one over the other? I'd love to hear your experiences and thoughts! #LEAGUES #ELL #Langchain #AI #TechInnovation

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Hiring and working with excellent people is what makes starting a company so fun

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Hey Network, happy Monday. I was ruminating today on the ever-increasing complexity of the GenAI tooling decision matrix that many of our clients face when I came across this timely collection of factoids: https://lnkd.in/gDmczhYJ. Something that we contend with in my work, as the major models have become commoditized, is the decision becoming less about benchmark performance and more about the cost/value equation or the nuance of usage patterns favoring different "category leader" capabilities. Or sometimes just platform vs. best-of-breed. With the commercial models all qualifying as "usually quite good," and the open source models closing the gap (something I'm super nerded out about,) I'm curious how you make decisions for yourselves or your clients about the right tool for the job (something, something hammer and nails...)

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Two books I always recommend are Peter Thiel's "Zero to One" and Eric Ries' "The Lean Startup," despite their occasional conflicting advice for startups😉 . Mike Maples, Jr 's "Pattern Breakers" https://lnkd.in/dPQWU8aB is now an instant recommendation and the essential bridge between these two books.  While "Zero to One" emphasizes the importance of monopolies and uncovering technological secrets, it often falls short in guiding readers on how to evaluate these secrets' worth or origins. "Pattern Breakers" addresses this gap through Inflection Theory and the concept of living in the future. Two things I am constantly working on. The book's first half is packed with examples and practical tools to identify and leverage inflection points effectively. On the other hand, "The Lean Startup" champions the power of iteration, but it sometimes leaves entrepreneurs (namely me) wondering when to pivot, when to persevere, and how to build momentum. The second half of "Pattern Breakers" addresses this by offering strategies to derive actual insights from iterations and turn them into transformative movements. And of course, when to be disagreeable and stick to your vision. I can't recommend this book highly enough; it's a must read.

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Where traditional #SAST scanners fall short, HoundDog.ai excels by detecting #PII data leaks directly at the code level. While SAST scanners are effective against predictable patterns, they struggle with the diverse naming conventions developers use for functions and methods handling sensitive data. HoundDog.ai overcomes these challenges using #AI and advanced techniques such as interprocedural and taint analyses. It’s a privilege to be part of this venture.

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Can probabilistic models, like LLMs and Nate Silver's election forecast model, ever truly be perfect, with no errors? According to Nate Silver: "We don’t talk about it much, but there’s a small amount of error introduced into the model because it’s probabilistic rather than deterministic. The margin of error on 40,000 simulations is about ± 0.5 points of win probability for either candidate; after 80,000, it declines, but only to ± 0.35." Sounds like a familiar refrain around Infactory as we discuss the limitations of LLMs... P.S. Vote!

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If you’re an early-stage founder, finding out what your customers *really* want so you can build the right product is critical. I’m excited to share some of First Round Capital's PMF Method program with Gagan Biyani on Friday! Gagan has founded 3 companies including Udemy, Sprig, and Maven. We’re hosting this live conversation for product leaders & founders on how to reach PMF. You’ll learn: - How to identify your customers' real problems - How to test demand by selling before building - When to write code vs. build a no-code MVP RSVP to join on June 14th (it’s free): https://bit.ly/3VBAK69

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