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Explore more posts
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Steve Cornwell
I just finished Isaacson's book on Musk. It's incredible! Every founder and CEO should read it. Here are my top four learnings: (1) Mission Above All: Musk has the fortitude to build many multi-billion dollar companies concurrently because each has a humanity-altering mission that deeply convicts him. He doesn't care about being the top rocket company; he believes humanity is doomed if we don't become multi-planetary. He doesn't care about making the best-selling car; he thinks society must transition to clean energy to survive. To him, SpaceX, Tesla, and Neuralink's missions are vital to preserving humanity. Musk won't stop until he achieves these missions. (2) Guided by First Principles: Musk challenges all generally accepted conventions with first-principles thinking. This approach allows him to create much grander visions than 99.9% of people. He questions everything. He considers all fresh ideas, no matter how ambitious and unrealistic they appear. So long as the laws of physics don't preclude an idea from becoming an actual product or process, it's game on. (3) Hardcore and Extreme Urgency: Musk sets seemingly unrealistic targets with public launches and oftentimes puts his teams through excruciating circumstances to achieve massive dreams. He catches a lot of flack for it. But show me another way to build numerous multi-billion businesses at the speed he's done it. Bill Gates ran Microsoft equally hardcore in the early days - same result. Every sports championship documentary I've ever watched is about blood, sweat, and tears. I'm convinced that if you want to go big and fast, you must be hardcore. (4) Maniacal Attention to Product Simplicity and Cost: I think this is so overlooked in software. CEOs delegate to CTOs while focusing on fundraising, GTM, and culture. Imagine CEOs obsessed over product details, simplicity, and production costs. Sure, that might drive some product managers and engineers crazy, but if managed well, we'd have much better products requiring much less marketing, sales, and support investment. If you're building a company today, a few key questions: a) How much conviction do you have in your mission? Even if you're not sending rockets to Mars, will your mission fuel your drive for the next 7-10 years? b) Are you breaking conventions or following common processes? How can you shatter the mold and push your industry forward? c) Is your culture hardcore or laid-back? Do you want to go big and win championships or be comfortable and achieve moderate success? d) Do you really understand your industry, user, and product? What are the top five ways to simplify your product and reduce time-to-market and production costs? #founder #startups #ceo #saas
5620 Comments -
Derick Ruiz
I recently talked with Paz Yanover, VP of Product at Amplication, about creating and managing effective docs. Here is his developer docs success formula (check 1st comment): In this interview, Paz shares his formula to creating developer docs that drive product adoption. You'll learn: - The important role docs plays in support and attracting devs - Tips for balancing technical accuracy with user-friendliness in your docs - Strategies for effective collaboration between technical writers and product teams Check the first comment for the full interview. --- Enjoy this? ♻️ Repost it to your network and follow Derick Ruiz for more.
