“Humans are innately driven to take the adventurous, longer route. Our distinct traits of creativity, innovation, and uphill thinking compel us to explore the unseen, unheard, and untouched, even when it's seen as rationally “wrong” by conventional standards.

This shared spirit, found in entrepreneurs, athletes, and artists alike, is demonstrated in our history of remarkable art, groundbreaking discoveries, and revolutionary innovations. This willingness to embrace challenges, endure setbacks, and choose “longcuts” over shortcuts underscores our unique capacity for uphill thinking.

Even as AI excels at efficiently executing repetitive tasks, it remains rightfully constrained by our design for safety and lower risks, making it less suited for the daringly imaginative and transformative tasks that creatives undertake. This courage to venture in unconventional directions, to bet the farm on an irrational path, is what differentiates us from today’s AI.

The uphill thinking that may seem suboptimal in an AI-centric view is, in essence, the core of human creativity.”

The truth is, AI is just a tool. It’s a drill instead of a screwdriver.

Over the next decade, the way we work may change, but why we work will not. We will still continue to trudge up hills, searching for the next breakthrough.

Happy weekend,

Raman at Rhetoric

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📚 What’s made me a better storyteller this week

Andrew Chen recently shared a framework to think through career decisions: The Next Next Job. It’s a great read and a simple framework:

TLDR: Ignore this next job you’re considering for a second. What do you want to do after that job (your “next-next” job)? What are the gaps between today and this next-next job? Now look at the options you’re considering for this upcoming job. Which of them will best set you up for your next-next job?

This makes sense. Companies do this exercise all the time (five-year plans, path to $100M in revenue, OKRs, north stars, etc.). However, as someone who has spent countless hours building growth forecasts at these companies, I can assure you that there is more “hand waving” than “data science” involved. We smirk at each other as we draw lines “up and to the right”.

However, unless you know exactly what your dream next-next job is, this exercise really just exists to scratch an anxiety itch. It doesn’t leave much room for the most important variable: spontaneity. When I look at my own career (psychology major, finance internships, marketing analytics consulting, data science at a fast-growing startup, to ultimately launching my own startup), I’m humbled by how little I purposefully orchestrated.

I could tell you that my psychology classes and finance internships during undergrad made me interested in the analytical side of user behavior. This is why I took a job in marketing analytics consulting, where I developed a technical skillset in data analysis tooling and coding. After two years of consulting, I knew I wanted to stop “consulting” and start “building”, which is why I joined the data team Lyft focused on growth. Lyft opened my eyes to the world of building successful products, which is the experience I wanted to go out, fundraise, and start my own startup.

Sounds legit, right? In reality, each and every career step felt like walking into the unknown. Sure, like most of us Type-A control freaks, I hate the unknown and attempt to plan out my next-next-next-next-next job and work backward it.

It feels wrong to talk about career planning (or any planning, really) without appreciating the role of spontaneity. Focusing on the inputs (working hard, facing challenges head-on, gracefully failing every now and then), may be a better exercise than only trying to define the outputs.

Let’s not forget the advice from the ultimate control freak, Steve Jobs:

“You can't connect the dots looking forward; you can only connect them looking backward. So you have to trust that the dots will somehow connect in your future. You have to trust in something - your gut, destiny, life, karma, whatever.”

Happy weekend,

Raman at Rhetoric

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📚 What’s made me a better storyteller this week

There are the usual suspects of soft skills: communication, executive presence, empathy, teamwork, etc, etc., but one that I think I’ve come to appreciate more than ever before is the ability to ask really good questions.

It’s a skill prioritized by journalists, sales teams, founders, and user researchers, but seemingly under-prioritized by the average knowledge worker. If you don’t (yet) appreciate the power of good questions, go learn from the master: Ezra Klein.

As I work on this skill, I’ve come across three questions that I’ve found to be especially impactful:

What haven’t I ask you about that I should have?

Ending a user interview with this question has led to some fascinating responses. After 25 minutes of pointed questions in a user interview, this “catch-all” question opens up the conversation and gives the interviewee the chance to express what is really top of mind for them. You’ll almost always learn something interesting.

