Richard Crowley

Ever since we launched SHAKTI, every quarter we write a letter to our LPs = Each letter includes an update on the portfolios, the GP's (our) view on the zeitgeist, an interview with a portfolio CEO and an interview with a TITAN = So far, we have 16 such letters = it's been on our "to do" list to share these publicly (i am lazy) = then Google comes along to save lazy people like me (thank you NotebookLLM) = here's a 10 min podcast summarizing our journey since Dec/2020 with the 16 LP letters as source = if you wanted to know what we are about, this is a pretty good place to start = https://lnkd.in/db7K2TrT cc SHAKTI

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Want a front-row seat to the frontier of tech? We’ve got the role (or two) for you! We’re expanding our frontier-tech team at Blackbird by hiring a Frontier Tech Investments Associate and Foundry Fellows! Got questions? We've got answers... 1️⃣ What are the roles? 🧪 Associate = a full-time VC investment gig in our Blackbird Investments team, working directly with me. We’re looking for someone with a science and/or engineering background and more curiosity than they can handle. You’ll grow your own investment brand and practice, support our portfolio founders, and will help build Foundry, our early-stage frontier-tech accelerator. ✨ Foundry Fellow = a casual/contract gig in our Blackbird Investments team, ~15h per week for 3 months. The Fellowship is ideal for PhD students and ECRs who want to learn more about startups and VC. You’ll go deep on emerging areas relevant to your expertise (or curiosity!), get a front-row seat to groundbreaking companies in those areas, build out your non-academic network, and develop a solid writing practice. 2️⃣ Why are you hiring? We love frontier tech, and we’re ready to grow our team. 3️⃣ Wow, it’s so great that you’re starting to look at deep tech! Look, we get it: we don’t make a lot of noise about our frontier tech investing. Buuuut we’ve been deep-tech investors since we backed Tim Kentley-Klay to found Zoox back in 2014—we’ve been on incredible journeys with PsiQuantum (building the world's first utility-scale quantum computer right here in Australia!), Inventia Life Science (transforming drug discovery with high-fidelity cell models), Remedy Robotics (surgical robots for remote endovascular procedures), Opto Biosystems (minimally-invasive neural implants to treat cancer), and more. We believe that frontier technologies, and great frontier-tech investing, will be part of the solutions to the greatest problems humanity faces today. 4️⃣ When do applications close? May 31st at 11:59pm AEST. 5️⃣ I have more questions! I’m sure you do! Clare Birch and I are hosting an AMA to answer any and all questions about these roles. Want to know what a week in the life of our team looks like? What’s keeping us up at night? What our ideal candidate looks like? Come along and find out - registration link in the comments 👇 Apply for these roles: Associate - https://lnkd.in/gCfj4EUJ Foundry Fellowships - https://lnkd.in/gj6ATZVZ If you know anyone that we should meet, send me their details! Cameron Elise Ben Andrew Robin Joseph Adelaide James Olivia Lucinda Raghav Jesse Christie Mohamed Tom Amee Pablo Haya Loong Hon Joshua Benjamin Megan Harry Denzil Matthew Diana Daniel Tom Deanna Justin Amar Lilly Stone Thomas