191 Comment -
Antti Pasila
Very interesting report on how Generative AI is rolling into corporate America. While business leaders are somewhat reluctant to make moves, employees aren’t waiting for official guidance or training—they’re skilling up with 76% saying they need AI skills to remain competitive in the job market. 💡 Move from technical focus to broader use: Business leaders have been recruiting for technical AI talent for the past 8 years and are now turning their sights to non-technical talent with AI aptitude—the skills to use generative AI tools like ChatGPT and Copilot: - 66% of leaders say they wouldn’t hire someone without AI skills. - 71% say they’d rather hire a less experienced candidate with AI skills than a more experienced candidate without them. 💡 The results are clear even if hard to quantify: Users say AI helps them save time (90%), focus on their most important work (85%), be more creative (84%), and enjoy their work more (83%). - 79% of leaders agree their company needs to adopt AI to stay competitive, but 59% worry about quantifying the productivity gains of AI - business owners are interested in bottom line results. 🚨 Something to worry about: A slightly frightening fact is that, 78% of AI users are bringing their own AI tools to work (BYOAI)—it’s even more common at small and medium-sized companies (80%). Is someone making sure your company information or confidential material isn’t shared with Google, Microsoft, OpenAI and others? Maybe the most shocking insight from this paper was the fact that 53% of people who use AI at work worry that using it on important work tasks makes them look replaceable. This will only lead to very bad company culture where people are afraid to share best practices and help each other because they are constantly afraid of being replaced and quickly the investments into AI will become counterproductive. Link to the Microsoft & LinkedIn report can be found in the comments 👇
94 Comments -
Zhia Chong
Google's Q1 earnings was amazing. https://lnkd.in/g9Se-HrD Google recently announced their earnings. Outstanding financial position, with beats across the board. EPS was 25% higher than expected, and revenue was 2% higher than expected. And they announced dividends for the very first time in history. Stock price exploded after the market, hitting $175 after-hours. All signs indicate that Google’s doing terrific and well. It’s getting leaner and more efficient as we can see from the increase in EPS. However, this earnings report comes as a stark contrast to their layoff announcements in early Jan where they laid off hundreds of jobs. Here’s my takeaway: 1. Companies are getting leaner - they're shuffling resources around to focus on biggest growth levers. 2. Job security is non-existent - even big tech companies with huge war chests are shaving fat. No one is safe. VPs, Directors, Engineers. Everyone is at risk. 3. In light of #1 and #2, you need to take care of yourself and people around you. In 10 years' time, I guarantee you won't remember the bonus or title change. But you'll definitely remember the way people treated you. 4. Never stop learning - the industry is constantly evolving. Make sure to learn the skills that are relevant. 5. Stay updated on your company's priorities - make sure you understand how your work lines up to your company's top priorities. If there's no clarity here, make sure you get clarity or get out. Conclusion: as companies trim fat and shuffle things around, regardless of financial health, make sure you take care of yourself and people around you. #google #techlayoffs #careertips
101 Comment -
Kate Brodock
I have disappointment. Firstly, this is not a defense (or lack) of Techstars' leadership, or the direction it's taking, or some of the accounts in this article. Many of you know I've been involved on the edges of Techstars for 10+ years in various program-based activities. I'm not here to comment on the specifics (I know very little). What I do want to comment on is something very salient in this article, and in accounts of too many women CEOs. In EVERY case where current leadership was reported on by name, they were ALL women. The current Techstars leadership team is not made up of all women, FYI. And in EVERY case, that woman was highlighted as being not competent for her role at the time when she started. In ALL BUT ONE case where the insider (employee or former employee) was either named or was referenced using gender pronouns, they were all men (disclaimer below). Let me rephrase: Every leader being negatively reported on here by interviewees is a woman, all were openly questioned by almost an entirely male employee base being interviewed as not being fit for their job from the get go. Right out of the gate. And here we are, with an internal account that then piles on failed partnerships and employee turnover without attribution to cause, leaving readers, if we aren't