What are you feeling?

You may have heard this one before. The question of “How are you?” has become so common and expected that our partner in conversation will almost always unconsciously respond with a lie: “Good”. A small change in wording from “How” to “What” prevents the interviewee from giving a canned response. The question is unique, and therefore their answer will be as well.

Using the inverse. What does your team do really well? What does you team do poorly?

Anchoring is powerful. If you ask someone what their team does very well, they’ll be quick to give you a detailed response with pride. If you then follow that question with the inverse, they will feel the need to provide an response that is equal and opposite in nature. They’ll really dig to figure out what their team does poorly.

What are your favorite

Happy weekend,

Raman at Rhetoric

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📚 What’s made me a better storyteller this week

The “art” of building a startup is not only business and technical acumen, but also creativity. Those who study and teach creativity define it as the process that forms something new and valuable. Sounds a whole lot like startup building if you ask me. Regardless of industry - from viral consumer apps to data pipelines - founders must be creative.

I thought about this while flipping through Rick Rubin’s book on creativity: The Creative Act: A Way of Being. Because I’ve been living and breathing this startup world for the past couple of years, I naturally digested the book from the lens of the founder's journey. There were three particular quotes in the “rules” chapter that particularly resonated:

“Limiting your palette to something manageable forces you to solve something in a different way.”

By design, startups are constrained by capital, resources, and distribution. It is these constraints that force startups to focus on delivering incredible value to users (or else, die).

“Rules direct us to average behaviors. If we’re aiming to create works that are exceptional, most rules don’t apply. Average is nothing to aspire to. The goal is not to fit in. If anything, it’s to amplify the differences, what doesn’t fit, the special characteristics unique to how you see the world. Instead of sounding like others, value your own voice. Develop it. Cherish it.”

Startups can’t just copy the incumbents. They have to offer a fundamentally different future and, as Mike Maples would put it, “bend the arc of the present to that different future.”

“The rules artists learn are different. They are assumptions, not absolutes. They describe a goal or method for short-term or long-term results. They are there to be tested. And they are only of value as long as they are helpful. They are not laws of nature.”

If Uber, Lyft, and Airbnb adhered to the rules of their environment, they would have never come to fruition and we would still be hailing taxis and booking expensive hotel rooms.

Happy weekend,

Raman at Rhetoric

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📚 What’s made me a better storyteller this week

Customer pain tends to evolve with time. It usually starts as a latent pain: the customer is blissfully unaware of their problem. However, with time, the problem eventually starts to nag at them and they realize that it is, in fact, an issue that they could deal with but, as usual, (1) who's got the time, and (2) is it really worth prioritizing right now? It’s now a passive pain point. But, then, a critical event occurs and the pain point becomes urgent. It could be a big enterprise sale opportunity blocked by a SOC-2 compliance need, a product outage, or as simple as your customer walking out of a meeting in which their CEO demanded new quarterly targets (e.g., we need a financial planning software as-soon-as-freaking-possible).

The key trait of a critical event is that it has a due date and there is a consequence if the customer misses that date. The prospect may say something along the lines of “I need to be SOC-2 compliant by the end of the month” or “I need this planning software by the end of the week.” The WBD team offers the following advice to identify (a) if there is a critical event and if so (b) what the critical event is:

The first question to ask is “When do you need this solution in place?”. Follow it up with “...and what happens if you miss that date?”

This simple question will let you know if the event is “compelling” or “critical.” After the prospect shares the critical event and the consequences of missing it, you can ask, “If you need to have this live by {date} to get {impact} or otherwise face {consequence}… how can we help you avoid that?”

As you can imagine, if you build a product that solves a common critical event (think Vanta, who casually onboards 600+ companies per quarter), you’re going to do pretty well. Here’s the thing, though. You’re probably building a B2B product that has plenty of prospects with “compelling” events, but very few/rare “critical” events. Collecting only “compelling” events doesn’t mean that you’re doomed for failure. I’m sure you can think of plenty of successful companies that don’t fit the “urgent user pain-point” mold. Realistically, not having a critical event simply means you’ll just need to gear up for a longer, more complex, sales cycle or lean into PLG / freemium motions that allow “curious” users to trial your product and find a magical moment.

