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<title>Aleks Arriola — Writing</title>
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<description>Essays on AI systems, quantitative finance, and building at their intersection.</description>
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<title>What a Repricing Narrative Does to a Sector</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-57</guid>
<category>Finance</category>
<pubDate>Thu, 17 Sep 2026 00:00:00 +0000</pubDate>
<description>Working on the GLP-1 market analysis was a case study in how fast a single drug class can reprice an entire adjacent sector. The direct beneficiaries — the manufacturers — were the obvious trade. The more interesting moves happened one and two steps removed: snack food companies, gym chains, and med</description>
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<item>
<title>What Risk and Audit Work Reveals About Control Failures</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-56</guid>
<category>Finance</category>
<pubDate>Wed, 16 Sep 2026 00:00:00 +0000</pubDate>
<description>Studying risk and audit frameworks reframed how I think about financial statement quality. The audit process is not primarily about catching arithmetic errors — computers do that reliably. It is about testing whether the controls around a number are strong enough that the number can be trusted witho</description>
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<item>
<title>What Sales and Trading Teaches About Spreads as Information</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-55</guid>
<category>Finance</category>
<pubDate>Tue, 15 Sep 2026 00:00:00 +0000</pubDate>
<description>The instinct in most valuation work is to treat the bid-ask spread as friction — a cost to be minimized, not a signal to be read. Studying sales and trading changed that. A widening spread on a name is often the earliest available marker that liquidity providers are repricing uncertainty, well befor</description>
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<item>
<title>Tax Structure Is Where Deal Value Actually Moves</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-54</guid>
<category>Finance</category>
<pubDate>Mon, 14 Sep 2026 00:00:00 +0000</pubDate>
<description>Studying tax and transaction advisory changed how I read deal announcements. Two acquisitions with identical purchase prices and identical target companies can produce wildly different after-tax outcomes depending on whether the deal is structured as a stock purchase or an asset purchase, whether a </description>
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<item>
<title>What the Bloomberg Terminal Certification Doesn’t Teach You</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-53</guid>
<category>Finance</category>
<pubDate>Sun, 13 Sep 2026 00:00:00 +0000</pubDate>
<description>The Bloomberg Terminal certification is a good crash course in function codes and a bad substitute for understanding why the data looks the way it does. Every screen on the terminal is an aggregation choice someone made — which pricing source to default to, how to handle a thinly traded bond, what c</description>
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<title>The Valuation Kit Taught Me Valuation Is a Pipeline Problem</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-52</guid>
<category>Finance</category>
<pubDate>Sat, 12 Sep 2026 00:00:00 +0000</pubDate>
<description>I built the Orcen Capital auto valuation kit expecting the hard part to be the DCF math. It was not. The hard part was getting clean, comparable inputs out of ten different filing formats, three different fiscal year conventions, and at least one company that changed its segment definitions mid-year</description>
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<item>
<title>What the Red-Flag Scanner Actually Looks For</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-51</guid>
<category>Finance</category>
<pubDate>Fri, 11 Sep 2026 00:00:00 +0000</pubDate>
<description>When I built the Company Health Red-Flag Scanner, the hard part was not the scoring logic. It was deciding which ratios lie. Current ratio looks fine right up until a company times its receivables collection to land two days before the balance sheet date. Interest coverage looks fine right up until </description>
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<title>Optionality Is a Career Strategy, Not Just a Greek</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-50</guid>
<category>Perspective</category>
<pubDate>Thu, 10 Sep 2026 00:00:00 +0000</pubDate>
<description>In finance, optionality is the value of having choices you aren’t forced to exercise. The same idea, applied to a career, is one of the more useful frames I’ve found — and one most early planning quietly ignores in favor of committing to a single narrow path. Building at the intersection of finance </description>
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<title>What Cold Emails Taught Me About Signal</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-49</guid>
<category>Perspective</category>
<pubDate>Wed, 09 Sep 2026 00:00:00 +0000</pubDate>
<description>Sending cold emails is an exercise in humility and, quietly, in information theory. Most go unanswered. But the pattern of which ones land teaches you something you can’t learn from a guide: the difference between noise and signal in how you present yourself. The messages that work aren’t the polish</description>
