This incident reminds me of a mental model I have learned & developed with experience over my career:
“When you come across something that looks stupidly irrational on the surface, instead of falling prey to first-order thinking, pause, take a step back, try putting yourself in that situation and think through some reasons why someone could indulge in that seemingly foolish or irrational behavior?”
In the case of this billboard, clearly the founders are smart enough & shrewd enough that institutional investors are handing them $25Mn. So it’s highly likely that they are trying to achieve some goal by putting up this cringeworthy sign.
Most likely, the goal was to drive awareness & word-of-mouth by making this meme-worthy. Similar to how celebrities say & do crazy, PR-worthy things strategically close to a big movie release.
While this billboard case is a bit frivolous, it highlights an important idea that we all should have in our mesh of mental models – when something doesn’t add up in plain sight, or when the herd has 100% consensus on an idea, it shouldn’t be believed prima facie. Rather, it deserves an even deeper investigation.
The crowd is largely a blob of first-order thinkers. Value almost always resides in second-order thinking & beyond. Train your cognitive radar to spot these signals & act accordingly!
Sharing some insights/patterns from various co-founder breakups I have witnessed over the years.
Recently, I received the sad news of a potentially powerful co-founding team breaking up rather acrimoniously. I had been tracking this team closely for several months now as a potential deal, and this happened right as the company received a seed term sheet from a Tier 1 VC.
Over a 15-year career in venture, I have expectedly seen several co-founder breakups, both in my own portfolio as well as those I have known well/ observed from the sidelines. This recent breakup got me thinking about any patterns/ insights I have noticed over several such instances over the years. Here are a few:
1/ Undergrad batchmates seem to have higher endurance
For some reason, I have repeatedly noticed that teams where the co-founders have been undergrad batchmates tend to survive much longer. Perhaps relationships born in those fledgling, relatively innocent years tend to have higher levels of subconscious trust and, more importantly, a sense of love and tolerance.
While it’s easier to find people with complementary skills and similar pedigrees (both of which look great on paper on the team slide), what keeps co-founders together is also what keeps people together in long-term marriages – having an underlying mutual respect & fondness, which leads to daily hours of fun as well as the willingness to both extend higher levels of tolerance to each other, as well as introspect and evolve to meet the other person midway.
Especially at the seed stage, company missions can evolve with pivots, but this mutual vibe is what keeps co-founders together across multiple iterations and often, multiple companies.
2/ Ex-colleagues and work friends seem to have a higher risk
My hypothesis here is that most people tend to put on a work personality at the job that suits their manager’s preferences as well as the company’s culture. Therefore, even after working with someone as a colleague, it’s very hard to know their real, full personality and values. In many cases, people end up misjudging mutual fit, especially when it comes under the immense pressure of doing a 0-to-1 startup.
Interestingly, this applies to colleagues at both large companies as well as startups. As an investor, I often hear pitches where founders say, “We worked together in the trenches of this early-stage startup and discovered this idea”. While this gives the impression of a strong set of founders germinating inside the cauldron of another startup, I have frequently seen such teams breaking up soon. While they do have the claimed early product and GTM skills they together learned at the startup, the mutual co-founder vibe & grit end up breaking under pressure.
3/ Co-founders coming together via common friends/ relatives, without a strong shared history, is a miss
I see this scenario a lot – one person decides to start up, spreads the word around for a co-founder, connects with someone via a really strong common friend/ relative, and both decide to partner.
In the majority of these cases, there is no shared history, and the team also hasn’t had the opportunity to spend enough time in the trenches going through the ups and downs together. When pitching to seed investors, they usually tell the story of “our skills are perfectly complementary, and both of us have met each other multiple times at this X/Y/Z person’s parties over several years, and developed a shared passion for this idea”.
In most cases, this ends up being a window-dressed story of the co-founding team and lacks the underlying bond & trust needed to grind out the tough times.
4/ “Earned co-founders” are solid
In many cases, folks start as single founders, surround themselves with early founding team members, validate, iterate, and get to early PMF with them, and during this journey, 1-3 people naturally come up and start playing a critical role in the management team. In a sense, they start playing the co-founder role without the title (or the equity).