What critical events have you seen recently? I’d love to compile a list of realistic examples to share more broadly.

Happy weekend,

Raman at Rhetoric

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📚 What’s made me a better storyteller this week

Anywho, to be honest, we’ve all been waiting for this, right? No-code website builders are incredibly powerful, but giving users the ability to infinitely customize means dense UXs that require joining a university to learn and navigate the product. This is a perfect use case for natural language prompts: instead of endless pointing/clicking and searching for certain components, I can just type out a request and be amazed.

To manage the difficult onboarding before GenAI, these platforms launched marketplaces of templates, specifically targeting the “ballers on a budget” who can’t (and won’t) drop $10k but still want a professional-looking website. While the templates were far from perfect, they got the user 60(ish)% of the way to the finish line. Moreover, they created an ecosystem of experts on their platforms that could develop endless variations of content ideal for the endless needs of their users.

The problem with templates is, of course, they’re templates. They’re average. Your story, brand, and platform now look legitimate, but it probably definitely doesn’t stand out. Your users likely aren’t having a religious experience on your website. However, the good news is that because of the template, you no longer have a bad website. You’ve been promoted to an “average” website! And that’s progress.

If Wix’s “coming soon” AI features end up anywhere close to the experience they demoed, then this is a huge success for the entire GenAI community and, more specifically, those bullish about the user experience of “natural language commands” to power an interface. Similar to what we’ve seen with Adobe Firefly, this reinforces the potential to improve all of the other complex no-code design experiences in our day-to-day: GSheets (think building a visualization), GSlides (hi, Tome), Figma (hi, Diagram), and so many more.

However, let’s be real: these products won’t be “fully autonomous” for at least another few years. These new AI features (1) enhance the template ecosystem by not needing to rely on experts to create everything and (2) make trialing the product easier. The underlying function of the tool has not changed. We’ll still likely need to get our hands dirty with endless point-and-clicks and custom code to solve edge cases, but it’s still progress.

Making complicated design tools easier to use means the digital world will look better / sleeker / more beautiful. I’m all for that, and it’s cool to see the future being pulled into the present by these incredible companies. In the long run, our entire definition of quality will change: as other platforms launch their own AI features, the quality we expect out of any given website will simply be higher.

Except Craigslist of course. I hope they never change.

Happy weekend,

Raman at Rhetoric

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📚 What’s made me a better storyteller this week

It’s still crazy to think about: every aspect of my job that I described above could look different because of LLMs and generative models. The promise is an inflection in productivity, which as I’ve discussed before, means smaller teams, more impact.

It seems like every week we learn a little more about where the value will accrue. Building a wrapper on top of OpenAI has no moat. There will be many LLMs (not just OpenAI, Bard, etc.) that are competing for niche use cases. The chat UX is promising for some things, but may not be the ultimate game changer for everything. AI agents are super cool and Langchain is sweet. These models are really-freaking-good at creative functions (generating copy, images, ideas, brainstorms) and analyzing insane amounts of text (legal, search 2.0, research). But, they’re sometimes bad at things like addition and subtraction. Hallucinations are tricky to solve. They make small mistakes every now and then.

While the Twitter-verse gushes it’s excitement on the above, I’m not seeing many people that can provide a reasonable answer to “when” my AI co-pilots will actually join my team and drive value. There are plenty of technical challenges (both hardware and software) that create a wide confidence interval, but one that I think is not talked about enough is trust.

A long-long time ago (2017-ish) at Lyft, the company went big on autonomous driving. Because of some incredible technical advancements in the prior year, it was time to start really betting on it. In addition to acquisitions and venture capital raises, long-term company north stars were added that were along the lines of “X% of rides will be autonomous by 2020”.

You all know the story. Autonomous gets snagged on the “last mile” of technical challenges. Regulation is a lot more dicey than we thought. 2020 comes and goes and autonomous is demoted back to a crazy cool upcoming technology.

