People are surprised when I say “the right amount of fraud in seed stages startups is greater than zero.”
What I mean is, the community works best when we move quickly, and assume trust between parties. That will likely mean there are some founders who commit fraud (and some investors too I guess). The cost to the ecosystem for doing so much diligence and background checks to achieve zero fraud would punish the 99.9% of founders who are ethical. And punitive unfairly – there are probably people who are totally honest nice folks but you can always turn up a rumor or a mistake earlier in their lives – we don’t want these things to be disqualifying if they’re righteous now.
At each phase – Series A, B, etc – there should be *less* fraud. Because it gets discovered, stopped, or whatever. Basically, by IPO or other exit there should be aspirationally zero fraud.
Zero fraud is still likely impossible so we need mechanisms to punish those who are fraudulent at those stages. The fear of getting caught and paying the fine/doing the time is necessary alongside whatever morals/ethics they should have as individuals.
When financial fraudsters get pardoned for their crimes [Nikola, Ozy] before the punishment has been completed, it creates an environment that changes the calculation for those who might commit these crimes. This is wrong regardless of political beliefs and the two I cited above have nothing to do with regulatory policies of either party, but the rule of law.
I knew I had to meet Molly. That’s what I felt when several friends separately mentioned her to me. It was either a very well coordinated inception or independent validation. Frankly, either would have piqued my interest (I’m pretty sure it was the latter). It only took a few Blue Bottle coffees for me to become an evangelist for her too. Molly is thoughtful, always evolving and an incredible believer in people, whom she backs via Moth Fund. And I recently asked her Five Questions.
Hunter Walk:Moth Fund says it “aims to increase the agency of exceptional individuals.” Say more about what that means (you cover some in your manifesto) and how it influences your investment decision framework?
Molly Mielke: My approach to investing is singularly focused on finding and developing relationships with outlier people. I do this by being weird myself and making myself findable in the right places — namely word-of-mouth from people whose taste I respect and by sharing how I see the world online. This approach was designed around my edge; I have an innate interest in understanding human beings and as a result, have different kinds of relationships with founders than most VCs.
I talk about my investment decision-making framework in detail here — I focus on gaining an understanding of a person’s motivation, spike, commercial aptitude, and how magnetic they are.
I try to think rigorously about people and their potential, in part drawing from my experiences working with top founders over the past five years and the deep relationships I have with entrepreneurs in my cohort class.
HW:You write wonderful essays each quarter – what’s the process which goes into those? And what does ‘success’ look like for you with this energy?
MM: Each quarter I pick a (usually qualitative) “research” topic that I discuss with many of the brilliant investors, founders, and operators I meet with in the context of my investing role. I collect data points in conversation and start building my own theory of the topic, which I then write up and share with the world in the form of my quarterly essays.
I consider my writing a success if I’m able to produce words I can both stand behind/formally weave into my worldview and think are decently original/worth sharing with the world. Success also looks like having better conversations with the people I’m meeting — I find the process of truth-seeking together one that builds a lot of trust and understanding of each other. I am at my most honest and concentrated on the page, so sharing that version of myself online helps me put a stake in the ground about what I believe in and find others who resonate or disagree in interesting ways.
HW:I find you to be a thinker who uses other’s opinions to inform your own. As someone new’ish to venture capital, what’s a piece of advice you received early on that really shaped the way you think about Moth?
MM: While not an answer to your question, I want to first say that learning to relate to others’ opinions in a way that is constructive as opposed to confusing is something that took me a while to figure out for myself. I received a decent amount of advice from people more powerful than me in my first few years in Silicon Valley (mostly because of my Twitter) and while I was lucky to get the attention, it definitely made my head spin. I gradually learned to see advice as merely potent information about how the other person sees the world, which helped me take it much less personally. My goal in asking for advice now is usually in order to refine my internal model of the other person’s brain — the goal being that I could guess how they’d think through a given person/place/scenario without asking them. I like simulating other people’s perspectives in my mind and putting them in conversation with each other as a way of identifying blind spots in my own thinking.
