Lucas Adams

🔥 2-Min Survey: Help Fix the Insights Pipeline, Boost Your Next Review At Ara Platforms we're *obsessed* with the data -> insight -> action pipeline and removing roadblocks. On the data (insight producer) side, we want to make it easier to generate and publish useful insights. On the stakeholder (insight consumer) side, we want to make it easier to ask questions and get useful answers quickly. The process feels like a broken market—data people produce insights that don't get used while stakeholders don't can't get insights to important questions in a timely manner. If you're on either side of this equation I'd love to chat—please reach out via DM! If you can't it would mean a ton if you could fill out one of these quick Google forms. The end goal is to improve everyone's performance reviews Insight producers (data scientist, analysts, researchers): https://lnkd.in/emtMV6um Insight consumers (product managers, leadership, anyone who uses data to make decisions): https://lnkd.in/eEJ3Wse7

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🚀 **Exciting News: Introducing Intrinsic Research** 🚀 Today marks the launch of Intrinsic Research, a brand-new Substack where we dive deep into the evolving world of data science, machine learning, and AI—while exploring their broader impact on society and culture. 🔍 What can you expect? Each week, we’ll break down complex data science concepts, share insightful stories from the cutting edge of AI, and explore how these technologies are shaping the future. Whether you're a seasoned tech expert or just curious about where AI is headed, Intrinsic Research is designed to keep you informed and inspired. 🎯 Why Subscribe? - Free insights into major trends and foundational concepts   - Exclusive, subscriber-only content and full archives for paid members   - Access to community discussions and special perks for founding members  Don’t miss out! Join us on this journey to unlock the mysteries of data, tech, and culture. #DataScience #AI #MachineLearning #TechCommunity #Substack #AIRevolution #IntrinsicResearch #TechInnovation #NewBeginnings

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Sharing some insights/trends we are seeing in the first half of 2024: - The majority of startups HQ’d in NYC & SF founded in the last two years are hiring most if not all of their employees in the office (at least 3 days a week) - Less than 5% of those are mandating 5 days a week in office. - Most top candidates are optimizing for hybrid with remote up to 3 days a week - Compensation across the board for early-stage startups has remained relatively flat since 2023 - For startups located outside of core major tech hubs, there is more openness and even preference for remote to tap into broader markets and compete for top talent The overview is that local talent and teams are making a comeback and salaries are not rising as drastically as they have in the past 5 years. Make sure to choose your next move based on fit, impact, passion, upside, growth, and not purely on comp. #startups #venture #VC #seed #Engineering #Hiring

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🚀 Zetta just released a new feature for automated anomaly detection to tell you when your data isn't looking right. Data quality is one of the biggest challenges data teams face and Zetta is solving this so you can trust your data and make confident decisions. Zetta is an all-in-one AI data platform designed to give you instant data clarity and insights—no data team, infrastructure, or building required. Company wide automated analytics and insights can be setup as quickly as one day with Zetta. Here’s what you get with Zetta: Ready-to-use dashboards that track your key metrics Automated insights that tell you what’s driving your numbers Predictive forecasts to help you plan ahead A conversational AI Analyst so you can explore your data with simple questions A secure, reliable, and scalable data warehouse that’s fully managed for you Let's unlock the full potential of your data, together! https://zettadata.ai/ #AI #Data #Analytics #Businessintelligence #Startups #Growth

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If you're wondering how AI will be monetized, and how we'll come to pay for it, this article by Abde Tambawala and https://lnkd.in/gYJxgPSS is worth a read. If you're building an AI-driven product and are thinking about how you'll price and package it, this is a must read.

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One of the biggest challenges for improving performance on Meta is teams beeing held accountable for daily (and sometimes hourly) results. This isn't enough time to try new strategies or products. So by optimizing towards a daily ROAS goal in the short term, might hurt performance in the long run as you could be missing out on new solutions.

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One of our biggest learnings building AI developer tooling is that vanilla RAG doesn't work out-of-the-box for code search. At scale, the embed code + retrieve paradigm leaves many unanswered questions: ✅ What's the right semantic chunk of code to embed? ✅ How can you use the interdependency between different source files / classes to inform similarity? ✅ How quickly can you reindex a large codebase to keep results fresh? ✅ How do you prioritize different file types (a typical Python library may have .py, .txt, .pkl, .ipynb, .md, and more)? These questions have to be solved to unlock generative development over all the world's code.