Luckily, GenAI is very different than the rollout of autonomous cars, but a big learning from the self-driving journey is that we hold technology to a really high bar. Like, absolute perfection. Road crashes are the leading cause of death for young people in the United States. You would think that if we could reduce these crashes by >10%, we would act on it as soon as possible (saving tens of thousands of lives each year). Autonomous promised safer roads, but because it is not perfect, we don’t trust it enough to roll it out at scale. It remained a “cool” technology instead of getting promoted to a “useful” technology. We give humans room for error, but not technology. The team at Cruise took out a full-page ad in the New York Times earlier this week, arguing that it was (finally) time to fully embrace self-driving cars as safer.

I’m curious if this same concept will end up dragging out when GenAI co-pilots actually make an impact. Does my AI co-pilot need to be perfect for me to integrate it into my work? I need to trust that it will help me find the bug in a feature and not miss anything, that my email sequences will execute correctly, and that my landing page copy is better than what I could spin up. These models will do very well in the creative space where there is no such thing as perfection. But, when it comes to data analysis or workflow execution, I get nervous about if we’ll see it get past a “cool” technology with crazy potential in the next few years.

Luckily, unlike autonomous, we can incrementally roll out generative analysis and workflows that automate the most simple and straightforward experiences. Co-pilots are starting as “QA-assistants” to your code rather than writing your entire micro-service. This ability to incrementally release and quickly improve is the powerful advantage of software over hardware and why the rate of change is so much faster. But, this does not change the fact that anyone who is trying to automate a human process needs to make sure that they keep their bar of quality really high and aim for perfection. Trial users are easy to come by while the AI hype is at its peak, but as we hit the inevitable trough of disillusionment, we may see design partners and curiosity usage decline. Keep pushing though, because I really need these co-pilots.

Happy weekend,

Raman at Rhetoric

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📚 What’s made me a better storyteller this week

I’ve always been fascinated with early onboarding experiences. How long does it take a user to find value? How much friction does the user need to wade through? At Lyft, the driver onboarding process was tedious and time-consuming: it required an upfront investment in sharing personal information and vehicle information, going through inspections and background checks, and then waiting a handful of days to be approved. As you can imagine, most prospective drivers that showed interest from an advertisement or referral did not end up becoming drivers. They got lost in the build-up of the story.

Your product’s narrative arc can be broken into the same components as any story:

• exposition: set up, background information, character introduction (submitting all the driver and vehicle information mentioned above)

• rising action: the introduction of incredible value for the user (realizing how much money you can make as a Lyft driver)

• climax: the magical product moment that brings your user joy (your first payout!)

• falling action: finding comfort in your product (integrating driving into their weekly schedule and retaining)

The less exposition and rising action your product needs, the sooner you can hook the user. Onboarding drivers at Lyft is long and tedious. It required a large team of PMs, designers, marketers, local operations managers, and engineers to really optimize this flow and get users to the magical product moment. On the other hand, AI tools like ChatGPT, Midjourney, DALLE, and have little exposition and rising action (just write a prompt!) and can bring the magical moment to the user in seconds. This is what enables their insane user growth. Their focus will need to be on the falling action where users build expertise and comfort in the product and retain.

Interested in optimizing these narrative arcs in your product? Look no further than Ben William’s newsletter, PLGeek.

Happy weekend,

Raman at Rhetoric

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📚 What’s made me a better storyteller this week

A skill that I had never really thought about (or appreciated) until I dove headfirst into startup land is "the ability to rapidly fail”. Anyone can just fail, but being able to rapidly and confidently fail is an amazing trait for founders who are hunting for PMF.

It’s counterintuitive for those coming from established companies where you are primarily nurturing an existing fire rather than trying to spark a flame. Most companies stop rewarding rapid failure after reaching a certain scale, and therefore, rapidly falling is an uncomfortable concept.

The founders who are good at this assume they are wrong by default and lean into user research and customer conversations as their north star. They close doors quickly so they can find the right door to open. They also make smart failure bets: focusing on ones that are inexpensive, fast, and have high learning potential. And, maybe most important, they are rarely discouraged by these micro-failures and instead see them as progress.