A memorable piece of advice I received from my first LP was that: “the ideal investor is a finance bro with a dash of Engelbart.” While I didn’t change myself to become this, what I did take from this framing was that investors need to be commercially-minded no matter their stage, and that a dash of weirdness can be particularly beneficial at early-stage in order to attract other strange outlier people (hopefully some of them great founders). Another piece of advice I received from an early LP was to find a great coach who pulls from enneagram in order to better understand your own motivation and become more cognizant of your failure modes. I highly recommend doing this, especially if you’re embarking on anything solo and want to stick to something for a long time.
HW:How has your model changed between your first fund and Fund II (which I’m fortunate enough to be investing in)?
MM: My main learning from Fund I was that the area where I had the unique advantage was pre-seed rounds where I was one of the first checks in and investing with a deep understanding of the person’s potential to be venture-scale founder. The strategy of Fund II was designed around my spending as much time serving founders at this stage as possible, meaning I now write slightly larger checks and devote the majority of my investing time to building relationships with exceptional people who I think might one day start an interesting company.
More qualitatively, I’ve become much more shameless about Moth not being for everyone, while a perfect fit for the right founders (and LPs, you being one I feel especially fortunate to have on board!)
HW:Ok, something outside of work. Give me two places in San Francisco which you find delightful.
MM: I really like the Fort Mason area — strolling around the Sunday farmer’s market, getting a lemon ginger tea at The Interval, and eating sushi in the park as the sun sets.
Read while recovering from St Patrick’s celebrations
The Anti-Social Century [Derek Thompson/The Atlantic] – Is isolation a leading or lagging indication of breakdowns in community, political polarization, declining birthrates and other 21st century American challenges?
Men who watch television now spend seven hours in front of the TV for every hour they spend hanging out with somebody outside their home. The typical female pet owner spends more time actively engaged with her pet than she spends in face-to-face contact with friends of her own species. Since the early 2000s, the amount of time that Americans say they spend helping or caring for people outside their nuclear family has declined by more than a third.
Read it, preferably at a coffee shop, with a friend.
Stay Gold America [Jeff Atwood/Coding Horror] – Jeff’s a cofounder of Stack Overflow and writes here about an admirable decision his family has made: they’re going to give away half of their wealth to “long term efforts ensuring that all Americans continue to have access to the American Dream” such as Planned Parenthood, The Trevor Project, and other humanitarian organizations. Go go Jeff! Tech needs role models like this right now.
How I Used AI to Save My Life in 77 Prompts: A Debrief [Bethany Crystal/Hard Mode First] – My friend Bethany had an incredibly dangerous health scare which could have been much worse if she wasn’t a proactive, informed patient. She didn’t use Dr Google, but instead ChatGPT. She goes deep here on where and how it helped, the prompt chains, and the reaction of her medical care professionals. I
Thinking Through the Future for LLM Companies… and What This Means for B2B AI Startups [Sarah Tavel/Benchmark] – Sarah basically assumes the LLM platforms are going to evolve into competition for most of the B2B businesses built on top of them so she gives her best guess as to how to manage this as a challenger. You need either (a) a network effect, (b) proprietary or hard to access data, or (c) “execute like hell and land grab in an overlooked vertical.”
“Be great at the job and proud of how you’re doing it.” That was our rallying cry at the beginning of Homebrew. We figured that if we enjoyed it, but weren’t financially successful, we couldn’t do it for the rest of our careers. And if we made money, but weren’t happy with the work, we wouldn’t do it for the rest of our careers. So why not focus on both. This extended to how we pitched LPs as well, aiming for a very concentrated base of institutional investors. We figured that given their commitment to the asset class, so long as we did our job well and treated them like partners in our business, they would show up each fund to back us.
