Investment Considerations

Small angel investors make the startup world go round - founders could be missing out by setting a high minimum check size. The SAFE has come to dominate angel / early startup investing, mostly because of decreased legal costs and time. So we looked at over 19,000 SAFEs signed by startups in 2023. All of these SAFEs went to companies that had yet to raise any priced equity. Some may be part of "seed on SAFE" rounds, others to true pre-seed companies. Small checks (under $25K) made up a full 62% of all checks signed in the earliest rounds (those under $250K total raised). Even rounds that came in just under $1 million had major participation from small checks. In fact, the median check size for all rounds $1 million or less never got over $25,000 last year. What do these small checks bring to a founder? Julian Weisser of On Deck suggests: 1. Expertise = They can help in a particular area (GTM, sales, hiring, etc).     2. Network = They can introduce you to other investors, potential customers, or future teammates.     3. Legibility = their involvement will help in the areas mentioned above and positively impact how other investors view your company. And sure, the total capital from these small checks may only account for a sliver of the total round. But they can demonstrate progress, push forward momentum, and the angels themselves may open doors to larger investors down the road. We are also seeing many initial advisors to nascent startups become strategic angels down the line. Lots of ways to improve your cap table. Here's to a year of small checks! Data just like this flows into 19,000 inboxes every Thursday morning - head over to the link in graphic to subscribe. #cartadata #startups #preseed #SAFEs #angelinvesting #founders

They spent $1M on an AI strategy … but 75% of it was impossible to execute. Here’s the full story… I sat in a boardroom, surrounded by executives who had just proudly shown me their new AI strategy. They'd just invested nearly a million dollars in this beautiful 120-slide masterpiece. These weren't just experienced leaders. They were smart, successful executives who had built a billion-dollar company. But as I flipped through the slides, my heart sank. After 30 minutes of gentle questions about their current capabilities, I took a deep breath: "9 of these 12 use cases? You can't actually do them. Not yet." The silence that followed was painful. One executive finally spoke up: "What do you mean? We just paid nearly a million dollars for this strategy and it looks great!” Sometimes the most expensive advice isn't the right one. Here's what nobody tells you about AI strategy: 𝟭. 𝗕𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗩𝗮𝗹𝘂𝗲 𝗶𝘀𝗻'𝘁 𝗲𝗻𝗼𝘂𝗴𝗵: Just because a use case could deliver $10M in value doesn't mean you can execute it. I've seen companies waste months chasing shiny objects while ignoring their actual readiness. 𝟮. 𝗙𝗢𝗨𝗡𝗗𝗔𝗧𝗜𝗢𝗡 𝗺𝗮𝘁𝘁𝗲𝗿𝘀 𝗺𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝗙𝗘𝗔𝗧𝗨𝗥𝗘𝗦 (𝗶𝗻 𝗺𝗼𝘀𝘁 𝗰𝗮𝘀𝗲𝘀) You need the right data infrastructure, talent, and operational processes BEFORE you can do the fancy stuff. It's like trying to build a skyscraper without checking if you have the right foundation. I’ve always had a motto “Master the Basics so you can Scale Your Innovation” - 𝟯. 𝗧𝗵𝗶𝗻𝗸 𝗕𝗶𝗴, 𝗦𝘁𝗮𝗿𝘁 𝗦𝗺𝗮𝗹𝗹, 𝘁𝗵𝗲𝗻 𝗱𝗲𝗰𝗶𝗱𝗲 𝘄𝗵𝗮𝘁 𝘁𝗼 𝗦𝗰𝗮𝗹𝗲 𝗤𝘂𝗶𝗰𝗸𝗹𝘆 It’s better to successfully implement 3 modest use cases than fail at 12 ambitious ones. Build confidence, learn, and scale from there. Now, coming back to the story… Today, they've successfully implemented 5 use cases (including 2 from the original "impossible" list). They stopped trying to match the theoretical playbooks and started with where they actually were. The lesson? Your AI strategy shouldn't be based on what others are doing. It should be based on three things: - Where you are with your maturity. - What you can execute. - Where you want to go. Sometimes the best million-dollar strategy is to save the millions you’ll be spending chasing the million- dollar strategy.