Happy weekend,

Raman at Rhetoric

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📚 What’s made me a better storyteller this week

Assuming you’re able to prevent yourself from immediately solution-ing, you (unbiasedly) investigate further. You learn more about the experience and then pry some more: “How do you try and make this better today? What band-aids exist?”.

This is a critical juncture because you’re about to learn about the type of pain point in front of you. Turns out, not all pain points are equal. The Jay-Z of customer development, Steve Blank, breaks customer problems into a few different categories:

1. a latent problem exists, but they are unaware of it (or ignorant of it)

2. a passive problem exists, but they aren’t motivated to change it (it’s whatever)

3. an urgent problem exists, and they are actively trying to figure out how to solve it

If we’re being honest during our user interviews, we should respect that everyone has a lot of latent problems, plenty of passive problems, and very, very, VERY few urgent problems. A good health check is to make sure your collection of pain points reflects this distribution.

Happy weekend,

Raman at Rhetoric

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📚 What’s made me a better storyteller this week

Anyway, when Adam Robinson and Shane Parrish jammed on chess and positioning last week, I was naturally all ears:

“Chess is an amazing game that I love. One thing is to be aware of positions that you excel in. I’ll steer the game as much as I can from the very opening to positions that are of my liking. So, it’s important that each one of us has an awareness of the positions that they excel in and steer the game — or their life — to those situtations.”

What I love about this idea is that it applies to just about everything: from running basketball plays (pass it to Steph Curry) to finding a dream job to executing a go-to-market strategy. Having unique strengths as a founder, investor, or leader is useless unless you’re able to deploy them at the right time and in the right place.

Founders only have a handful of shots on goals; before committing to writing a line of code, make sure your position is strong. As James Cham likes to say, “Be a heat-seeking missile”.

Happy weekend,

Raman at Rhetoric

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📚 What’s made me a better storyteller this week

On my bike ride home from the office earlier this week, I thought about the percentage of my startup stress/anxiety that is externally delivered (a bad sales call, product issues, delayed roadmaps, etc.) versus internally manufactured (WTF are we doing, will this ever work, can I do this, etc.). Basically, a mental health metrics tree.

I was thinking about this after reading Scott Belsky’s latest book, The Messy Middle, over the weekend. The book is a deep dive into the part of a growth journey that no one talks about: the middle. The middle is what comes after the “joy” of the start has receded into a distant memory. It’s a long-dark period (years!) that is an onslaught of both external and internal anxiety. It lasts until the relief of the end finally comes to light.

Scott’s recounting his own “messy middle” experience with Behance will have you nodding along the entire way. There is nothing unique or special about these stresses: every founder will face them. Like most things, it’s less about what is thrown at us and more about how we handle it.

While the entire book is a must-read, one passage that quotes Justin Fried of Basecamp especially changed my thinking: “The best startups are really just ‘stay ups’. Outlasting is one of the best competitive moves you can make.”

Bear with me because I can’t help but turn this into a sports analogy near and dear to my heart: In tennis, there is a special type of opponent known as a “pusher”. These are players that just refuse to miss. They don’t chase the instant gratification of a big forehand ripped down the line for a winner. They are relentless and run down every ball. Regardless of how hard you hit it or where you place it, they will get it back over the net. They are annoying as hell.

Yet, they win. Being a “pusher” may not look glorious, but it is exactly the type of play that is necessary in a marathon match in which all of the odds are stacked against you.

I’m deep in my “messy middle” as I’m sure you are too. I guess we’ve just got to keep on swinging.

Happy weekend,

Raman at Rhetoric

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📚 What’s made me a better storyteller this week

Instead of attempting to summarize their learnings and regurgitate their advice, I’d rather focus on a fleeting comment from the conversation with Andy. While talking about the process, he mentioned the importance of embracing and appreciating the “shit first draft” of a story. This comes from an idea shared by Anne Lamott in Bird by Bird:

For me and most of the other writers I know, writing is not rapturous. In fact, the only way I can get anything written at all is to write really, really shitty first drafts.