Years later Satya and I also started Screendoor alongside Homebrew. If Homebrew’s goals were to back exceptional founders building companies then you can think of Screendoor as backing exceptional founders building new venture firms. We’re now four years in, having invested in almost two dozen VCs, which by the way, if you’re raising a fund, let us know. Whereas Homebrew was always meant to be just the two of us, Screendoor is more expansive and now has a team of three running the show.
One of the folks, Lisa Cawley (Screendoor’s Managing Director), recently published a blog post called “Work with your LPAC, not for your LPAC,” which got me thinking about Homebrew’s LPAC (Limited Partner Advisory Committee). Ours has always been small – just like our LP base in general – and we’ve worked with them in ways that are spelled out in our LPA (Limited Partnership Agreement) but also used them for advice, as the name suggests. Lisa’s post – and more coming – goes into depth about what an LPAC is and how it can be helpful for a VC, especially a new firm. To make it really tangible, here are examples of why we’ve gone to our LPAC over the 12+ years of Homebrew.
Standard Asks/Approvals
Extensions on fund length as needed – everyone knows it’s taking longer to get liquid. No reason to sell winners prematurely just because of original fund length, especially given our LPs are largely cash-on-cash return focused more than IRR.
Exceeding our limits on company concentration and recycling – we are aggressive in using early liquidity to get more turns on the dollars rather than distribute. We’ve hit 120%+ recycled in most of our funds, and have gone beyond our 10% concentration limit (per the LPA) in at least four investments.
Investing in a startup across funds – while we generally don’t want to do this (for various reasons), there was an occasion or two where it made sense.
Situation Specific Guidance We’ve Asked About
Taking early partial liquidity – Big believers in smart portfolio management and that for true seed funds, taking secondary liquidity is an important tool to be used. While this is now becoming more common, when we started exploring these opportunities it was a little more contrarian, or at least, not talked about publicly. We asked our LPAC about what frameworks they’ve seen across their venture portfolios. Not surprisingly there’s no one approach – some of their managers never sell ‘early’ while others had a rule of thumb to try and pull 1x the fund out of their ‘unicorns’ at each growth fundraise. Most encouraging was hearing from our LPAC that we should never feel pressure to sell prematurely just to create DPI ahead of larger gains. And that they trust our judgment since we knew more about the companies than they did. So nice to have longterm partners like that.
Living our values – A while back we encountered a situation where we felt that, despite our best attempts to provide an alternative, a portfolio company was making a decision that challenged our values. We sought some advice from other VC friends but ultimately wanted to do something no one recommended: sell our shares back to the company at our cost, despite an in-process financing occurring at a higher valuation. We shared this decision with our LPAC and again, received nothing but support from the LPs.
Most of these have been ad hoc emails or phone calls, but we make sure to get our LPAC together each year as part of our AGM, usually in an informal lunch or discussion prior to the main presentation. They’ve been invaluable and we feel really fortunate to have a relationship that’s professionally oriented but also supported by care and personal affinity.
I’m a believer in the ‘software eats the world‘ thesis, although I often change it to ‘software enables the world,’ which is not nearly as evocative but also not as consumptive. One byproduct of this movement, especially during the blitzscaling era, were new startups in areas such as finance, healthcare, housing, education, using venture capital to acquire customers at accelerated rates. And when these startups failed, the customers might find themselves confronting situations where a product they relied upon ceased to exist with very little notice.
For the investors it’s of course a disappointing outcome, but the failure is built into their model and they knew going in that ‘taking a zero’ was a potential ending – that’s why they’re ‘accredited investors.’ For the human being who is your using your service, quite often they don’t have the same visibility or understanding of the risks – there’s no such hurdle to make sure someone is an ‘accredited consumer.’
In the B2C world, especially when the startup is serving a the bottom of Maslow’s pyramid, a flameout ca leave you without a home, a therapist, or your savings. Because to some people on the org chart and on the cap table it’s better to use the last $500,000 to take one last growth hack swing than to manage a wind down.