careful, to attribute that to the leadership in question. Disclaimer: Some of the specific accounts in here aren't what I'd call savory (e.g. the individual account from the former executive assistant of the SVP was the only identifiable woman in the interview set. Her claims shouldn't be ignored and are valid), and again, I'm not here to defend (or not) the specifics. But it's CRUCIAL to understand these dynamics when we read stories like this, especially about competency. And also? This entire story failed to highlight the pretty darn basic process happening here, a process that every actor, journalist, and reader in this space understands extremely clearly: You have a system that has been built over the two decades that's just plain no longer a startup. It needs to take a new form, often needs new leadership, and new leaders come in with a shake up. People who've been in the system will be uncomfortable, pissed off, in disagreement. They might even leave or get fired. They're probably going to lose some of the power they so enjoyed. THIS IS NORMAL. The reporting even suggests that the CEO's appointment came at a time of tumult, that it needed "rescuing" (a time when so many women CEOs are asked to come in - clean up!). It also suggests that power was changing, "fiefdoms" may not look the same. But how flipping normal is this, how less dramatic so much of this story actually is this? No, we have a picture of the incompetency of a group of women execs who messed everything up. We need to do better. It's 2024. https://lnkd.in/gmHhGGM7
11318 Comments -
John Ennis
Yelp has launched a new AI-powered assistant on their iOS app, revolutionizing the way users connect with local businesses. Located under the "Projects" tab, the Yelp Assistant allows users to easily find professional services by simply chatting with the AI, which smartly matches them to relevant professionals based on their needs. Yelp is empowering developers with the new Yelp Fusion AI API, enabling the integration of this conversational AI into third-party platforms for tailored business recommendations. On the restaurant front, Yelp has also revamped its Guest Manager tool, enhancing the dining experience for customers and streamlining operations for restaurant staff. Yelp continues to innovate, providing efficient solutions for discovering and connecting with local businesses. Read more from Techcrunch here => https://neoswap.cc/28e2a5 #YelpUpdate #AI #TechNews #LocalBusiness #Innovation
102 Comments -
Gokul Rajaram
AI SOFTWARE PRICING: PRICE BASED ON METRICS IN YOUR CONTROL AI-Native Software Founders: I'm sure by now, you've all read the posts around how you should price your products based on end-customer outcomes (vs seats or other old-school methods). While this is all good, I have a caveat for you. Be careful that you only price based on metrics that you have control over. For example, if you're building an AI SDR agent that's used by other companies as a replacement for human SDRs, the temptation might be to price based on appointments scheduled by the AI agent. The challenge with this is that you don't have control over the product quality / differentiation, the competitive dynamics, or even the customer mindset when they get a message from you. For all these reasons, the right metric to price on is an intermediate metric under your control, such as "activities" (where an activity might be generating a lead list, composing a personalized email to a prospect, etc). One can estimate how many activities a SDR completes per month, and the AI SDR agent should be able to tirelessly accomplish multiples of this number at a fraction of the price. And so hopefully, the cost per appointment should be lower than with a human SDR. But it's a folly to price on this. A good analogy is search advertising. Google could have priced search ads as cost per conversion instead of cost per click, since Google has tremendous amounts of conversion data (from Google Analytics, Chrome, etc). However, ultimately the conversion rate on the website is impacted by many factors not under Google's control (product, offer, marketing message, website design, etc), and it doesn't make sense to price on conversions. Google reports the number of conversions per campaign, since they can track it, but they don’t price on it. Don’t confuse being able to track something with being able to influence or control it. tl;dr Figure out a leading indicator that's fully under your control, and price based on this intermediate metric, vs on the eventual outcome. PS this exercise of finding the right metric to price on, is not easy. You must deeply align with customer outcomes and understand the entire chain of events that leads to value being delivered, and figure out what the right event is to price on. An ultimate balancing act. A critical ingredient to do this well is having a feedback loop around outcomes as a guardrail.