…

Almost all good writing begins with terrible first efforts. You need to start somewhere. Start by getting something -- anything -- down on paper. A friend of mine says that the first draft is the down draft -- you just get it down. The second draft is the up draft -- you fix it up. You try to say what you have to say more accurately. And the third draft is the dental draft, where you check every tooth, to see if it's loose or cramped or decayed, or even, God help us, healthy.
-Anne Lamott, Bird by Bird

If this resonates with you, it’s because, once upon a time, you found yourself staring blankly at your laptop screen trying to get through a first draft of a pitch deck, company presentation, or even a simple email. After countless false starts, you finally put together a shit first draft. While it may not have felt good, it was the exact point at which everything started to turn up and to the right.

While absorbing Nancy and Andy’s teachings are absolutely important, it’s equally as important to remember that a good story starts as a bad story. It just takes some poking and prodding.

Happy weekend,

Raman at Rhetoric

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📚 What’s made me a better storyteller this week

Earlier this week, I met with one of those incredibly generous founders who do their best to tell you about all of their early mistakes so that you can bypass them and move faster.

As a product person (and first-time founder), one of my (many) weaknesses is jumping too quickly into ideating features, growth hacks, and interfaces. I err towards solution-ing: I take a small nugget of feedback from a user, fill in the gaps with assumptions and biases from my own experience, and then confidently put forward a plan.

In other words: I’m throwing on a blindfold, picking up a dart, and “yolo-ing” it in the direction of where I think the dartboard is. This rarely goes well.

The founder’s advice to me was simple: think about customer development as merely “story collection”.

“What sucked for you last week?”. “How can you prevent that?”

Imagine that you are publishing your own version of Humans in New York that’s focused on a specific type of role or customer. Note that the author of HNY, Brandon Stanton, never adds his own thoughts, candor, or opinons to a post about someone. It’s just their story.

The hard part about this process is letting go of our analytical muscle and just listening. Collect enough of these truly unbiased stories, and what they need (or more likely, don’t need) will become clear. Huge thanks to Hiten for the guidance.

Happy weekend,

Raman at Rhetoric

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📚 What’s made me a better storyteller this week

One concept I love (and is credited to Ernest Hemingway) is called the Six Word Story. In just six words, how would you tell an entire story? This is not easy and is eerily similar to those difficult moments when you need to distill your life story to 90 seconds during an interview.

Refining this takes work. Every word needs to be meticulously selected, adjusted, and then replaced. It forces you to prioritize your story based on your audience. The goal is that the six words are the tip of the iceberg - the audience realizes that there is much more depth and is left wanting to hear more. I highly recommend taking 10 minutes and writing out a few of these. And if you’re proud of what you pulled together, share it with NPR.

Related to this, we’ve been playing around with a cool concept for Rhetoric around interview preparation. Interested in hearing more? We’d love to have you alpha-test it.

Happy weekend,

Raman at Rhetoric

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📚 What’s made me a better storyteller this week

What made these people more impactful than the average was not that they had the latest growth, product, or experimentation numbers at their fingertips. Looking at day-over-day changes in a dashboard is usually not that interesting. However, by looking at dashboards over and over and over again, they started to build an implicit intuition of why metrics were moving. They started to understand (and respect) the relationship between metrics, the various business levers that made KPIs move, and the extent to which a business lever could affect a metric. Put differently, they understood the interworkings of the business better than most, and therefore, they knew where to focus and why.

This week, I watched Abhi Sivasailam’s talk at Data Council 2023 on Designing & Building Metrics Trees. Metrics trees are an incredibly simple, yet powerful concept that can be applied to any and every business model. What are your top-line KPIs? How do you solve for it? (e.g., ARR = leads * win rate * ACV). The leaders that spent time in dashboards were strengthening their understanding of the business by building a mental metric model. They understood how their OKR fit into the larger business and the importance of it.

Most founders at the seed stage that I chat/consult with think that it’s far too early to spin up dashboards and start consuming metrics. Sure, at the pre-PMF stage your growth metrics may not move much. Early-stage growth is definitely more of an art than a science. However, as Abhi argues, your business is not a snowflake and you should have a clear understanding of how your business can/could grow. At the very least, you will see your business as less of a complex system and more of a simple math problem.