Which leads us to the fundamental difference between, say, a small self-funded online therapy practice and one that has taken millions of dollars in seed capital: the latter can acquire a larger number of patients much faster using investment dollars for both customer acquisition and to subsidize the economics of serving those clients. That’s what always gives me a little bit of pause in this particular area — the scale ahead of the sustainability
And some hopes,
Whether you’re the platform providing the therapy or the software powering the therapist, entrepreneurs in this area should have their own version of the Hippocratic Oath. What I’d ask the investors in these companies is that they share the same values. Push for responsible growth and make sure patients are well-served. Realize that when you look at stats that involve quality of customer interactions, drug prescriptions, etc you’re talking about real people, not just percentages. And perhaps most essential, have a plan for what happens if the company doesn’t succeed. What does client offboarding look like, how long would it take and how much would it cost?
This concept is top of mind for me because we are now seeing the potential for AI products to change the quality and economies of service for addiction and therapy once again. As a recent WSJ article highlights, “When There’s No School Counselor, There’s a Bot,” and one particular company trying to solve for a startling coverage gap in adolescent mental health
The hybrid chatbot is now available to more than 4,500 public middle and high school students in nine districts across the country, many of which are in low-income and rural areas where mental-health services are lacking. The American School Counselor Association recommends schools employ at least one counselor for every 250 students, but says the national average is one counselor for every 376 students. And 17% of high schools don’t have a counselor, according to the Education Department.
This is great! And if you’re founding, building, or funding any of these companies please please please know that you are taking on a responsibility, not just an opportunity. I toast to your success and your efficacy. But know that your customers aren’t taking ‘startup risk,’ they just want some help.
Screendoor has now looked at more than 1,500 venture firms raising funds, backing roughly 1.5% of them, often as their first or second largest investor. When I’m scanning a pitch deck I’m basically looking to put it into one of two buckets – Traditional or Different.
“Traditional But Better” means they are basically running a playbook which doesn’t appear too different from existing firms – sourcing companies in categories considered ‘venture scale,’ with a portfolio model that has consistent stage and ownership targets, and ‘value add’ that mirrors the language other firms might use. Of course Screendoor has an eye towards new VCs with identities, backgrounds and networks which are ADDITIVE to the venture ecosystem to better serve founders, so while the structure of the playbook is duplicative, the people running the playbook aren’t – and that’s the key. In these cases we’re asking ourselves, can this individual/partnership execute a ‘known’ playbook better than incumbents, because it’s not very interesting to put people in business who are going to be Traditional But Average. Mediocre VCs get wealthy themselves but they won’t make money for their LPs, and are, at best, just a WITHDRAWALS ATM for average startups.
“Different & Excellent” equates to something that doesn’t exactly look like other VCs. Could be pinning their thesis on a category of technology or type of founder that isn’t yet understood by the investment community. Or contrarian in the number of companies and/or dollars invested per company compared to their peers. Maybe even a strong POV on what value they can add that isn’t typically available to early stage founders. These firms aren’t carbon copies of anything else out there. In fact, they probably aren’t generally replicable. But they take advantage of their unique founding partners, very often the type of people who would reject – or not get hired by – ‘traditional VCs.’ Here we have to torture the models to really understand the quantitative sensitivities around expected performance. And how quickly the firm can process new information and adjust if portions of their hypothesis need tuning once in market. But we’re interested in taking this risk when the person and opportunity warrants it.
If you’re a VC raising your first fund, and you think you fit either of these descriptions, please let us know. I could even ask you directly which one of these you think you are and why.
First, a piece of literary history. The phrase needle in a haystack is commonly credited to the book Don Quixote from the early 1600s (“needle is a bottle of hay”) but there’s also a Fujian proverb “To dive into the sea, to feel for a needle” that is thought to be even older and gets to the same point. The idea that it’s nearly fruitless to blindly search for a single small object when it’s located in a vast container.