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I have been thinking about "Why, after 6 years, I'm over GraphQL" (https://lnkd.in/g_XDCvbQ). I faced many of the same issues with my GraphQL implementations but came to a different conclusion that led to Exograph (https://exograph.dev/). ❗ Problem: GraphQL authorization is a nightmare to implement. ✅ Solution: A declarative way to define entity or field-level authorization rules. In Exograph, you define authorization rules alongside your data definitions. This not only makes it easy to audit authz rules, but lets you lean on the engine to enforce them. ❗ Problem: GraphQL queries can ask for multiple resources in a single query, overwhelming the backend. ✅ Solution: Trusted documents, query depth limiting, and rate limiting. Exograph supports trusted documents/persisted queries and other mechanisms to control the load on your backend. ❗ Problem: GraphQL queries can overwhelm the parser. ✅ Solution: The same solution as above. You can control the load on your parser by using trusted documents and limiting query depth. ❗ Problem: GraphQL queries can lead to the N+1 problem. ✅ Solution: Defer data fetching to a query planner. The classic and dreaded N+1! Exograph uses a query planner to ensure that you never run into this. ❗ Problem: Balancing authorization and the N+1 problem can be tricky. ✅ Solution: Make authorization rules a part of the query planning process. By making authorization rules a part of the query planning process, Exograph ensures that you never fetch data the user is not authorized to see. ❗ Problem: GraphQL makes it quite hard to keep code modular. ✅ Solution: Reduce the amount of code by leaning on a declarative approach. More code, more problems! In Exograph, you write only a few hundred lines of code to define even complex data models. ❗ Problem: GraphQL makes balancing authorization, performance, and modularity tricky. ✅ Solution: Simplify implementing GraphQL through a declarative way to define data models and authorization rules. This is the core of Exograph: declarative data models and authorization rules. Read the full blog post at https://lnkd.in/gBwpXMHF

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DeepCast shipped a number of really cool new features recently in advance of a broad outreach push to podcast listeners. One new feature is our new Daily DeepDigest tool that sends you a concise daily email including any new episodes from the trailing 24 hours from any podcasts you Subscribe to (on DeepCast). Think daily podcast cliff notes or podcast news ticker tape, with a hint of Morning Brew various brews or PitchBook News—it's increasing information throughput when you're pressed for time. And this feature is rapidly evolving to distill other key extractions from shows you're already interested in, but also exposing you to other shows you might be unfamiliar with that also have nuggets to share—and thus increasing your aperture yet still conscious of your time. Want to go deeper on any given episode? Click the episode detail and you're off to an episode on DeepCast, where you can subsequently read a longer form distillation of that episode or go straight to the source and listen to the episode. (And podcaster friends, these pages are definitely increasing indexing and thus Google entry points to your shows!) I'm loving this feature as a user, personally. Can't wait to see what others think! #BuildingInPublic #Podcasts #AllTheWorldsInformation #HowYouWantIt

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During yesterday's LibreQoS APNIC webinar, I posed the question: won't more bandwidth solve these problems? As Herbert Wolverson said, yes, more bandwidth is good, but, still these problems remain if queueing is done incorrectly. Here's my take on why bandwidth alone is not as good as bandwidth + good queueing policies: Generally it was believed that 'data is important, so don't throw it away; hang on to it and send it later'. In practice, this has proven to be suboptimal as two issues may emerge: 1) latency increases for some flows due to heavy demand from other flows using the same bottleneck link, 2) even a single flow can have excessive latency due to aspects of typical TCP behavior (referred to bufferbloat) when the buffers grew large enough that the data being buffered was retransmitted anyway. It turns out that not all data is equally important. Active Queue Management is the art of deciding priorities, both in deciding what data to throw away, but also in allowing some later arriving data to be transmitted ahead of data in another connection that arrived before it. These problems have been studied, and good solutions have been found by using certain queueing policies in routers and switches, referred to as “fq_codel’ and “cake”. These track the different flows not by classifying the data, but by watching the behavior. Flows that send relatively little data (DNS lookups), or at a measured pace (video chat) have priority over flows that send a lot of data as quickly as possible (App and System updates, Video and ISO downloads).

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*Full disclosure: I'm an angel investor in Requestly* This is the feature I wanted as soon as I tried the product. I find most developers take too long to stage their setup and this is the number one productivity killer. TDD and all is great, but not very practical for a lot of projects and hard to practice when you have a complex set of dependencies (especially between front and back end). Being able to quickly record mocks and apply them makes front-end development *so much faster*. I think this is the way all front-end teams should work. If you do any JS development, go give requestly a try right now, it's free and open source.

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Interesting concept to rename rounds by milestones. But "Series Client Expansion Extension" just doesn't have the same ring to it 😋 . Maybe we can start incorporating it into a descriptor to add context, "Series Seed Extension: client expansion." #startups #venturecapital

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Early stage VC investing is a job for the innately curious with an aptitude for risk.

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