Happy weekend,

Raman at Rhetoric

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📚 What’s made me a better storyteller this week

I’ve found that I constantly oscillate on a confidence spectrum of I can’t, I could, or I can. I’m sure most of you early-stage founders have felt the darkness of the “I can’t” moments: the ones in which you’re asking yourself why you left a stable job and believed that you could build something from scratch.

But, at some point, before that darkness, was a dawn in which you believed that you could build a company. You could make it work. That feeling of “being able” did not stem from runaway overconfidence, but instead quietly emerged from hope, curiosity, and excitement. It may have been built on a unique insight about a market or a technology breakthrough.

Believing that you could still does not mean that you can or will be able to do it (only time will tell). In startup-land, we’re all underdogs to the incumbent players and the countless variables against us. So, next time you feel that moment of “I can’t” creeping in, remind yourself that all an underdog needs is the belief that they could make it work.

Happy weekend,

Raman at Rhetoric

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📚 What’s made me a better storyteller this week

Let’s take the most common first-time founder mistake: focusing too much on “building a solution” (product) instead of “solving a pain point” (market). You’ve likely already read or heard advice about the importance of honest customer discovery and pain point analysis. I’m sure it all made complete sense to you. Yet, countless founders (myself included) still fall for the common trap of making too many assumptions about market demand or the severity of a pain-point. Instead, we build a vitamin that never scales.

Respecting knowledge oftentimes comes from making mistakes and accumulating scars. Jack Altman tweeted some common mistakes that first-time founders make. I’m sure that as you skim through them, they will all make perfect sense. You’ll understand them, but will you respect them?

Happy weekend,

Raman at Rhetoric

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📚 What’s made me a better storyteller this week

Mike describes early-stage startups as “jazz bands”. They are a group of talented individuals, without a playbook. They don’t follow sheet music, because there is no sheet music to follow: they are creating something completely novel. Take the other side of the coin: large companies hire project and program managers and implement countless processes en route to becoming what Mike describes as “marching bands”. These bands follow strict musical sheets and hope to sound the same every time.

I thought about this earlier this week while chatting with an investor about hiring and then again after reading Anu Atluru’s take: The Rise of the Silicon Valley Small Business. As venture fundraising tightens, it’s increasingly more difficult for founders to hire new accompaniments.

Leaning into Mike’s analogy, while today’s startups may be more inclined to stay small and nimble, the good news is that the instruments we’re playing are fundamentally changing. I think that’s the most exciting part of this generative AI boom: we’re all becoming DJs working on mixing boards that can play an infinite number of sounds. We can generate copy and creative content faster, build targeting lists, spin up landing pages, and maybe even Auto-GPT our GTM. Instagram was acquired for $1B with only thirteen employees - tomorrow’s unicorns could be even smaller.

Anywho, here’s a link to Fred Again’s Tiny Desk performance to bring the point home. Enjoy.

Happy weekend,

Raman at Rhetoric

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📚 What’s made me a better storyteller this week

Last week, I chatted about how difficult it can be to navigate which SaaS tools to buy and how our choices will only multiply in the coming years. Founders and leaders also must consider if they should build instead of buy. The preference, for many technology companies, is to build internally. This offers customizability and cost savings, but also layers on complexity, roadmap tradeoffs, and countless potential headaches down the road. If it’s not part of your core product and will be a distraction to engineers, buying may make a lot of sense. Further, if your team does not have expertise in this space (e.g., non-data engineers) then buying may make even more sense. Regardless of the decision, the goal is to be a mountain bike.

We found that with any startup we advised or any meetup we attended, the conversation almost always landed at: “What tools do you use?”. Given our backgrounds in the data space, we had strong opinions. We love chatting with startups about this, so we decided to formalize our knowledge with this survey tool: What Data Stack?

We ask a series of exploratory questions before writing up a short diagnosis of the data stack that fits your needs and sharing it with you. Our goal is to help you select the best product analytics, ETL, warehouse, and transformation tools that minimize monthly SaaS cost. In many cases, we may recommend no tools and instead a series of hacks to get the job done. Check it out!

Happy weekend,

Raman at Rhetoric

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📚 What’s made me a better storyteller this week