Ok, back to the VC content marketing.
A few years back I helped start Screendoor, a fund that backs new venture firms by hopefully being one of their earliest and largest supporters. As a result I’ve seen hundreds of VC decks, all certain they will be among the top performers. Most strategies are some combination of innovation and best practices along the classic five steps of venture investing: See, Pick, Win, Service, Exit. This post is about ‘seeing.’
In addition to hustle and one’s existing network, I’m always interested in whether or not a ‘needle magnet’ is being built alongside the other efforts to find startups. What’s my needle magnet definition? Some force that pulls exceptional startups to you, directly or via intermediaries, in a privileged and sustainable fashion. What are, in my mind, some examples of needle magnet strategies that exist today?
Content Marketing of all Forms: Social media presence, podcasts, blog posts, How To manuals
RunningWorkshops and Other Experiential Programs/Events: On leadership, finding PMF, pricing and GTM, hiring, and so on
Humans Outside of the Firm With Incentive to Source For You: Scout Networks are Like Distributed Mini Magnets and we see all sorts of version here. People who can invest with the firms money at arms length, bounties for sourcing a startup, small investments in other VCs that are upstream from your firm.
and related, of increasing importance.
Data: Turn the needle magnet into needle radar, by pinpointing the location of the needles.
So my general advice is as you’re building a firm, think about which magnets feel right to you and start investing in them early. You’ll also need to tune the magnet over time so that it pulls less detritus – or at least build a great sorting filter so that you can kindly decline/exclude other stuff which gets pulled in.
Don’t be afraid to experiment, don’t be afraid to try something new – unless you’re really excited about podcasting and have a novel idea on how to break through the noise, it’s not worth doing. Pick the magnet strategies which are consistent with your brand, stage, resources, and temperament.
There, some loose thoughts on magnets. Did I miss any categories?
Sometimes I write a post just to be able to send the URL to people when they ask me a specific question. This one is “what advice do you have for someone who is a new VC analyst or wants to join a firm at that level?”
If you’re joining a venture capital firm as a junior professional I’d recommend against being a generalist, or trying to get good at everything. Instead once you’ve gotten your bearings optimize on developing distinct super powers.
One super power that is in service of your GP. Assuming you’re working for a particular partner or a specific coverage team, pick something that is of great value to you partner and can be performed repeatedly. Maybe it’s around sourcing and depth within a particular network. Expertise in a technology platform. Or some data analysis competency. A tool you can build and maintain for the partnership. Something along the See, Pick, Win, Service, and Exit spectrum that creates value and is distinct from how any other person would approach the job.
The other super power should be in service of the founders you back. Pick something that is matched against the stage and markets you partner is investing in and just become the go-to person for the founders. Maybe you are just excellent at sourcing new grad engineering hires from your old school. Or running data analysis projects. Or whizbang at influencer marketing. It almost doesn’t matter what – it just needs to be high value, repeatable and welcome to come from the cap table (vs needs to live on the org chart).
Sure beyond these two items you will have responsibilities, and should have capacity, to spring into action for one-offs, or other jobs to be done. But I think a beachhead of value aligned against these two ‘customers’ will make you more valuable in specific ways and build your reputation versus just being ‘responsive’ and a ‘good guy.’
Of course YMMV – I’ve never hired or mentored a venture analyst – I’m just observing from my experiences working with founders and venture co-investors. Good luck!
Homebrew makes investments by consensus – it works because there’s just two of us. We’ve done it this way for two reasons – first, it works internally given our style of decision-making and respectful but loud debate. Second, it matters to us externally that founders know it’s always Homebrew making the investment – never a situation where one of us was excited and the other one didn’t block it. To that end, backing Regal, now a leader in AI Powered Calls for your businesses’ sales, support and operations, was quick to mutual agreement. Satya and I were excited by the vision and the cofounders’ previous work experience together. Since the world of AI is moving quite rapidly, I wanted to check in with Regal CEO Alex Levin to ask Five Questions.