34313 Comments -
Victor Lang
Seed rounds seem hotter than ever, but Series A rounds are getting scarcer and stingier. So what’s going on? My take is that the market has split in two. The NASDAQ and S&P are flying based on AI optimism, but the rest of the market has been pretty sideways. That’s translated into private markets. All the enthusiasm for SaaS has evaporated and been replaced with love for AI. This is disproportionally benefiting earlier companies because more of them fit the AI thesis, and they have nice, clean cap tables. But it’s also creating some idiosyncratic valuation issues. I saw a commentator say that Series A companies need to be hitting 400% annual growth and $4 mm ARR on a 1x Cash conversion score to raise a Series A right now. They might be right, but that only applies to non-AI startups who are struggling to fit into any investor thesis at all. AI startups are raising without metrics that don’t even come close to that. So where does this all end? Well - based on the marketing materials I’ve seen for funds, it seems that almost all the new capital being raised has an AI thesis to it (even in the defense space, which is... controversial and maybe terrifying….). That probably means this dynamic is likely here to stay. But unlike other hype cycles, like sharing economies (which required a whole new business model) and blockchain (which required a totally new code base), LLMs seem relatively easy to incorporate. To the extent that they help solve a customer pain point better, everyone can be an AI startup. So my guess is that AI or not, the buzzy crop of AI startups in YC will go through the same painful process of finding product market fit. It’ll be hard to find customers. It’ll be hard to make a great product. And it’ll be hard to charge the prices they need to. And while they are working through that, some decade old marketing/legal tech company that knows their market really really well is gonna be using AI to roll out the features their customers have been requesting for years - and making good money from it
264 Comments -
Omer Khan
Meet the founders who raised $50M, never spent it, and still grew their SaaS startup to well beyond $10M ARR... In 2014, Kaveh Rostampor & Niklas Skog worked at different SaaS companies, but both spent a lot of time figuring out how to reduce churn. They decided to launch a startup to solve this problem. 1) For the first six years, they bootstrapped: They had to be very careful with their money, focusing on creating a product that provided genuine value. 2) Acquiring initial customers was no easy feat: It required building a deep understanding of potential customers' problems and relentless cold calling. 3) As their startup grew, they faced a new hurdle: How could they keep both small companies & enterprise customers happy? It meant tough decisions & tradeoffs. 4) They raised money but kept their bootstrap culture: They continued running their company with a 'bootstrap mindset', and it kept growing without them having to spend the $50M. Today, their startup Planhat: - Serves hundreds of customers - Tens of thousands of daily users - Generates 8 figures in ARR And that $50M is still sitting in the bank account. Here are 3 lessons from this story: 1) When you bootstrap, you've got no choice but to build something people actually want to pay for. 2) As your startup grows, juggling the needs of different customers gets tricky. Mastering prioritization is key. 3) Raising capital helps, but true success hinges on founder resilience, not the size of your bank account. --- Want more insights to help build and grow your SaaS? Get my 5-minute weekly newsletter (link on my profile).
22012 Comments -
James Murphy
What do VCs actually look for in pre seed deals, particularly given the recent wave of AI startups? As a B2B SaaS focused investor, I have the opportunity to evaluate thousands of software businesses, and invest in 100+ each year. One of my favorite parts of my job is meeting exceptional founders and learning about problem spaces that are completely new to me, but the investment team at Forum Ventures spends a lot of time discussing focus areas and opportunities where we see the most promise and are actively looking to invest. In the coming weeks, I'll be sharing a series of market opportunities where I am looking to back exceptional founders solving challenging problems. * Automation of complex, legacy workflows within enterprise, particularly across regulatory and compliance use cases. * Application of AI across the defense and broader government sectors, specifically related to operational efficiencies, the infrastructure stack required to leverage cutting edge AI advancements, and the development and adoption of autonomous systems. * Manufacturing/hardware design and production, spotlighting modern manufacturing - robotics, aerospace, alternative energy, medical devices, etc. * Complex manufacturing supply chains- from extraction to processing and refining, and ultimately through manufacturing and distribution. If any of the above sounds like something you are building, let’s connect. #GenerativeAI #VentureCapital #EarlyStageStartups #Innovation #TechTrends #AI
393 Comments -
Tomasz Tunguz
