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Are Your AI Agents Reasoning From a Snapshot That Never Existed? | Tacnode Founder + CEO

Could Tacnode be the next Databricks? Yes. Imagine the world before writing. Before books. People had to learn everything from scratch.Thanks to writing, thanks to books, knowledge compounded. Everyone could learn from each other. Today's AI agents don't yet have their version of writing or books. They operate in isolation, without the shared understanding or context of what previous agents and humans have experienced. They have to start over. Learn everything from scratch.This is the context gap.Tacnode exists to solve the context gap. I interviewed Xiaowei Jiang, Tacnode founder + CEO on AI with Alec E31. What follows are four of his arguments that have stuck with me, worth weighing in your own context. 1: The primary user of enterprise software is shifting from humans to agents. Databricks. $5.4B revenue run-rate. 65% YoY growth. $134B valuation. 60%+ of the Fortune 500. The most valuable private enterprise software company in the world.That's the bar.In Xiaowei's view, lakehouse architecture became the standard because humans were the primary consumer of data. Databricks and Snowflake built extraordinary capabilities for the analytical workloads they were designed to serve.But humans are slow. A handful of decisions a day with long gaps. Pipelines had time to catch up. Caches had time to refresh.Agents collapse those assumptions. Thousands of decisions a second. No human in the loop. Zero tolerance for conflicting signals.This isn't about replacing analytical platforms. Tacnode sits alongside the lakehouse, purpose-built for real-time agent decisions. 2: Most "AI failures" are not model failures. They are context failures. Xiaowei broke it into three patterns. AI invents things when context is missing. AI contradicts itself when sources conflict. AI commits confidently to information that is no longer true.The model is rarely the bottleneck. The pipeline behind it is.When an agent reads account balance from one system, transaction velocity from another, and behavior signals from a third, each with its own lag, the model is reasoning from "a snapshot that never existed in the world."In fraud detection and credit underwriting, that fictional snapshot shows up on the P&L. 3: The design starts with what must be true at decision time. The intuitive approach is to wire together best-in-class components. A great stream processor. A great feature store. A great search engine. Each one correct in isolation. The composite system is not.Guarantees that hold inside one system erode the moment you cross to another.Xiaowei's team inverted the design. Start with what must be true at decision time. Build everything else on top of that contract.This is what first principles looks like below the waterline. 4: Shared context compounds. Isolation does not. "If a database gives you application shared state, context lake is going to give agents shared memory in a compounding system." Read that twice. Every decision an agent makes generates a signal worth keeping. A fraud pattern. A predictive signal. A route cause. In an isolated stack, that learning evaporates with the session. In a Context Lake, it becomes every other agent's capability instantly.The early movers don't just deploy infrastructure. They accumulate institutional knowledge inside it."The cost of waiting is not linear. Every month you wait, the gap grows." Early movers compound. Late movers start at zero. Humans + Machines. Never Humans vs. Machines.

"We Don't Do Tokenized Assets" Is the New "We Don't Do the Internet" | Jason Dobbs

The promise of deploying autonomous AI agents at scale hinges on infrastructure and architectural truths. AI isn’t magic or a silver bullet. It most definitely isn’t one size fits all. What did it accomplish?  What steps were taken to get there?  What was the general knowledge vs more specialized, subject matter expertise required? What logic was introduced and how did it reason along the way? Jason Dobbs, Founder and CEO of ICTI, is building AI-enabled tokenized issuance for sovereign debt. He joined me on AI with Alec E30 and shared his truths using the fascinating vocabulary of a space I’m intrigued by.  I was all ears. Two of Jason’s quotes are stuck in my head: 1. “‘We don’t do tokenized assets.’ That’s the same as saying, ‘We don’t do the internet.’” 2. “That’s a real big sledgehammer approach, when sometimes you just need a tiny little jewelry hammer going at something.” Below the waterline. Architecture and infrastructure is where it’s at.

The AI Questions CEOs Are Running Out of Time to Ask | Henrik Werdelin

There's a short list of people who shaped my AI journey before I even knew it was a journey. Henrik Werdelin [https://www.linkedin.com/in/werdelin/] is at the top of that list. We met in NYC in 2011. A few months before he launched BARK [https://www.linkedin.com/company/bark-thedogcompany/]. I was the furthest thing from technical. He had a gazillion things going on. But he made time, answered every question and never made me feel like I was behind. Those conversations in NYC accelerated my learning curve in ways I'm still drawing from today. Bark now ships millions of dog toys a month. Henrik has since built Audos.com [https://www.linkedin.com/company/audos/], an AI-native incubator that can launch a business in 15 minutes. He hasn't slowed down once. My hope with this episode is simple. What Henrik did for me back then, this conversation does for all of you now. A few things he said that I can't stop thinking about: 1️⃣ Most enterprise leaders are about to hit a wall they don't have language for yet. 2️⃣ AI agents are going to free up enormous human energy inside your organization. The question nobody is asking soon enough: what does your organizational design do with it? 3️⃣ The unlock isn't a better AI strategy. It's a harder question: what is your company's strategy in an age of AI? Humans + Machines. Never Humans vs. Machines.