Alex Levin: I remember studying the philosophy and psychology around consciousness in college and thinking I might pursue academia. One day I realized that I could study my topic for my whole career and never get to the end of what was already known. And at that moment, it was crystal clear to me that I had to find a career where I could get to the forefront of what was known more quickly so I could help contribute instead of feeling like I was always behind.
After graduation, I dove headfirst into tech startups as it was clear they were investing the future every day. I knew that one day I wanted to be an executive, or even the top executive. And I understood that if I didn’t know how the sausage was made—if I didn’t know how to build technology—I’d never be eligible for those top roles. So early in my career, I prioritized being close to engineering teams, teaching myself how to build software, and learning how to be a product manager.
When I came across Marc Andreessen’s article, “Why Software is Eating the World” in 2011, it felt like a vindication of the direction I had chosen, but I was already down that path.
I’ve experienced both large and small companies, and I’ve found that I thrive in early-stage environments. It’s like how they describe the professional leagues of any sport: “things move faster”. Also, there’s more opportunity, and you really feel like if you’re not there one day the project doesn’t move forward. I love that sense of accountability.
I’ve been fortunate to take on progressively senior roles, mostly on the commercial side, and experience scale, including reaching $1.5 billion in revenue at Angi. And now, I’ve taken everything I’ve learned and put it to the test by starting a company myself.
Looking ahead, I hope my story is one where I continue to take on challenging opportunities, create something where nothing existed before, and build companies that truly change their markets. And, ideally, not just once—but many times.
Regal’s cofounders Rebecca Greene and Alex Levin
HW:Similar to you, I started Homebrew with a former coworker. How did your relationship with Rebecca evolve and do you remember the ‘we’re going to do this!’ moment?
AL: While we were at Handy, Rebecca and I both had our first kids, and I distinctly remember talking about starting something together soon afterwards. We spent months having general conversations, but eventually, we sat down and did a “Founder Dating Quiz”. We went through a list of 20 to 30 key questions—things like our working styles, how big we wanted the company to be, what a good exit looked like, whether we wanted to raise money, what could go wrong, and what we were most worried about. After that, it really felt more real as we knew we were aligned.
It still took some time to land on Regal as the company we were going to start as we had two or three other ideas we seriously considered (which is a story for another time). But when we talked to potential Regal customers about our vision, and how we wanted to change the way companies engage with their customers, the response was overwhelming. People were pulling for it. And once we felt that “market fit”, we jumped in fast.
HW: Regal is an AI-driven company that was founded prior to the ChatGPT launch. How have the last few years accelerated the roadmap? How has it challenged the company?
AL: Coming from a background in product and marketing before Regal, Rebecca and I were used to great tools that could tap into data sources, personalize customer interactions and even apply machine learning—it wasn’t really AI back then—to do some pretty smart things. Meanwhile, in contact centers, teams were afraid to change anything in their software for fear it would all break, let alone try using data for personalization or machine learning. So we knew it would be a bit of an uphill battle to get contact centers to change.
From the very beginning in 2020 we had a vision of better business-customer interactions powered by customer data + ml/ai + software for teams to make changes easily. In 2020 the avant-garde AI was for assisting human agents, not autonomously handling tasks, but as we started building, we knew customer data and orchestration had to be at the core of our platform, hoping that one day, autonomous AI Agents could take over the customer conversation instead of a human.
For years, though, AI just wasn’t good enough. But we kept pushing on it because human agents cause issues because they have other motivations, weren’t always well-trained, could quit, or just have an off day. The public might assume humans are the gold standard, but anyone who has actually operated contact centers with human agents knows it’s actually really difficult, and there are plenty of challenges with human agents.
Then, about a year and a half ago, everything changed. LLMs finally reached a level where they could understand and generate language and make decisions similar to humans. And we got to a point that our AI agent demo completely opened our eyes as to what was possible. We started focusing on creating an “omni-agent” system, one where both AI and humans could operate seamlessly. Build the policies, scripts, orchestration, guardrails once, and deploy them to both human and AI agents.
