🚀 Jon Schlinkert

Something that founders need to be aware of in the early days is that "Deep intellectual honesty is an INCREDIBLY important trait for founders" -- Connor Zwick. It's easier to avoid the truth, than to face it. Dalton Caldwell and Y Combinator call this "magical thinking"

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This is the auto-healing system inside VantageOS. Most platforms depend on people to notice when something breaks. This one is built to notice, understand, and respond on its own. Behind the interface is an internal agentic layer continuously monitoring system state, data integrity, workflow execution, and operational signals. When something drifts, degrades, or fails, it does not just raise a flag. It diagnoses the issue, traces dependencies, and initiates corrective action to restore alignment. Quietly. Continuously. Without waiting. Because in complex environments, small inconsistencies do not stay small. They cascade. Adam and I built this with a simple principle: a serious system should not just run, it should maintain itself. That means detecting anomalies early. Resolving issues before they compound. And keeping the platform stable, reliable, and aligned even as conditions change. This is what operational resilience looks like when it is built into the system itself. #VantageOS #AI #AgenticSystems #Automation #OperationalIntelligence #Resilience #Infrastructure #SystemsThinking https://lnkd.in/giTUvp3p

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We're not in the AI or Platform business. We're in the edge case business. 😅 In the AI world of "move fast and break things," our competitive advantage (and biggest headache) lies in something unglamorous but critical: catching and fixing edge cases before they cascade downstream. And sometimes we don't. But when our users point them out as they encounter them, it makes the software better for everyone. It's not sexy, but it's what keeps the whole system running smoothly. Where's the vanity metric for "edge cases handled"??!

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Most founders avoid government markets. Too complex, too slow, and too much red tape. But that complexity was the opportunity. Ion-Alexandru S. noticed contractors drowning in 100+ page RFPs. He and his co-founder built GovCon in a Box to cut through the noise. What started as a chat app became a vertical SaaS that: > Solved a painful, daily problem > Turned free users into loyal paying customers > Scaled through word of mouth When the time was right, he listed on acquire.com. Clear records, steady revenue, and a simple story. Buyers moved fast. Within weeks, he had a life changing exit. Lesson for founders: > Complexity hides opportunity. > Customer feedback should shape your roadmap. > Clear, boring SaaS beats flashy features every time. Ion is now onto his next venture, seoforge.ai. Full story + podcast here: https://lnkd.in/gh9QQ-9r

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Holy crap, I guess I have not run a competitor evaluation in a few months on OpenAI or Gemini. They have become brutal in their approaches for both tactics and strategy. Playing to win/last man standing, that much is for sure. "[Product Name] that is functionally adequate for basic use cases but is technologically lagging and beset by significant integration flaws. This gap between the product's market position and its technical reality creates a substantial, time-sensitive opportunity for a technologically superior challenger to enter and redefine the market." 50 other pages that follow, that just ripped through the entire industry, like a laser beam. The amount of data that Gemini is pulling in--and the speed at which it does so--is staggering.

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Former Indiana governor Eric Holcomb is right. AI presents a real opportunity in American manufacturing, not just in theory but in practice. The industry faces a projected need for 3.8 million new workers by 2033, a gap that can’t be closed by hiring alone. AI won’t replace workers outright, but it can change how work gets done, enabling factories to be safer, more productive, and more competitive than they have been in decades. Holcomb frames this with historical context and the idea that AI can help sustain and expand manufacturing jobs by boosting productivity and attracting investment. The value isn’t just automation. It’s augmentation, enabling people to oversee AI systems, discover new use cases, and apply human judgment where it counts. That perspective aligns with what we’re seeing across the industry. AI-enabled tools are optimizing work from the factory floor to customer-facing teams - driving revenue, reducing downtime, and enabling smarter decision-making, while people continue to play an indispensable role in guiding the technology and creating new opportunities. #Manufacturing #AI #IndustrialTech #FutureOfWork https://lnkd.in/gPXtEnNS

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Same File. $202,000 vs. $15. A ministry was preparing to mail a large donor file selected through its existing fundraising process. From within that mailed universe, Pulse Predictive selected two 1,000-donor cohorts and made a prediction before we saw any campaign results. One cohort was predicted to produce a positive ROI. The other was predicted to produce a negative ROI. When the results came in thirty days later, the Positive ROI cohort had generated 592 gifts, more than $202,000 in revenue, a 59.2% response rate and an estimated ROI above 400:1. The Negative ROI cohort generated two gifts and $15. Its response rate was 0.2%, and it failed to recover the cost of mailing. I keep coming back to that result because the ministry’s existing process had already made one important decision about all 2,000 donors: mail them. What it could not see was how radically different their economic potential had become. That is an important distinction. A mailing file answers who qualifies to receive the campaign. It does not necessarily reveal where the economic opportunity is concentrated inside that file. Two donors can satisfy the same historical selection criteria and still carry dramatically different probabilities of producing net income now. Across a large fundraising program, that difference becomes real money. The question is no longer simply whether a donor belongs in the mailing file. It is whether the ministry knows where each fundraising dollar has the greatest probability of producing more net income before that dollar is spent. That is what made this validation so compelling to me. Pulse Predictive did not explain the results after they happened. We made the prediction first and allowed the campaign to tell us whether we were right. If 2,000 donors your current process has already decided to mail can separate into more than $202,000 on one side and $15 on the other, what could knowing where the economic potential is concentrated do for your ministry’s net fundraising income? If you’d like to answer that question with your own data in time for Q4, send me a message. We still have a small number of Predictive A/B Validations available using anonymous donor data. No software demo required. Don’t believe the claims. Test them. 🔁 Repost if you believe better fundraising decisions deserve as much attention as better fundraising reports. 🚀 Follow Jerry Rassamni for practical insights on AI + Analytics, predictive fundraising, and increasing net fundraising income. #Fundraising #Nonprofit #Ministry #PredictiveAnalytics #ChristianMinistry

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We’re all sold on OpenClaw, but can it ACTUALLY be useful to the average person who doesn’t just sit around writing code? Turns out it can! Here’s how Matthew Berman used OpenClaw to help solve his stomach issues!

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