Alex Solomon

🎙️ From Square to Mercury: How Rohini Pandhi became one of fintech’s top product leaders—and how velocity of learning at high slope companies shaped everything. Rohini dropped so many gems in our first episode of First Builders: 💎 Generalist → Specialist: In her early career, she was a generalist and tried everything. This led her to critical discoveries. She specialized in product and fintech when the “time was right” 💎 Follow the Engineers and Designers: Square was a high slope environment for Rohini, packed with talent density and learnings. She finds high slope environments by studying where smart engineers and designers are going. 💎 Fake News about PMs: PMs don’t just “move fast and break things.” Her team runs 30-50 customer interviews per quarter, providing rigor behind every decision. 💎 It’s Usually Too Early to Hire a PM: A top question she gets from founders is whether they should hire a PM. She usually says: “it’s too early.” 💎 Hiring a World Class Team is Like Tennis: When finding a tennis partner, you want someone a little better than you who can challenge you to improve your game. Give us a listen and leave a review on your favorite podcast location (see comments for links)! #FirstBuilders #StartupPodcast #ProductLeadership #TechCareers #Leadership

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Thrilled to announce that Together Fund is investing in Sentra, alongside a16z speedrun! You track results in Jira. Decisions in Notion. Conversations in Slack. But the reasoning, the debates, trade-offs, and context behind why you chose A over B, disappears into what we call "Dark Matter." A decision made in March looks insane by July because no one remembers the constraints that made it smart. I lived this firsthand at Twitter scaling from 800 to 8,000 employees, and at Google while launching AI Overviews to billions at planet scale. The problem isn't process. Process is compensation for something deeper: organizational amnesia. An organization’s "Systems of Record" doesn’t solve this, they encode it. They store what happened, never why. That's why we are investing in Sentra. Sentra is the always-on collective memory that eliminates organizational amnesia by maintaining accurate context for all members and agents, functioning as an operational nervous system. It connects to every channel where work happens, meetings, Slack, email, code commits, docs, calendars, and treats them not as artifacts to search, but as living signals to synthesize. The fleeting and the permanent, unified into a memory that understands. The founding team is built for this: - Jae Gwan Park (CEO): Product-first founder, memory systems research at UofT and MIT - Ashwin Gopinath (CSO): Former MIT professor, created "Reflexion" (NeurIPS 2023), agents that learn from mistakes, 2x founder - Andrey Starenky (CTO): Early Vapi engineer, ex-IBM, built to process enterprise-scale data firehose Together is an operator-led fund. We invest in problems we've lived. This is one of them. Many congrats Jae, Ashwin and Andrey, we are so excited to partner with you! Read the full thesis: https://lnkd.in/gixj9cE4 Book a demo: https://www.sentra.app/ #OrganizationalMemory #AI #Sentra #TogetherFund #a16z #ContextGraphs

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Venture funding isn't success of course, but it's nearly impossible to win big markets without it. Unlike the AI hype, Ando is very, very real. And unlike others, Ando is here to make lives genuinely better for everyone. (*) #proudinvestor #micdrop #oversubscribed Big thx to Bradford Oberwager and James Kairos, Ben Metcalfe, Andy Mutz, Joseph Chittenden-Veal, Scott Sanders, Massy Ghausi, John Lyman, Thomas Wesley, John Holder… and of course Phoenix Toews and Paul Wellons (to name a few) — (*) Yeah yeah, some pencil-pusher will use AI to over-optimize profits over people, but as American Airlines is learning the hard way (WSJ: https://lnkd.in/ePz_QNzt ), net of competition, "people businesses" don't work that way. You HAVE to care for people or you lose. Ando plays a beautiful collaborative role in that dialogue, helping profit-focused management more clearly see the effects of a motivated labor force. That's why I'm truly #proudinvestor --- Posts co-authored with my LinkedIn secret weapon Dennis Buckley

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If you’re a CEO/founder or PE operator and your tech org is: ❌ Shipping late ❌ Stuck in reactive mode ❌ Struggling through the Series A/B jump, or post-acquisition integration or after a major release It’s not “a delivery problem.” It’s an operating model problem. At the inflection point, the old playbook breaks: what worked at 10 engineers fails at 40… and breaks again across multiple products/teams. That’s where I come in as a fractional CTO: - Spot platform and delivery risks before they hit revenue and retention - Rebuild execution rituals (prioritization, ownership, release confidence) without derailing the roadmap - Align architecture + team structure to your value-creation plan (growth, margin, or exit timeline) If you’re feeling the strain of growth, I can help you turn “busy and reactive” into predictable shipping, and a platform that scales. #CTO #SaaS #StartupScale #PrivateEquity #TechStrategy