A year and a half ago, not many companies were ready for AI. They worried about hallucinations, customer reception, and whether it would really work. But AI agents have advanced incredibly fast, and the platform we spent four years building to help human agents take the right action actually gave us the best-in-market platform to operate AI Agents and we now have a huge advantage over companies just starting to build AI agents from scratch. So we are seeing a seachange at consumer companies – everyone is evaluating AI Agents in 2025.
The best part of this shift is that it’s made our GTM simpler. To move human agents into Regal required ripping and replacing their current contact center software. Now when we sell Ai Agents, we roll out without touching their contact center software, accelerating the sales process and implementation.
HW: Content marketing dominates the venture industry these days, much of it about Artificial Intelligence. Since you’re down on the field with the actual companies buying these products, what’s something that we’re missing? Share an ‘earned insight’ that you have from the work at Regal?
AL: Rebecca and I are not naturally public people, so for years, we didn’t focus much on marketing. That was a mistake. With our newly built marketing team (who have strongly encouraged us to get on our game and step up), we are finally getting in front of more customers, and Rebecca and I are starting to embrace building in public.
One simple earned insight is about how to start testing AI Agents in production. Every company wants to start small. And most gravitate to small use cases (like out of hours) to test. I always advise against that as even if that succeeds, it won’t have a material impact on the company and you will need to start again with a larger use case. Instead, pick the largest use case for voice (like your main inbound or outbound calls) and test your AI Agent on 1% of calls to start. Then as it succeeds, scale up to have impact immediately.
HW: What’s your advice for founders who might be starting companies today in the general AI space – let’s focus on those who are using AI to solve problems for customers (applied AI) versus lower in the stack base models or deployment infra.
AL: Rebecca and I are founders and angel investors in the AI Voice space. You have to assume every company will have access to the same LLMs and voices. The challenge, then, is to build a company that thrives despite this reality. Said otherwise, build a “thick” workflow or application layer that will provide value no matter what the LLM and voices do.
So much of what Regal focuses on, and what we invest in as angels focuses on role-specific or industry specific workflow tools for generative AI to solve problems that LLMs alone cannot. For example, integrating AI into customer data systems, and enabling actions (like processing payments, updating CRMs, or sending SMS messages). Or ensuring AI stays within its intended scope, provides accurate information, and recognizes when it should say, “I don’t know.”
These challenges exist across industries and roles, and won’t be solved by LLMs alone.
Thanks Alex! To demo Regal, or learn more about their product, head to their website. And if you want to join a fast growing company that cares not just about what they’re building, but how they’re building it together as a team, well, Regal is hiring.
Podcasts are typically escapism for me, which is why I don’t listen to very many about tech or venture capital. Except The Learning Corner from Precursor, because I love Charles Hudson.
A few months back they were discussing Solo GPs and some ways their processes differ from larger partnerships. Prompted by a blog post from Ubiquity Ventures, Charles notes “the whole ‘I couldn’t get it through my partners,’ I’ve always found that to be a really unsatisfying thing to tell a founder,” for reasons of intellectual honesty, competency and/or agency.
CHARLES WE ARE SINGING FROM THE SAME HYMNAL MY FRIEND. Here’s the post I wrote a while back about the same topic.
So, if you’re raising from a multipartner VC firm, as most are, you should always:
I. Understand the decision making process at the firm
II. Use your lead partner to help you understand the firm’s general sentiment towards deals like yours (partnerships have long histories and they will/won’t like deals because it reminds them of successes/failures in the past)
III. Help your lead partner with their partners. You want as many advocates in the partner meeting as possible. Work with, but not around, your lead partner to ID backchannel references you can be providing, etc
And always enroll any current investors to help you navigate this – Homebrew can help 🙂