I call these earned co-founders, and these are solid personas. In many of these cases, I have pushed the solo founder to look at these 1-3 people as core parts of the leadership team, if not as full co-founders, and have it also reflect in their equity at the appropriate time.
During my recent India trip, a question I got asked repeatedly by both founders & investors was, “What are you seeing as the main differences between the AI ecosystem in the Valley vs India?”.
I currently see 2 main differences:
1/ Exposure (& therefore, Ambition)
AI founders in the Valley seem to have significantly more direct exposure to the work happening at the frontier. And not just in terms of the foundational technology, but also what battles the incumbents are taking on, how workflows are being iterated on, what lean, full-stack startup teams are doing to be able to generate significant product velocity & revenue, and how customers are thinking & allocating resources.
Essentially, they have the advantage of directly drinking from the Bay Area fountain of knowledge & information, spread primarily via networks.
A direct consequence of more exposure is that it uplevels the ambition of Valley AI founders and organically pushes them to raise the bar for execution within the company. Thus leading to sharper thinking, more courageous bets, and faster execution that all put together, improves the odds of a large outcome.
2/ Story-telling
I see that while AI founders in both the Valley and India are picking very similar problem statements to work on, the storytelling around the same use cases in the Valley is significantly superior.
I guess one reason is that operating directly in the target market (vs being a few degrees of freedom away from it) makes it much easier to get higher-quality early validation signals, making the story much more believable.
Also, AI founders in the Valley tend to emerge from the leading-edge companies of the last mobile/ cloud/ SaaS cycles. So they have a much better intuitive understanding of how to position & message the company in the early days to customers, investors & key hires.
Story-telling becomes even more important as how the AI landscape will evolve in specific market segments & verticals remains highly fuzzy.
So, what can India-based AI founders do to bridge these 2 gaps? Here are a few actionable things:
1/ Do extended sprints in the Bay Area regularly to drink from the same fountain.
2/ Surround yourself with Bay Area-based operators, angels & advisors (even remote is ok to begin with) who can regularly feed this knowledge & intel and, more importantly, help uplevel your thinking & ambition.
3/ Follow a conscious 0-to-1 strategy of only building for US design partners, so your product is held to the same bar as those from Valley startups.
4/ Specific suggestion for VCs – mine your network of LPs, Advisors & Portcos to hold regular AI knowledge sharing sessions with leaders of marquee AI-native companies that are building on the frontier in the Bay Area.
From recording many episodes of An Operator’s Blog on US-India GTM, one clear pattern is emerging from the experiences of many founders:
“If you are new to the US, don’t have a strong brand and/or connections to existing cliques (eg. haven’t done your Masters here, haven’t worked a Big Tech job, haven’t done YC etc.), cold outbound is likely to have a low success rate, especially in the initial phases of US GTM.”
Cold outbound tends to work better when done on the back of adequate customer validation, social proofing & ecosystem reputation, all of which take time to build.
Rather than depending too much on cold outbound, a better use of time when on the ground in the US is to:
1/ Build 1:1 ecosystem-level relationships with influential/ connected founders, operators, and investors.
2/ As you meet each person, try and get some warm intros. That’s your best shot at getting a relevant 30-minute meeting where the other side is leaning in.
Meet → Ask for one intro → Meet this new person → Again ask for another intro → Rinse & repeat…
3/ In parallel, execute an ongoing track of building your early reputation in the US (Bay Area?) ecosystem via social media content, engaging in relevant communities, regularly showing up in VC mixers & meetups, and generating value for the people you are meeting.
The main objective of the first 6 months of US GTM is to put the foundational elements of a future GTM engine in place. At the heart of it is:
With AI disrupting middle-management roles, many professionals in their late 30s to 50s will need to reinvent themselves.
Anecdotally, in the Bay Area, I’m seeing middle managers—particularly at the Director level—disproportionately affected by recent layoffs at large tech companies.