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Always fun to host engineering dinners with Sumeet Vaidya and Crafting. Few takeaways for me: 1. We are living through one of the most dynamic periods in software engineering. Everyone by now knows to heavily leverage “Plan” mode upfront when coding with AI - but now we are hearing there’s even more time/tokens/turns spent on “Ask” mode before writing the Plan. And PRs of plans! We are literally flying up the abstractions curve. 2. Documentation used to be a luxury, but it is now cheap and easy. Documentation is increasingly agent-first, and markdowns in the repo seem to work a lot better than Confluence/Notion. 3. Historically the magic of GitHub was how it captured the collaboration context - PRs, discussions, reviews, commit history. Today so much of that context sits in prompt/chat history which does not go in GitHub or anywhere else! Feels like this needs to be solved. Openclaw’s memory system and Granola are both inspirations.

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87% of YC companies are enterprise. Now it makes complete sense that AI is starting in enterprise. The models are expensive to run, and enterprise lets you automate workflows and vertically integrate. But to reach billions of people in their daily lives. The real prize is still consumer. A lot of founders are scared of consumer right now. At any point, OpenAI or Google can vertically integrate and kill your company. But you can make a similar argument for enterprise applications. The other part is that consumer is genuinely hard. Distribution is more mature, the App Store feels saturated, and there aren’t obvious new channels. At the same time, we are in the midst of a revolution. Interfacing with the world will be more than just a handful of chatbots. If you pay attention to daily life, to your parents, your kids, anyone close to you, you’ll notice how many small, annoying things still exist. Yes, the App Store is mature. But the top apps right now are AI apps. If something is truly great, innovative, or fun, people will go out of their way to find it. Menlo Ventures analyzed routine tasks of US adults. The Takeaway: Fewer than one in five people actually use AI for their day-to-day tasks. Most people stick with whatever system they already have, even if it’s annoying. At Hands, we're building with these 3 rules in mind: 1. Meet people where they already are 2. Make it easy to try. 3. Prove the product's value almost immediately

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CPTO Revolution: Why SaaS Companies Are Merging Product and Tech Leadership I’ve lived the pain of siloed leadership and the inefficiencies it creates many times. And I’ve also seen how tightly integrated product and tech can transform not just delivery, but outcomes. Traditional org charts are no longer keeping up. The most competitive SaaS companies aren’t hiring separate CTOs and CPOs anymore - they’re bringing both roles under one roof with CPTOs. This isn’t about headcount optimization. It’s about reducing friction and moving faster in a world where complexity is climbing and customer expectations evolve by the week. Here’s the core issue: when product and engineering leadership are separate, you’re always playing a game of telephone. Product defines what’s needed. Engineering estimates and negotiates. Product pushes. Engineering pushes back. Handoffs everywhere. Every step is a delay. A CPTO owns the entire journey - from insight to shipped product. One person accountable. One vision. One continuous flow. And it works. Companies running this model are seeing up to 40% faster go-to-market. Less tech debt. Clearer priorities. Higher team velocity. What Actually Changes 1. Aligned Metrics You stop optimizing for isolated outcomes. Product isn’t chasing adoption while engineering shields uptime. Both roll into shared business goals. 2. AI Gets Strategic With unified leadership, AI isn’t a bolt-on. It becomes core to how you design, build, and validate products - through data, feedback loops, and automation. 3. Developer Experience Matters Platform engineering gets the attention it deserves. Internal tools align with product delivery, and suddenly teams aren’t waiting - they’re shipping. UX maturity, platform architecture, technical scalability - all of it becomes a single continuum. You’re not just improving “process”; you’re aligning every decision to what users need and what’s feasible to build. The CPTO Skillset This isn’t a hybrid role - it’s an integrated one. You need the technical depth to guide architecture and the product judgment to say no to overengineering. You talk to engineers about latency and reliability, and to the board about market traction and differentiation. As AI accelerates software development, what matters is orchestration—of systems, teams, and strategy. You need to see the whole board. Cloud infra spend is growing ~10% yearly, mostly due to AI. That spend needs direction. CPTOs are the ones who can match innovation speed with platform efficiency. Companies clinging to the old CTO/CPO split are playing a slower game. Integration is no longer optional - it’s a competitive advantage. So—what’s keeping your org from making the leap?