I found this meme funny… but also strikingly accurate. Many CEOs are rushing into AI with huge enthusiasm, but often without clarity on what specific problem they’re solving. The result? Exactly what you see here. After 3+ years partnering with companies on conversational AI solutions, I’ve seen this pattern repeat countless times. Organizations invest in AI, then wonder why they’re not seeing ROI. The real challenge isn’t “Do we need AI?” (we do). It’s “How do we implement it to create measurable, sustainable value?” Here’s what I’ve learned separates successful AI implementations from expensive experiments: Start with the problem, not the technology – Define outcomes before choosing tools. Establish clear success metrics – If you can’t measure it, you can’t improve it Align strategy across stakeholders – Technical teams and business leaders must speak the same language. Focus on value, not features – Shiny doesn’t always mean useful The technology is ready. What’s often missing is the strategic bridge between business objectives and technical execution. I’ve worked with CTOs who knew exactly what they wanted to build but couldn’t quantify business impact. I’ve advised executives who had clear ROI targets but no technical roadmap. The magic happens when strategy and execution align. What’s been your experience with AI implementation? Are you seeing real value — or just expensive experiments? #AI #ConversationalAI #DigitalTransformation #BusinessStrategy #TechLeadership

We’re in a moment where CIOs and other business leaders need to see their investments in AI pay off in both quantifiable and qualitative ways. Time to value is critical — and so is having a clear idea of how to measure that value. I’m being asked more and more how business leaders can ensure that their AI investments are having maximum organizational impact right now. Here’s how. Invest in areas where people are already active: To quickly unlock value, focus on making AI accessible to every business user. By integrating AI or deploying AI agents into existing workflows—where performance metrics are already established—you create an ideal setup for measuring incremental impact and demonstrating tangible value. Measure everything: It’s often more straightforward to account for quantitative improvements (hours saved, dollars saved, faster response times, etc.). But it’s also important to gauge the qualitative benefits, like improved employee confidence when selling to or serving customers. Don’t underestimate the qualitative: AI is still an emerging technology, and the better business leaders can understand customer and employee sentiment around productivity gains, the more of an edge they’ll have on the competition. #ArtificialIntelligence #AI 

Trust, But Verify A Firsthand Look at Oil & Gas Investment Due Diligence In the world of alternative investments, trust is essential—but verification is non-negotiable. You should never be a passive investor, especially before you write a check. It’s your responsibility to do your homework and perform due diligence. Go beyond just reviewing the pitch deck or attending a webinar. Dig into the material, ask hard questions, meet the people behind the deal, and—if possible—visit the site. There are a lot of things you should do before committing your capital, and the more thorough you are, the better your investment decisions will be. Recently, I had the opportunity to visit an oil field firsthand to verify the details of an investment opportunity. This wasn’t just about reviewing projections or reading geological reports; it was about seeing the operation, speaking with field experts, and assessing risks on the ground. What I Looked for On-Site 1. Production Infrastructure & Maintenance – A well-run site reflects operational efficiency. Are the wells in good condition? Are the pipelines and equipment well maintained? 2. Geological & Engineering Reports vs. Reality – Reports tell one story, but do the reserves, drilling plans, and production rates align with real-world conditions? 3. Operator Track Record – The experience and integrity of the operators matter. Have they successfully managed similar projects? Are they transparent about potential risks? 4. Regulatory & Environmental Compliance – Permits, environmental safeguards, and adherence to state regulations are critical indicators of long-term viability. Why This Matters for Investors Too often, passive investors rely solely on pitch materials and financial models. While these are important, they don’t tell the whole story. Physically verifying an investment—or ensuring your investment partner does—can be the difference between a calculated risk and an uninformed gamble. This visit reinforced an essential principle: A great investment isn’t just about numbers—it’s about execution, management, and integrity. Final Takeaway: Be an Active Investor with the goal of passive income. If you’re investing in oil & gas, multifamily, or any alternative asset class, ask yourself: ✅ Who is managing my investment? ✅ Are their assumptions backed by reality? ✅ Have I (or my trusted partner) verified the details firsthand? The best deals stand up to scrutiny. Trust, but always verify. Would love to hear from fellow investors—what’s your approach to due diligence? Drop your thoughts in the comments!

