Andy Chou

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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In vertical SaaS, the very best companies landed with a product solving a specific, burning pain point that horizontal solutions solved badly and then became broad product suites over time (ServiceTitan, Veeva Systems, Doximity, etc). My partner Gordon Ritter calls this “layering the cake”. In vertical AI, the landing wedges are much more brittle. While the painpoints they solve are very real (and often unaddressable by SaaS alone), they’re also much more likely to commodotize in the near term as the tech advances. 👀 Therefore, the need to layer the cake in vertical AI is much more urgent than in vertical SaaS. 👀 The best vertical AI CEOs not only recognize the dynamic, but talk about it openly. Helps those around them keep up the speed of innovation and their eyes on the bigger prize.

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Today, GTMfund’s is excited to announce to launch of Operator, its first incubated company. Max Altschuler (founder of GTMfund) teamed up with co-founder Adam M. (design engineer and 0-1 builder) and co-founder Mark Kosoglow (Outreach employee #1 and former SVP of Global Sales) to create Operator.ai alongside an insanely talented team Pleasant Middelhof, Jeremy Jonas, Carl Gunderson. We've entered a period called “The Great Ignore”. Spam and irrelevant, poorly-automated outbound campaigns are running rampant.   Operator gives you an easy-to-use Growth Engineer that allows you to build and enrich lists with accurate data, and run experiments and queries using AI to generate highly targeted outreach.    Check out their website to get updates, early access, and see how they are taking the world back to 2 touches meant to attract buyers into conversations that convert, instead of 20 touches meant to make sure you hit your activity number: https://www.operator.ai/

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In this week's episode of the Mobile Dev Memo podcast, I speak with notable X personality Trung Phan about the evolving social media landscape, and how to tame the mayhem and pandemonium of X. https://lnkd.in/dVHMzbui

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Ross Haleliuk posted the fantastic article below. This is the world where I live day-to-day. At TechOperators, we invest mostly in early-stage cyber, but we do things a little differently, and we believe there are ways to invest successfully outside of pure Power Law math. The article argues that many security problems are too small for VC. I agree. I often try to convince bootstrapped founders not to raise venture because doing so can turn a successful, slow-growing bootstrapped company into a failed venture-backed company because, despite a large infusion of capital, it couldn't double every year. VC is not monolithic--not by stage, strategy, or style. Venture is often equated with "Tier 1 Venture". Ross argues that VC is not always great for early-stage cyber--and he is right. Bootstrapping AND VC work when incentives are aligned. Does it work for an early-stage VC with a <$200M fund to invest in several early companies at reasonable valuations, setting up the conditions for reasonable exits that pay off for both investors and founders? Yes. Does it work for $800M funds investing in seed stage at $100M+ valuations? Well, that depends! Power law says it does (for VC), but the unfortunate externality is that these rounds destroy companies and founder equity more often than not. There is a role for patient capital in this ecosystem to fuel successful companies that retain exit optionality as they scale--driving exit value for both founders and investors.

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For a young software company, what does a dream end-market look like? A few great signals off the top of my head: ▶️ Low NPS of incumbent solutions ▶️ Lots of manual / lightly-digitized processes ▶️ Many buyers (i.e. top 3 don't control the market) ▶️ High ability to pay (decent margins and trendlines) What else should be on the short list???

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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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🎃 Ready to carve out your path to Product-Market Fit?🎃 Join Companyon Ventures’ Behind the Curtain roundtable tomorrow (Oct 30) with Michael Ho, Firas Raouf, Eric Morgan, and Hersh Tapadia as they 'exorcise' the mysteries of PMF. Don’t ghost us—RSVP in the comments 👻 https://lnkd.in/emCJcn4w #emergingmanager #venturecapital #productmarketfit

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VC platform teams rarely add meaningful value to portfolio companies. They’re mostly a tool for GPs to justify raising larger funds and collecting higher management fees.

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Sharing this primarily for markets outside the top 5 in VC as it's a problem I've experienced as well. One can and sometimes should criticize SV founders who have too much ambition in the way some pursue it, but a super serious problem almost everywhere else is not enough ambition, certainly to include NM. It may surprise some to hear that Seattle lacks ambition given headquarters of Microsoft, Amazon, Costco, Starbucks and others, but that's actually part of the problem--golden handcuffs and conformity, versus hungry and competitive when I grew up in WA in business in the 80s. It's also a problem with many VCs around the country now. They have become so focused on flipping to incumbents their (BT) dominance became a self-fulfilling prophecy. That's not the role of VCs -- if that's their goal they should be a CVC. NM has a similar golden handcuff problem to Seattle, but it's worse in some respects. The national labs pay really well relative to the local cost of living, so it's the career goal of thousands to spend entire careers working for the labs. In both markets the level of early stage funding is so low that it's difficult to leave big tech or labs to join a startup. And in both, the experience of big tech and labs doesn't apply well to startups. Very different world. A related challenge is SV rarely invests outside the region in would-be market leaders--most want to see those remain in CA. So we have a problem for certain, and big disconnect in the market.