The precedent was set by Meta in 2022/23 when Zuckerberg openly questioned the need for multiple organizational layers, arguing they slowed execution. Many of Meta’s layoffs were aimed at flattening teams.
Likewise, Elon Musk and Jensen Huang are known for engaging directly with frontline employees, even interns, to unblock key challenges. Brian Chesky’s “Founder Mode” philosophy echoes this approach, encouraging leaders to dive into details and manage execution at the ground level rather than delegating critical projects to layers of managers.
Now, AI is accelerating this shift. By supercharging individual contributors—turning them into self-sufficient, full-stack execution engines across coding, marketing, and sales—AI is reshaping how Big Tech structures its workforce. As companies prioritize efficiency, the middle management layer may be on the verge of disappearing.
In the last mobile/cloud/SaaS cycle, middle managers served as the bridge between executive leadership’s vision and frontline execution. However, as tech companies swelled due to ZIRP-driven capital excess, Directors and Senior Directors—whether intentionally or not—became bureaucratic bottlenecks.
With AI disrupting these roles, or at the very least redefining their purpose and required skillsets, many professionals in their late 30s to 50s will need to reinvent themselves. This could mean re-skilling or up-skilling to become AI-native knowledge workers, transitioning to different industries, or even leaving core tech altogether to apply their experience elsewhere.
This may sound extreme, but it’s exactly what I’m observing in my circles.
Zoom pitches demand quick engagement—capture attention in 60 seconds, use visuals wisely, and keep slides concise. Bring personality and storytelling to stand out.
More than half of the pitches I take as an investor happen on Zoom. I also frequently pitch to LPs on Zoom, so I’ve gathered plenty of experience here.
Over the years, I’ve realized that pitching effectively on Zoom is a completely different skill from pitching in person. In fact, I almost always nail in-person meetings, but Zoom can be hit or miss.
In-person meetings have a consistent energy and setting—standard surroundings, small talk, and even table arrangements. Zoom, however, introduces external factors that can impact the experience: audio quality, lighting, background noise, AI note-takers, joining delays, screen interruptions, and even the lingering mood from a previous (probably also Zoom) meeting.
TL;DR:
Attention spans and patience are significantly lower on Zoom than in person. Participants lose interest and get irritated much faster.
While first impressions, body language, and icebreakers set the tone in an in-person meeting, on Zoom, you have 60 seconds to capture attention and pull your audience into your pitch.
If that’s true, Zoom pitch meetings should be structured very differently. Here’s what I recommend:
1. Open with Your Strongest Points
With only 60 seconds to grab attention, avoid meandering intros or generic company overviews. People tune out fast on Zoom. Instead, start with the three strongest parts of your pitch in the first 30 seconds.
❌ BORING: “I’m the founder of… We’re based in SF and started three years ago after identifying this opportunity while working at…”
✅ INTERESTING: “[COMPANY NAME] is [1-line description]. We’re at $X ARR/N users, growing Y% week-over-week. Our team comes from [COMPANIES], and here’s our unique insight: [1-line unique value prop].”
Walking through slides one by one makes Zoom meetings boring. It also reduces face-to-face engagement, shrinking participants to tiny squares above a massive slide. This makes it harder for investors to read facial expressions, passion, and conviction.
Instead, use slide sharing only when diving into specifics—metrics, product visuals, or key data points. If a conversation naturally leads to deeper discussions, screen-sharing makes sense. And if someone asks for more details, that’s a great sign—they’re engaged.
3. Prioritize Stories Over Generic Narratives
Broad business narratives and jargon make Zoom meetings dull. They’re harder to internalize and, in the worst cases, cause brains to switch off entirely.
Instead, use specific, personalized stories to make your points.
Rather than saying “Our product saves companies X dollars”, share a real customer success story.
Show how one specific customer (name, picture, and all) used your product and what impact it had.
Investors remember compelling stories more than numbers and percentages.
4. Leverage Visuals – Videos & Images Work Best
Spoken words are harder to absorb on Zoom, but visuals—especially videos—have a much stronger impact.
After your opening, incorporate relevant images or a short video to drive home key points. A well-placed visual can communicate in seconds what might take minutes to explain verbally.