If I asked you, “When someone turns in a work assignment, how accurate is it? 80%, 90%, 95% or perhaps 100%?” We don’t think this way about coworkers’ spreadsheets. But we will probably think this way about AI & this will very likely change the way product managers on-board users. When was the last time you signed up for a SaaS & wondered : Would the data be accurate? Would the database corrupt my data? Would the report be correct? But today, with every AI software now tucking a disclaimer at the bottom of the page, we will be wondering. “Gemini may display inaccurate info, including about people, so double-check its responses” & “ChatGPT/Claude can make mistakes. Check important info” are two examples. In the early days of this epoch, mistakes will be common. Over time, less so, as accuracies improve. The more important the work, the greater peoples’ need to be confident the AI is correct. We will demand much better than human error rates. Self-driving cars provide an extreme example of this trust fall. Waymo & Cruise have published data arguing self-driving cars are 65-94% safer. Yet, 2/3 of Americans surveyed by the AAA fear them. We suffer from a cognitive bias : work performed by a human is likely more trustworthy because we understand the biases & the limitations. AIs are a Schrodinger’s cat stuffed in a black box. We don’t comprehend how the box works (yet), nor can we believe our eyes if the feline is dead or alive when we see it. New product on-boarding will need to mitigate this bias. One path may be starting with low-value tasks where the software-maker has tested exhaustively the potential inputs & outputs. Another tactic may be to provide a human-in-the-loop to check the AI’s work. Citations, references, & other forms of fact-checking will be a core part of the product experience. Independent testing might be another path. As with any new colleague, the first impressions & a series of small wins will determine the person’s trust. Severe errors in the future will erode confidence, that must be rebuilt - likely with the help of human support teams who will explain, develop tests for the future, & assure users. I recently asked a financial LLM to analyze NVIDIA’s annual report. A question about the company’s increase in dividend amount vaporized its credibility, raising the question : is it less work to do the analysis myself than to check the AI’s work? That will be the trust fall for AI. Will the software catch us if we trust it?
5910 Comments -
Victor Lang
A simple way to understand seed venture capital: a founder needs to build a company worth roughly 20x the size of the VC that invests in it. Here’s why: A typical seed stage fund has a 10-year life and will pitch its investors 12% a year (compounding) returns. That means it needs to 3x it’s fund over 10 years. Statistically, it’s likely going to achieve most of that from a single investment, which it will likely own roughly 15% of at exit. So for founders the math is simple. You need to convince a VC that you can build a company that is worth the Venture Capital Fund Size x 20 (or 3/15%) I.e. A $100mm seed fund will be betting you build a $2bn company. The bigger the fund the bigger the number. Keep this in mind when you are pitching.
333 Comments -
David Cyrus
99% of tech companies use the term “platform” wrong. Coinbase is in the 1% that uses it correctly. A tech platform is infrastructure that other companies, products, and services can be built upon. Sorry, but your SaaS, while a great SaaS product with happy customers, is likely not a platform. Examples of tech companies with platforms: • Microsoft: Windows, Azure, etc. • Apple: iOS • OpenAI: ChatGPT • Staffbase (my former employer): white-labeled employee app and intranet But isn’t Coinbase just a crypto exchange? For most of its history, yes, but it’s about to become something much bigger. Coinbase has launched Base, a Layer 2 blockchain built on top of the reliability of Ethereum, which enables smart contracts. Base is built to handle large amounts of transactions at fast speeds and with little to almost no fees. And with that, and their user-friendly programs, companies, products, and services will be built on top of Base. This makes Coinbase a platform company – arguably one of the most important ones soon. Jesse Pollak, Head of Base, demonstrates below. I know my “Digital Business Model Strategy” professor Dr. Roger Moser would love this - it's a picture perfect digital business model strategy. #DigitalTransformation #BusinessStrategy #Strategy #Coinbase #Blockchain #Innovation #Technology
89 Comments -
Sunil Daluvoy