Enough with the AI Hype! Show Me the Money. (3 Questions Every CEO Needs to Ask) AI investment is surging, but are we actually seeing the measurable impact?  A Boston Consulting Group (BCG) study drops a truth: 74% of companies struggle to get real value from their AI investments. We're all hearing about AI's potential, but I cut through the noise with three crucial questions every leader needs to ask BEFORE diving into any AI initiative: 1 - Where does AI fit in your business? To drive real ROI, pinpoint where you’re applying it: ↳ Product: Personalizing recommendations to boost customer engagement. ↳ Process: Automating claims processing to cut costs. ↳ Problem: Detecting fraud in real-time to prevent losses. Each use case requires a different AI strategy—so be specific about where it fits. 2 - How will we measure success? Define clear KPIs with measurable impact: ↳ Cut churn by 15% (Product). ↳ Reduce call center costs by $5M (Process). ↳ Detect fraud with 98% accuracy (Problem). Baseline your current performance, track improvements, and prove the ROI. 3 - Is a tech vendor confident enough to commit to results? ↳ If they can’t back their claims with SLAs and performance-based contracts, they’re selling hype, not value. Stop chasing hype and start demanding ROI. Let's start talking more about this real challenge along with the tech hype Andrew Ng Allie K. Miller Zain Kahn Ruben Hassid What AI investments have actually delivered tangible results for you? Do you know how to measure it? #AI #AIActionSummit #TheInsider

Founders do not discount investors just because their check sizes are small. “But Shuaaaaannnnnn I need $1 million for my AI garlic bread startup, not a $10k check from an angel!” Right, champ. Because obviously you are going to turn down money while building a company that currently lives in a WeWork and runs on free AWS credits. Founders often set a minimum check size. $10k. $20k. $50k. They want to “keep the cap table clean,” or “it is too time consuming to manage multiple investors,” or the classic, “it nudges people to invest more.” That’s a mistake. You can keep your cap table clean with an SPV. You can manage multiple investors with one monthly update email that you already copy-paste anyway. And no, you are not “nudging” anyone to invest more than they want to. If someone is only willing to part with $5k, no amount of your “AI garlic bread TAM analysis” is going to magically make it $50k. By keeping your minimum check size high, you are excluding most of the people in your network. Which is the exact opposite of what you should be doing. Lower your check size and you 10x the pool of people who can participate. You give more people a reason to root for you, to open doors, and to make intros. If it’s good enough for a YC startup, it’s good enough for you. Some of the scrappiest founders out there stacked their seed rounds with dozens of “tiny” checks, and then used those investors as a distribution network to raise bigger ones later. Accept small checks. Put more people in your corner. Build momentum. Use their networks to create new pathways. Because one investor can write you a check. Fifty investors can write you checks and introduce you to the next fifty. And if you are lucky, one of those $10k angels might just bring you the intro that changes everything. After all, AI garlic bread is better when you share it. #startup #founders  #venturecapital