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I had an absolute blast with Michel Gagnon and the Stun and Awe crew - THANKS again for having me... Sneak peek of the substance below: > Micro SaaS companies can be just as safe and stable as larger businesses, offering lower valuations and less competition from institutional players. > Founder-product fit is crucial, as founders solving their own problems often create useful products with great retention. > Founder burnout can be a buying signal, indicating a solid business with a founder ready to move on. > The first 90 days post-acquisition should focus on visibility, documentation, transition, and validating diligence assumptions before pursuing growth. > Building transparently and maintaining open communication with users post-acquisition helps preserve the human element and avoid the pitfall of going silent. > Simplicity equals mastery - if it takes a complex explanation to justify an acquisition, you probably don't fully understand the business. > Establishing reasonable incremental growth goals based on baseline performance (systems over goals) is more effective than setting arbitrary targets. > Fostering a culture of care and respect enables honest feedback and allows teams to move faster through a shared commitment to truth-seeking.

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"Falling costs of building new software companies are a mirage, and the reason for that is this thing in economics called the Jevon's paradox... ...the Jevon's paradox occurs when technological progress increases the efficiency with which a resource is used (reducing the amount necessary for any one use), but the falling cost induces increases in demand enough that resource use overall is increased, rather than reduced." Marc Andreessen with a counterintuitive take on what the future could hold for the software industry. #tech #technology #innovation #software #deeptech #startups #entrepreneurs #entrepreneurship #ai #artificialintelligence #vc #venturecapital #money #business

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I like this idea of "technical taste". It gets into where software engineering is as much creative art as it is science. Four great takeaways (IMHO) for software devs in this era in particular: 1. Aspiring engineers should cultivate a sense of curiosity, experiment with different tools and technologies, and embrace a mindset of continuous learning. 2. AI has the potential to streamline processes and enhance productivity for engineers, but it may also lead to disruptions in traditional software development workflows. 3. Developing technical taste and judgment is essential for making informed decisions about which technologies and approaches to pursue. 4. Collaboration and open-mindedness are key to leveraging the full potential of AI and staying ahead of technological advancements. I also really liked these two quotes from Sam Schillace: 1. "The right time to do something is when you have that feeling in the pit of your stomach that's like, 'oh, this is a great idea and it's going to suck to build because nothing's ready yet.'" 2. "Technical taste is like, 'how well have you consolidated that set of experiences and heuristics into judgment that you can apply accurately when you see new things?'" 3. "It may be the case that very small teams can do very large projects, or like we were talking about before, it may be the case we're just going to get really ambitious about what we try to do with the same size of teams, which is kind of where I would put my money." Great job on continuing to put out great episodes, Brett Berson and team First Round Capital! #ai #engineering #softwaredevelopment

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We're launching the inaugural edition of Beyond Benchmarks, a deep dive into the metrics and trends observed across the early-stage enterprise cloud market. This is the first look at some of the business data around GenAI in SaaS. Some initial observations: 1) 60% of SaaS companies have already integrated GenAI into their offerings (60% of these as part of their current product and 40% as a new product), and an additional 20% are planning to do so this year. Almost half aren't monetizing these features. Those that are are primarily experimenting with both usage-based and flat fee pricing models. 2) Most companies are utilizing OpenAI as their primary LLM, but many are experimenting with multiple models - and we are noticing an early trend towards intelligently routing GenAI inference requests to different models based on cost, performance, and security. 3) Though we are in the initial innings of GenAI, we are seeing some positive signals - companies that implemented GenAI had 7% higher NDR than those that did not. Still early days, but we'll be doing this benchmarking report regularly to track and share how things progress in this new era. Link to report in comments.

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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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Insightful breakdown from my great Partner Omri Amirav-Drory on the simple factors that really separate the top 1% of investors from the rest, and how more operators should become investors! https://lnkd.in/gEiZdT2h

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Instacart is a market leader when it comes to leveraging AI tools to boost productivity at work. I had an amazing conversation with JJ Zhuang, Instacart’s Chief Architect, who has shepherded over 50 AI-driven initiatives to market across the org. We explored what catapulted Instacart to the forefront of AI integration, supporting radically diverse use cases across various functional areas. One striking insight (echoed by Ethan Mollick and others elsewhere) is that you often don't need specialized tools for specialized work. Frontier models like GPT-4 can seamlessly adapt to a wide range of functions and use cases. They're not just for engineers; they're incredibly versatile tools used by marketing, comms, and legal teams. From generating code to proofreading and ideation, GPT-4 empowers every department to leverage AI for enhanced productivity and innovation. By integrating LLM’s like GPT-4 into their workflows, teams can streamline processes, automate repetitive tasks, and unlock bandwidth for new creative possibilities. How can you harness the power of AI in your own work to boost productivity? Share your thoughts below 👇 Want to hear more insights from JJ? Check out the full podcast episode by clicking the link in the comments.

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ex Google CEO Eric Schmidt spoke at Stanford this week. Lots of nuggets here, but most interesting for the near term, Schmidt believes in the next year AI is set to make a big leap forward. He predicts AI will combine three important features: 1. Vast knowledge retention (1 million token models) 2. Text-to-action capability 3. Personal AI agent fleets While the full impact is unknown, everyone may soon command their own AI teams. Here's an example: Imagine you're developing new quantum computing algorithms. Your AI assistants could: - Continuously scan and synthesize global quantum research papers - Generate novel algorithm ideas based on this knowledge - Simulate and test these algorithms across various quantum architectures - Automatically document findings and prepare draft papers - Identify potential collaborators and draft outreach emails All initiated by a command like "Advance our quantum algorithm research." This could dramatically accelerate R&D cycles and scientific breakthroughs.. https://lnkd.in/eJbg6cnD #frontiertech #AI #futurefrontier

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