What I learned from Jerry Yang & Larry Page TL;DR: Technology companies launching disruptive products should religiously focus on end-users above everything else, including partners. Solve end-user problems and everything else follows– adoption, revenue, and partners. Yahoo! & Jerry Yang (2006) In 2006, phone calls were expensive and based on time & distance pricing. Skype changed all that with VoIP, which bypassed telco networks and made super cheap calls using the Internet. They already amassed 34 million users and were growing at insane rates. At the same time, Yahoo Messenger had over +110 million users worldwide. We could leverage this userbase and create a VOIP product to challenge Skype. Yahoo had all the advantages on paper: the brand, the users, and the technology. So, with the leadership of Brad Garlinghouse, we built a competing product with a very disruptive pricing plan – 1 cent/min; Skype's pricing ranged from 2-3 cents/min. However, a week before the launch, Jerry Yang paused the project at a partner’s request. ATT-SBC was concerned our pricing would cannibalize its own voice business. Yang did not want to upset that relationship. Ultimately, Yahoo missed its opportunity, and Skype was off to dominate the VoIP market. Google & Larry Page (2008) Before the iPhone, companies had to negotiate with mobile carriers to get their apps on phones. Google was struggling to secure deals with Verizon for Google Maps and a new phone concept, Android. Around the same time, the FCC planned to auction 3G spectrum. Google pushed for open application and open device requirements on the carriers who won the auction. This infuriated the carriers. They argued that such conditions would decrease the spectrum's value below the $4.8 billion auction floor set by the US government. The FCC was leaning towards the carriers. The agency did not want to risk the auction not meeting the government's financial goals. Google's only option was to participate in the auction to ensure the minimum bid. Inside Google, the decision to bid was intensely debated. Android founder Andy Rubin argued the carriers would hate us and never partner with Android; Chris Sacca argued that bidding was the only way to guarantee Google's future in mobile. Page sided with Sacca. Page’s rationale: “. . . the carriers already hate us. If we don’t bid, they would hate us and not respect us.” We bid, the openness provisions were triggered, and we secured a path for Google apps on 3G. Sixteen months later, Andy got his deal Verizon – Verizon Droid! Page was willing to sacrifice mobile carrier deals to ensure Google’s products were universally accessible to its users. He played spectrum poker with $4.8 billion to achieve that result. (cont. below)
2911 Comments -
Peter Walker
More startups using Carta closed down in Q1 2024 than in any other quarter. 254 startups shutdown in Q1 vs 161 in Q1 of 2023 - 58% higher. To tackle an expected objection: 𝘁𝗵𝗶𝘀 𝗶𝘀 𝗻𝗼𝘁 𝗮 "𝘀𝘁𝗮𝗿𝘁𝘂𝗽 𝗳𝗮𝗶𝗹𝘂𝗿𝗲 𝗿𝗮𝘁𝗲". I do think that the failure rate is higher (see the other panes in this slideshow to see more on this) but apologies in advance for folks who want the failure rate only. It's pretty tough to get an exact failure rate given the denominator changes with companies joining Carta. However, most companies join Carta these days at the pre-seed stage (through our free Carta Launch program) so the population for priced round companies is more stable. 𝗢𝘁𝗵𝗲𝗿 𝗞𝗲𝘆 𝗣𝗼𝗶𝗻𝘁𝘀 • Shutdowns rose across the board, but the increase was higher for companies who had already raised a priced round vs those that have yet to get into priced equity fundraising (click to the second slide for this). • Shutdowns rose 102% from Q1 2023 to Q1 2024 for companies in the Priced Seed stage. Really challenging moment for founders at that point. • Shutdowns rose 133% for Series B companies over the past year. It's not just the smaller companies closing up shop. This is a very difficult moment for many startups, brought on by interest rates changes flowing to fundraising slowdowns, on and on. Hug your founder friends - so much respect for those trying to push forward through the muck 🙏 #cartadata #startupshutdowns #shutdowns #startups #fundraising
32776 Comments -
Peter Walker
Seed-stage fundraising looks very different depending on the startup industry. Valuation and cash raised typically move together (not a lot of tiny rounds at very high valuations), but the disparity between industries can be quite large. All data from 1,271 priced Seed rounds raised from Apr 2023 thru Mar 2024. Primary rounds only, US rounds only. Industries had to have 10 separate raises to be included. A note on AI - if you tracked it as a separate industry, it would at the top of every list. But it exists within many of these categories as well, so we displayed it in the chart below as a little red box. 𝗢𝘃𝗲𝗿𝗮𝗹𝗹 𝗞𝗲𝘆 𝗣𝗼𝗶𝗻𝘁𝘀 1. Healthtech overtook Fintech as the second-largest category in our data, a change from the last time we measured these metrics. 2. Seed volume is down across almost every category save AI (and even there, not up much lately). More seed deals are being completed on SAFEs (not shown in this chart) but the valuations and cash raised are very similar between SAFE and Priced rounds by industry. 3. The laggards in the chart (DTC Retail, Food, Personal Products) are essentially the same as last year. Are founders here turning towards other methods of funding, including revenue, instead of going the VC route? 4. Will many of these companies ever raise a Series A? Lots of talk lately about "venture stripping", "thin VC", "single round VC", whatever you want to call it - founders who explicitly set out to raise only 1 round and then fund their growth with revenue from then on. Very cool strategy! Remains to be seen if many $1B+ valuation companies can be built that way (though of course that isn't always the goal). Please share this post with a fundraising founder 🙏 #cartadata #startups #fundraising #seed #founders ---------- More data like this out every week in our Carta Data Minute Newsletter - subscribe at the link in graphic!