After reviewing dozens of enterprise AI initiatives, I've identified a pattern: the gap between transformational success and expensive disappointment often comes down to how CEOs engage with their technology leadership. Here are five essential questions to ask: 𝟭. 𝗪𝗵𝗮𝘁 𝘂𝗻𝗶𝗾𝘂𝗲 𝗱𝗮𝘁𝗮 𝗮𝘀𝘀𝗲𝘁𝘀 𝗴𝗶𝘃𝗲 𝘂𝘀 𝗮𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺𝗶𝗰 𝗮𝗱𝘃𝗮𝗻𝘁𝗮𝗴𝗲𝘀 𝗼𝘂𝗿 𝗰𝗼𝗺𝗽𝗲𝘁𝗶𝘁𝗼𝗿𝘀 𝗰𝗮𝗻'𝘁 𝗲𝗮𝘀𝗶𝗹𝘆 𝗿𝗲𝗽𝗹𝗶𝗰𝗮𝘁𝗲? Strong organizations identify specific proprietary data sets with clear competitive moats. One retail company outperformed competitors 3:1 only because it had systematically captured customer interaction data its competitors couldn't access. 𝟮. 𝗛𝗼𝘄 𝗮𝗿𝗲 𝘄𝗲 𝗿𝗲𝗱𝗲𝘀𝗶𝗴𝗻𝗶𝗻𝗴 𝗼𝘂𝗿 𝗰𝗼𝗿𝗲 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗽𝗿𝗼𝗰𝗲𝘀𝘀𝗲𝘀 𝗮𝗿𝗼𝘂𝗻𝗱 𝗮𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺𝗶𝗰 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻-𝗺𝗮𝗸𝗶𝗻𝗴 𝗿𝗮𝘁𝗵𝗲𝗿 𝘁𝗵𝗮𝗻 𝗷𝘂𝘀𝘁 𝗮𝘂𝘁𝗼𝗺𝗮𝘁𝗶𝗻𝗴 𝗲𝘅𝗶𝘀𝘁𝗶𝗻𝗴 𝘄𝗼𝗿𝗸𝗳𝗹𝗼𝘄𝘀? Look for specific examples of fundamentally reimagined business processes built for algorithmic scale. Be cautious of responses focusing exclusively on efficiency improvements to existing processes. The market leaders in AI-driven healthcare don't just predict patient outcomes faster, they've architected entirely new care delivery models impossible without AI. 𝟯. 𝗪𝗵𝗮𝘁'𝘀 𝗼𝘂𝗿 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 𝗳𝗼𝗿 𝗱𝗲𝘁𝗲𝗿𝗺𝗶𝗻𝗶𝗻𝗴 𝘄𝗵𝗶𝗰𝗵 𝗱𝗲𝗰𝗶𝘀𝗶𝗼𝗻𝘀 𝘀𝗵𝗼𝘂𝗹𝗱 𝗿𝗲𝗺𝗮𝗶𝗻 𝗵𝘂𝗺𝗮𝗻-𝗱𝗿𝗶𝘃𝗲𝗻 𝘃𝗲𝗿𝘀𝘂𝘀 𝗮𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺𝗶𝗰𝗮𝗹𝗹𝘆 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗲𝗱? Expect a clear decision framework with concrete examples. Be wary of binary "all human" or "all algorithm" approaches, or inability to articulate a coherent model. Organizations with sophisticated human-AI frameworks are achieving 2-3x higher ROI on AI investments compared to those applying technology without this clarity. 𝟰. 𝗛𝗼𝘄 𝗮𝗿𝗲 𝘄𝗲 𝗺𝗲𝗮𝘀𝘂𝗿𝗶𝗻𝗴 𝗮𝗹𝗴𝗼𝗿𝗶𝘁𝗵𝗺𝗶𝗰 𝗮𝗱𝘃𝗮𝗻𝘁𝗮𝗴𝗲 𝗯𝗲𝘆𝗼𝗻𝗱 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗼𝗻𝗮𝗹 𝗺𝗲𝘁𝗿𝗶𝗰𝘀? The best responses link AI initiatives to market-facing metrics like share gain, customer LTV, and price realization. Avoid focusing exclusively on cost reduction or internal efficiency. Competitive separation occurs when organizations measure algorithms' impact on defensive moats and market expansion. 𝟱. 𝗪𝗵𝗮𝘁 𝘀𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗮𝗹 𝗰𝗵𝗮𝗻𝗴𝗲𝘀 𝗵𝗮𝘃𝗲 𝘄𝗲 𝗺𝗮𝗱𝗲 𝘁𝗼 𝗼𝘂𝗿 𝗼𝗽𝗲𝗿𝗮𝘁𝗶𝗻𝗴 𝗺𝗼𝗱𝗲𝗹 𝘁𝗼 𝗰𝗮𝗽𝘁𝘂𝗿𝗲 𝘁𝗵𝗲 𝗳𝘂𝗹𝗹 𝘃𝗮𝗹𝘂𝗲 𝗼𝗳 𝗔𝗜 𝗰𝗮𝗽𝗮𝗯𝗶𝗹𝗶𝘁𝗶𝗲𝘀? Look for specific organizational changes designed to accelerate algorithm-enhanced decisions. Be skeptical of AI contained within traditional technology organizations with standard governance. These questions have helped executive teams identify critical gaps and realign their approach before investing millions in the wrong direction. 𝘋𝘪𝘴𝘤𝘭𝘢𝘪𝘮𝘦𝘳: V𝘪𝘦𝘸𝘴 𝘦𝘹𝘱𝘳𝘦𝘴𝘴𝘦𝘥 𝘢𝘳𝘦 𝘮𝘺 own 𝘢𝘯𝘥 𝘥𝘰𝘯'𝘵 𝘳𝘦𝘱𝘳𝘦𝘴𝘦𝘯𝘵 𝘵𝘩𝘰𝘴𝘦 𝘰𝘧 𝘮𝘺 𝘤𝘶𝘳𝘳𝘦𝘯𝘵 𝘰𝘳 𝘱𝘢𝘴𝘵 𝘦𝘮𝘱𝘭𝘰𝘺𝘦𝘳𝘴.