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Comprehensive #Seed VC Contact Database. Access a list of over 1,250 venture capital firms, 7,400+ VC professionals (including partners and principals), and 6,400 email addresses. https://payhip.com/b/cs7UQ #startup #startups #vc #venturecapital #investmentbanking #privateequity #managementconsulting #b2b #founders #entrepreneurs

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📈 Curious about the startup scene in Massachusetts? Explore our detailed funding list featuring startup names, HQ locations, and investor info. Perfect for investors and entrepreneurs alike! Check it out: https://lnkd.in/dAp3xj-Q #startup #startups #venturecapital #funding #vc #managementconsulting

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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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Are there CTOs/VP of Engineering in Philadelphia who are interested in learning about Gen AI saving 30% of their team's time on top of CoPilot? Send me a DM. #cto #vpofengineering #generativeai #genai

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In the future, all efforts will on data curation and engineering. All model training and Fine-tuning will be standardized. That doesn’t leave much to do for AI engineers :)

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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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🔮 What's the future of developer platforms? ☠ Or the death knell for open core companies? Get the answers (and more) from Ethan Kurzweil; longtime partner at Bessemer Venture Partners and soon-to-be founder of a new, early stage venture firm. In his time at Bessemer Ethan invested in Launchdarkly, Twilio, PagerDuty, Intercom, Twitch, SendGrid, HashiCorp and npm. He's seen it all, you won't want to miss his takes on what's next and what isn't going to work. I'm sharing our closing lightning round questions here, but the full interview (which is much juicer) can be found at calyx.substack.com. ⚡Lightning round questions!⚡ *What's the developer platform that you respect most?* 🔶 Zapier. It's the ultimate democratizer of development for 4,000 different esoteric use cases and some not so esoteric use cases. And they built it in a way to allow anyone to use it. *Who is a developer GTM leader you respect?* 👨 Adam FitzGerald at HashiCorp. Disclaimer - he’s a Bessemer operating advisor. He is the best thinker to help companies structure developer evangelism programs at scale. *Unpopular opinion re: dev tools?*  💼 That a lot of dev tools shouldn't be businesses. Many should be free or part of a larger developer platform offering. The difference between tool and platform can make a big difference as to whether you have a sustainable business. *How do you feel like you’re able to uniquely work with developer-first companies?* ⚾ I’ll keep it to one for the lightning round: I’ve gotten lots of experience with false signals. If you’re a founder working on a startup sometimes you’ll respond to a false signal and it’s hard to go back and unwind those choices—we have lots of experience with developer platforms and can help founders avoid those pitfalls. Disclaimer: Ethan would never use emojis like this. He actually...doesn't use emojis!? I've just added them in an attempt to improve readability on LinkedIn... enjoy!

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Here's the secret behind fast roster scheduling: I don't use generic solvers at all. Instead, I use Mixed Integer Program (MIP) Solvers. Generic (e.g. MINLP) solvers are designed to be versatile, but their solving speed is not so fast. MIP deals with more constraints in how you could formulate the model, but in general it's orders of galaxies faster than MINLP. As your problem scales up: - Solving speed: MIP > MINLP - Handling Complex Formulations: MINLP > MIP But MIP can handle 99% of rostering problems by itself. That is why I choose MIP over MINLP solvers. I've written an article on how we use mathematical models to power our rostering engine. Read it here: https://lnkd.in/ecvkKuH5 What other approaches have you tried to speed up your scheduling?

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We have the largest database of LLM API pricing at Helicone (YC W23) with over 300+ models! 🚀 And it's now fully open-sourced! We've launched a free LLM API Pricing Calculator that lets you compare costs across various models and providers like OpenAI, Anthropic, and more—all in one place. 📌 Link in the comments

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With Redpanda Data's recent acquisition of Benthos I've gotten some questions about how it compares to Arroyo. In short: Benthos is *stateless*, while Arroyo (like Flink or RisingWave) is *stateful*. This may sound small, but adds up to a fundamental difference in how these systems are designed, built, and used. In a streaming engine, statefulness combines two inter-related features: * Repartitioning data (GROUP BY in SQL) * Remembering previously seen events With just these two features, we can support most of normal SQL (window functions, joins, aggregation, etc.) plus time-oriented streaming operators (time windows, event-time semantics, watermarks). Stateless engines on the other hand are limited to simple transformations and filters (SELECT and WHERE in SQL terms) that operate on individual events. But all of this is a tradeoff; stateful systems are much harder to operate. So if you don't need joins, aggregates, or windows, a stateless system can be a better choice. They also work well as infra glue, routing data between different systems—Benthos in particular has a huge connector ecosystem. For a deeper dive on this, I wrote down some thoughts on our blog:

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Huge opportunity

Paul Graham’s article on ‘Founder Mode’ versus ‘Manager Mode’ for managing a company is spot on! It aligns closely with what Peerdom facilitates. "In effect there are two different ways to run a company: founder mode and manager mode. Till now most people even in Silicon Valley have implicitly assumed that scaling a startup meant switching to manager mode. But we can infer the existence of another mode from the dismay of founders who've tried it, and the success of their attempts to escape from it. There are as far as I know no books specifically about founder mode. Business schools don't know it exists. All we have so far are the experiments of individual founders who've been figuring it out for themselves. But now that we know what we're looking for, we can search for it. I hope in a few years founder mode will be as well understood as manager mode. We can already guess at some of the ways it will differ. The way managers are taught to run companies seems to be like modular design in the sense that you treat subtrees of the org chart as black boxes. You tell your direct reports what to do, and it's up to them to figure out how. But you don't get involved in the details of what they do. That would be micromanaging them, which is bad." Source: https://lnkd.in/e3dPKa9e

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