54546 Comments -
Healy Jones
🔎 This is a well done analysis. 🔎 I gave a founder pretty similar advice yesterday about what to target and expect at the seed. And while I'm seeing founders raise seeds w/o any revenue, those founder are either repeat founders or strong pedigree founders (like AI Phd's with time at Google etc.). So for the typical founder, shooting for at least $250k in true ARR with 300%+ growth or more is a good target. And the more the more likely you are to raise funding. 🎯
205 Comments -
Healy Jones
🚨 Bookkeeping is HARD - a Lesson from Synapse's Collapse 🚨 I was recently quoted in Mary Ann Azevedo's TechCrunch article on the bankruptcy of Synapse, a banking-as-a-service startup. As someone who works at a CPA firm that does bookkeeping for clients, the Synapse situation really resonated with me. Synapse had essentially one job - to sit between fintech startups and banks, and keep track of where each end-customer's funds went. Sounds simple, right? WRONG. Bookkeeping, especially in the highly-regulated world of finance, is incredibly complex. When Silicon Valley tries to "move fast and break things" in fintech without truly understanding the accounting complexities, people can actually get hurt. Supposedly, Synapse's collapse has impacted up to 10 MILLION consumers who now can't access their money. 😱 That's a lot of ordinary people who are going to have problems paying their rent or getting groceries. I'm seeing a similar wave of unkept promises hitting the small business accounting space. Startups saying that they can "automate" complex accounting tasks, but not really understanding what they actually need to do. And not taking into account how their mistakes will impact their small business customers. The last time this happened there were a lot of business owners who ended up losing a lot of their hard-earned cash when their supposed expert accountants messed up or dropped the ball. 😞 I'm sure that will happen again, and it bums me out. I'm all for moving fast and breaking things, but not if it hurts other people. https://lnkd.in/g6p_5viM?
82 Comments -
Gokul Rajaram
PRICING STRATEGY WORKS (EVIDENCE) Just got this note from an amazing repeat founder: “Saw the above and felt compelled to ping you. Spot on. I wanted to price on outcome for the past year. We are creating a a massive increase in EBITDA—upwards of 110% based on our real data built into proforma. I was being absolutely stonewalled when it came to convincing our customers to let us profit share from the savings we generated (never mind actually being in control of that outcome). Even if they were on board they would say (but in year 2 where are the savings….not understanding it's a before/after not a yearly thing). We settled on a pricing structure that is exactly as you say. Based on metrics we control, not outcomes we don't. XMM in ARR this year.”
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San Antonio, TX -
Oscar Rodriguez
Vice President, Data Analytics at Citi
Greenville-Spartanburg-Anderson, South Carolina Area -
Oscar Rodriguez
Greater Orlando -
Oscar Rodriguez
Software Engineering Student at UC Irvine | Seeking Summer Internship 2024 | C++/C, Java, Html/CSS, React, x86 Assembly, & relational databases
Los Angeles, CA
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