5. Design Zoom Slides Like a TED Talk Deck
Verbose slides won’t be read. While your full pitch deck can be detailed, the version you present on Zoom should be simple, bold, and visual—like a TED Talk deck.
Each slide should focus on one core idea
Use minimal text and large fonts
Whenever possible, let charts, images, or visuals tell the story
For inspiration, check out the following slides used by top TED speakers—they prove that less is more.
TLDR: for Zoom meetings, like for TED Talks, less is more…
6. Let Your Personality Shine
Too many Zoom pitches feel robotic—monotone delivery, deadpan expressions, and no effort to break the ice. That’s a missed opportunity.
The easiest way to be interesting? Be yourself. Show quirks, humor, and enthusiasm. Your journey, energy, and passion make the conversation engaging.
Your job isn’t to blend in—it’s to stand out. If you can’t get people to actively listen and engage, a future investment isn’t happening anyway.
Closing Thoughts…
Mastering Zoom pitches is an evolving skill, but structuring them thoughtfully can make all the difference. Adapt your approach, test what works, and refine as you go.
Have you found any techniques that work particularly well in Zoom pitches? Would love to hear your thoughts!
Saw a post about how YC has been backing fewer India-based startups than before. I guess Antler, South Park Commons, and Entrepreneurs First are attempting to fill this gap to some extent.
With YC, the issue is that the quality and volume of AI founder talent in the Valley is so high right now that it doesn’t make sense to look outside.
Also, on a risk-adjusted basis, it’s unclear how India-based founders without global GTM experience/ networks will win against global competitors, especially given the rapid pace of AI evolution.
Personally, in addition to backing Indian diaspora founders in the Valley, am also tracking India-based founders who have specific product/ GTM/ verticalized superpowers and are hacking early US/global GTM in interesting ways.
For eg., am seeing a few India-based founders getting to $500k-$1Mn ARR with solid US logos by doing back-and-forth on B1/B2 visas. A few others are leveraging channel partner-based GTM cutting across multiple geos. In areas of deeptech’ish software/ hardware+software plays, the product itself tends to be fairly differentiated and sees relatively less competition from typical Valley/ YC companies, especially when you account for competitive pricing/ more value/ white-glove service/ rapid speed of iteration from India-based startups.
The enigma of junior VCs toiling-away to create market maps.
Probably one of the most mind-numbing jobs for a junior VC must be creating these frikkin’ market maps and thesis visualizations.
Imagine churning for days/weeks on a landscape doc, only for it to be obsolete in a few weeks/months with how AI is evolving.
And who do these docs eventually serve? Can’t think of them creating any real value for seed founders. Perhaps LPs?
These market maps remind me of the “market slide” that all consulting/IBs have in their deck. Hardly any customer cares about them much. They end up becoming junk collateral that some analyst/associate toiled hard to put together.
Btw this reminds me of when I was a junior VC. I had to ghost-write articles for the Partner and in the end, not even get credited for it. Even as a 27-year-old, I found it extremely discomforting that having joined the VC industry to invest in and support founders, I was spending inordinate time helping the GPs market themselves.
My (subconscious) revenge for the ghostwriting days? After a decade, have now turned blogger & podcaster with my own brand (An Operator’s Blog – blog + podcast) + investing in founders with my own world-view & conviction (my Fund Operators Studio), not begging GPs to “get a deal through”.
The backstory of Operators Studio investing in Breakout’s seed round.
Happy to share that Operators Studio has invested in the $3.2Mn seed round of Breakout, led by Village Global.
I have known Sachin Gupta since 2011 when we first met at the YourStory office in Indiranagar. He was a young IIT Roorkee grad and only a few months into starting HackerEarth. Since then, our paths crossed many times. He moved to the Bay Area a few years after I did, and we kept meeting through our respective journeys.
A few months back, Sachin reached out with just the figment of an idea of leveraging AI to fix holes in the top-of-the-funnel of enterprise sales. We brainstormed, and once he decided to go all-in, I literally became the first commit into what eventually became a marquee seed round.