Most people invest because someone else said it was a “sure thing.” But what if confidence without clarity is just a risk in disguise? You know that FOMO-fueled move when your friend brags about a big win? Many investors follow the hype, calling it a shortcut. But there’s a sharper way. One that trades noise for knowledge and luck for logic. 5 questions to ask before following someone else’s investment: 1. Do I understand the business or asset? ↳ “If you can’t explain it, you probably shouldn’t buy it.” 2. What’s my risk tolerance? ↳ “Just because they’re comfortable doesn’t mean you are.” 3. Does this align with my goals? ↳ “Quick wins rarely build lasting wealth.” 4. What’s the downside? ↳ “Hope is not a strategy. Know what you could lose.” 5. Have I done my own research? ↳ “Your money deserves more than secondhand conviction.” The smartest investors don’t copy; they calculate. Sustainable investing starts with personal responsibility. What’s one lesson you’ve learned from doing your own due diligence? Follow Justin Donald For More

Ever signed a deal… only to later realize the numbers you trusted were hiding the truth? It looks perfect at first glance, but what if those “profits” are just smoke and mirrors? That’s exactly what happened when I worked with an investor who nearly bought a company showing $6M in annual revenue and “20% margins.” On paper, everything looked solid. But once we dug in, the reality was very different: - $800K in receivables were over 120 days past due and unlikely to be collected - Inventory was overstated by $300K because obsolete stock wasn’t written off - One-time revenue made the last quarter look artificially strong Without proper due diligence, he would have overpaid by millions. Here’s what financial due diligence really checks for: 📌 Quality of earnings — are profits sustainable or inflated? 📌 Working capital — is enough cash tied up in receivables and inventory? 📌 Liabilities — hidden debts, tax exposures, or off-balance-sheet risks 📌 Forecasts — are future projections realistic or just a sales pitch? After the review, he adjusted the valuation, renegotiated terms, and saved himself from a bad deal. Business owners and investors, remember this:   Due diligence is not paperwork. It’s protection from financial pain you can’t undo later. #duediligence  #finance  #businessgrowth