75% of Your Creative Team's Week Is Wasted. Shane Hegde Built a Salesforce for Creatives to Fix It.

Creativity is magic. 75% of your creative team’s week is logistics, 25% is actually creating. What happens when you invert that? Shane Hegde [https://www.linkedin.com/in/shanehegde/] has spent eight years fixing that problem and the implications for modern CMOs are staggering. Most CMOs have no visibility into what content their org is creating, where it’s going or how it performs. Shane drew the parallel to a CRO with no pipeline view, something unimaginable at this point. What Salesforce [https://www.linkedin.com/company/salesforce/] is to CROs, Air [https://www.linkedin.com/company/airhq/] is to CMOs. Air is an operating system for your visual data. Images, videos, raw files, ad campaigns + brand assets. Organized, enriched, searchable and connected to performance data so your CMO knows what content exists, where it lives and what it’s doing. The 75/25 split? Air flips it. Air backs it up with six months of forward deployed engineers on their dime, not yours. My man Shane Hegde put his actual cell phone out there, multiple times, on my podcast. That’s what 15 years of friendship and 8 years of obsession looks like. He’s expecting your call. I guarantee he will get back to you. Quickly. Humans + Machines. Never Humans vs Machines. s/o Tyler Strand [https://www.linkedin.com/in/tyler-strand/], Ping Ma [https://www.linkedin.com/in/ping-ma-04a1327/], Ariel Rubin [https://www.linkedin.com/in/arieljrubin/]

Polsia: The AI That Doesn't Just Help You Build a Business. It Runs it. | Ben Cera

Would you believe me if I told you there’s an autonomous AI agent platform that enables anyone with a business idea to outsource to a swarm of AI agents to handle everything except what the founder wants to focus on?Would you believe me if I told you this company has seen its ARR run rate grow from $0 to $100K to $1.5M in a few weeks, with a trajectory that looks less like a hockey stick and more like an elevator shaft?Allow me to introduce you to Polsia and the founder + CEO, Ben Cera.There are 3 reasons Polsia and Ben are the focus of #10.1: Polsia epitomizes how AI is unleashing a sonic boom of entrepreneurial and human potential by dialing up our ability to “focus on making the beer taste better” instead of all the other important but tedious workEntrepreneurs spend 26-50% of their work week on administrative tasks [https://www.timeetc.com/resources/how-to-achieve-more/the-big-price-of-small-tasks-how-entrepreneurs-may-be-unwittingly-keeping-their-businesses-small/]. First time founders have an 18% success rate and the leading reasons startups fail are no market need (42%), running out of funding (29%) and the wrong team (23%) (link [https://ff.co/startup-statistics-guide/]). There are 28.5 million solopreneurs in the US, 81% of all small businesses are solo, non-employer firms, yet less than 4% ever break $1M in revenue (link [https://www.score.org/greaterphoenix/resource/blog-post/small-business-failure-rates-2024-summary]).Ben’s framing is simple and surgical: AI handles 80% of the operational grind. Humans focus on creativity, taste and direction. What used to be inaccessible infrastructure for a bootstrapped one-person company is now table stakes.2: Solo founder + AI stack is a new start-up archetypeOne person. No employees. No engineering team. $0 to $1.5M ARR. Ben never looked at the code. Polsia was built by AI and works in production.Team size as a proxy for ambition is becoming a thing of the past.We’ve moved from AI enabled promises to reality. The future arrived yesterday. 3: What’s the difference between the democratized AI-enabled infrastructure an Entrepreneur vs Intrapreneur has access to? Hint: nothingPolsia is enabling Entrepreneurs to capitalize on the AI Technical Overhang. No different than the way Intrapreneurs in established companies can lead tiger teams, departments or even entire companies by harnessing the technology.Remember the one word (“Goose”) Jack Dorsey left out of his memo (AIWA “The One Thing” #08 [https://alecs-newsletter-e6d356.beehiiv.com/p/aiwa-the-one-thing-08-the-one-word-missing-from-jack-dorsey-s-letter-about-block-s-layoffs])? Remember Anthropic’s AI labor market research describing “what AI is theoretically capable of doing versus what’s actually happening in the workplace” aka The Gap is the Game (AIWA “The One Thing” #09 [https://alecs-newsletter-e6d356.beehiiv.com/p/aiwa-the-one-thing-09-the-gap-is-the-game])?You know what I mean?Less strategy, “more hands in the dirt” doing.The 18-year-old with a great idea who couldn’t afford a team? They can now build like a funded company. That’s not disruption. That’s democratization.Never run from it. Run at it.