So happy that Hitesh Aggarwal agreed to partner with Sachin on this journey. He is an incredibly accomplished product leader and a co-founder with very complementary skills.
What is Breakout?
Think of Breakout as an agentic workforce that grows your inbound pipeline by delivering personalized engagement to every website visitor.
Here are some of its key features:
🔸 Personalized Interactions: Breakout uses third-party signals and first-party data to tailor conversations based on visitor personas, offering relevant content and case studies. 🔸 Live Demos: It can deliver interactive demos aligned with buyer interests. 🔸 GTM Insights: Breakout provides actionable insights, such as visitor segmentation, commonly asked questions, and competitor comparisons. 🔸 BANT Discovery: It naturally uncovers Budget, Authority, Needs, and Timeline through dynamic conversations. 🔸 Fast Onboarding: Breakout offers quick setup and easy maintenance, automatically updating its knowledge base.
If this has sparked your curiosity, consider joining the Breakout Growth Program where you will get the first 6 months free, in addition to dedicated onboarding & support, as well as the ability to join their exclusive community of GTM leaders and help shape the product roadmap.
PS: this partnership is another reminder that venture is a game of long-term relationships.
Most investors try to “slot” startups in their heads, whereas extraordinary venture outcomes lie in the “slot violations”.
A few weeks back, I was helping a portfolio founder put together the story and deck for raising the next round. This company is one of the true category-creators I have seen in my career and has now reached a PMF tipping point that will lead to explosive growth going forward. Customers and channel partners are literally pulling the product out of the company’s hands, and all metrics are going up and to the right.
Despite this, the founder was sharing how difficult it still is for him to explain the business, the market opportunity, and how this is an extremely differentiated play to investors. Having seen this startup’s thesis play out as an existing investor, my conviction on it is 200% but despite powerful operating signals, it’s still non-trivial to put together a narrative that investors “get” immediately.
This isn’t a new pattern. I have seen this repeatedly play out with truly groundbreaking companies, simply because most investors prima facie, try to “slot” the company in their heads within the first few minutes of the 1st meeting. These slots are pre-existing buckets created by years of pattern-matching, and not surprisingly, 90% of startups can easily fit into one or more of these slots – eg. big company exec stepping out to start an enterprise company, young engineers hacking a dev tool, repeat founder building in the same market, generalist founders executing really fast in SaaS etc.
The issue is this – history tells us that extraordinary venture outcomes are created in the narrative violations (or what I now call “slot violations”). These are companies that are hard to understand in the present moment, being built by founders who are quirky and/or with non-obvious backgrounds, or resulting from messy pivots. Well-known examples include:
When Evan Williams was shutting down Odeo and hacking around with a micro-blogging tool (which eventually became Twitter), it had no business model even in the foreseeable future.
Imagine how Canva looked as a deal when the founders came to the Valley to fundraise – an Australian couple, no revenue, competing with Adobe, raising at $25Mn cap.
Uber had massive regulatory risks that most investors couldn’t get their heads around.
Almost every major VC has mentioned Pinterest as a big miss. It was totally unclear how Pinterest could be a “business”. Ben Silbermann talks here about “why every VC passed on Pinterest“.
As a venture investor, I think a lot about what mental models to use in order to spot these slot violations. Thinking through the earlier discussion with the portfolio founder, it was clear that even though investors might struggle to slot the company at this moment, the market was clearly resonating with the product. In a way, the early adopters in the market had been educated by the founder and therefore, were already bought into the “insight”, whereas the existing mental models of investors were lagging in their appreciation of this insight.
I call this “Insight Arbitrage” – the delta between the market’s and investors’ understanding of a startup’s unique insight. At the pre-seed stage, this market understanding will be mostly qualitative and anecdotal. At the seed stage, this understanding will still be likely on a very small base of users.
Because a majority of investors find it hard to build conviction in the above two scenarios, an Insight Arbitrage continues to perpetually exist in the venture world. And I believe that this is where an opportunity lies for investors like myself to generate alpha, provided we show the courage to trust this arbitrage and put our money behind it.