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🚨 Founders: If you're not exploring cross-industry alliances, you're playing the wrong game. Some of the biggest breakout companies didn’t scale by outspending the competition they scaled by out-partnering them. 🚀 Think Figma embedding into dev workflows. 🚀 Calendly riding the rails of Zoom and Salesforce. 🚀 Zapier integrating with Trello and Slack before raising big money. 💡 The playbook? Fuse your solution with another industry's infrastructure and unlock distribution, data, or demand without burning capital. Cross-industry alliances do 3 things: 1. Collapse time by borrowing someone else’s audience. 2. Unlock non-obvious use cases that give you strategic moats. 3. Increase your valuation before the first funding conversation. If you're a startup founder and you’re stuck thinking, “We need capital to grow,” you’re asking the wrong question. Ask instead: 👉 “Who’s already serving my customer in a different way and how do we win together?” That’s how exponential growth actually happens. 💬 Founders: Which alliance would double your reach in 90 days? #Startups #GrowthStrategy #VC #EarlyStage #FounderTips #Platform #AI

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We’re all familiar with first-mover advantage. But is AI quietly making second-mover advantage more powerful? Dalton Wais and I have been talking a lot about how our roles as engineers have shifted over the last few months. AI is pushing engineers further upstream, closer to product management. When you can build almost anything, what you choose to build matters more than ever. That was always true, but it feels amplified now. A lot of our time recently has gone into experimenting with how we define, analyze, and capture product requirements. Some of this is still very traditional. Talking to our ICP, listening carefully, synthesizing notes, analyzing transcripts. But more and more, we’re using AI to surface requirements at a depth and speed that just wasn’t possible before. For the payroll system I’m working on, that looks like a few things. Asking AI to find and analyze every payroll product demo video on YouTube, not just reading transcripts but inspecting the UI itself frame by frame, and producing a comparative matrix of features across vendors. Asking AI to scan blogs, Reddit, and forums for people complaining about payroll software, clustering those complaints, and turning them into candidate requirements. Asking AI to read thousands of reviews across G2 and similar sites and separate what customers say they want from what they say they hate. And then layering all of that together. This is what got me thinking about second-mover advantage. When you’re the first mover, very little of this data exists. The market is mostly theory and opinion. But once a category matures, it generates an enormous exhaust of demos, reviews, complaints, and expectations. AI can now consume that exhaust almost instantly. If you can take a well-understood set of requirements and turn it into working software quickly, the old moat of “we’ve been building this for years” starts to matter less. Time to market was a real advantage pre-AI. Now time to insight might be the bigger one. Of course, this just pushes pressure onto the other hard problems. Narrative. Distribution. Lock-in. First movers still have advantages there, if they execute well. But the quiet moat of time spent just building is eroding fast.

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Founders with capital that refuse to hire or add resources to alleviate constraints aren't preserving runway -- they're sabotaging growth velocity. I'm seeing this pattern more frequently: 20+ moths of runway, strong customer demand, a product that's delivering ROI but a founding team clearly spread too thin resulting in self-inflicting issues and paper cuts. I think founders feel that by doing everything you're evoking resiliency and capital discipline. Sometimes that's lauded. However, I think it's founders optimizing for control and comfort rather than scale and delegation. From the investor seat, here's how I'm trying to understand this behavior: (1) Avoiding 'role evolution.' - It's hard to graduate from scrappy founder that has to do everything to scrappy founder with the ability to delegate and deploy resources. Hiring means transitioning from building - - > manager - - > leader (2) Control-minded orientation - We naturally feel more accomplished when we can measure our own output (Ex: sales calls made, lines of code written, support tickets resolved, etc...). When you take time hiring and then ultimately unload these tasks, you have to reinterpret your own productivity and be okay with anchoring towards somebody else's. In reality, runway is not the lens to view your business. If capital is sitting idle on your balance sheet with clear use cases for deployment, all you're doing is suppressing momentum and growth. I care less if you were ultimately wrong where you deployed capital rather than running your business to optimize for more runway. Investors implicitly trust your judgment so just have a more growth-oriented mindset 🫡 🚀 .

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