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<title>The Underrated Value of Finishing Small Things</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-48</guid>
<category>Perspective</category>
<pubDate>Tue, 08 Sep 2026 00:00:00 +0000</pubDate>
<description>Ambition tends to reward for scale — the big project, the grand plan, the thing that will matter once it’s done. But grand plans have a way of never being done, and a graveyard of impressive unfinished work teaches you almost nothing except how to start. Finishing is a separate skill from starting, </description>
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<title>Why I Study the Boundary Between Two Fields</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-47</guid>
<category>Perspective</category>
<pubDate>Mon, 07 Sep 2026 00:00:00 +0000</pubDate>
<description>The center of any established field is crowded. The problems are well-defined, the experts are numerous, and the returns to being one more competent person there are shrinking. The boundary between two fields is a different place entirely — less crowded, less mapped, and far more interesting. At the</description>
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<title>Being International Made Me a Better Builder</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-46</guid>
<category>Perspective</category>
<pubDate>Sun, 06 Sep 2026 00:00:00 +0000</pubDate>
<description>Studying far from where I grew up came with obvious costs — visa constraints, distance, the friction of always being slightly outside the default. It would be easy to file all of that under disadvantage. But the same conditions quietly trained a way of working I now rely on. Being the outsider means</description>
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<item>
<title>The Skill That Doesn’t Show Up on a Transcript</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-45</guid>
<category>Perspective</category>
<pubDate>Sat, 05 Sep 2026 00:00:00 +0000</pubDate>
<description>Transcripts measure a narrow band of ability: how well you performed on defined problems under supervision. That’s real, but it leaves out the thing that turns out to matter most once the supervision ends — the ability to make progress on a problem no one has scoped for you. School hands you well-fo</description>
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<title>Learning in Public Is a Forcing Function</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-44</guid>
<category>Perspective</category>
<pubDate>Fri, 04 Sep 2026 00:00:00 +0000</pubDate>
<description>Learning privately is comfortable. You can stay in the phase where everything is tentative and nothing is finished, indefinitely. Learning in public removes that comfort, and the discomfort is precisely the point. When you commit to shipping something others will see, you can’t hide behind almost-do</description>
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<title>Why I Write These Essays</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-43</guid>
<category>Perspective</category>
<pubDate>Thu, 03 Sep 2026 00:00:00 +0000</pubDate>
<description>Writing a short essay every day isn’t a content strategy. It’s a thinking discipline. The act of putting an idea into clear prose is a stress test the idea has to survive, and plenty of things I was sure I understood didn’t make it through the first paragraph. You can hold a fuzzy notion in your hea</description>
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<title>The Portfolio Is the Resume Now</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-42</guid>
<category>Perspective</category>
<pubDate>Wed, 02 Sep 2026 00:00:00 +0000</pubDate>
<description>A resume is a claim: here is what I say I can do. A portfolio is evidence: here is a thing I built that you can open and inspect. As it gets easier to make claims and harder to trust them, the balance of proof has shifted decisively toward the evidence. This is freeing if you take it seriously. You </description>
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<title>Depth Compounds Faster Than Breadth</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-41</guid>
<category>Perspective</category>
<pubDate>Tue, 01 Sep 2026 00:00:00 +0000</pubDate>
<description>Early on, the appealing strategy is to sample widely — a bit of everything, so no door is closed. It feels safe. But breadth without depth tends to produce a long list of things you’ve touched and nothing you can actually do, and that list impresses no one for long. Depth behaves differently. Push f</description>
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<title>Latency Is a Correctness Problem for Agents</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-40</guid>
<category>AI Systems</category>
<pubDate>Mon, 31 Aug 2026 00:00:00 +0000</pubDate>
<description>Latency is usually filed under user experience — a slower system is a more annoying one. For autonomous agents, slowness crosses over into something more serious: it changes what the agent is reasoning about, because the world can move while the agent is thinking. An agent that reads a price, delibe</description>
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<title>Why Most Agent Failures Are Data Problems in Disguise</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-39</guid>
<category>AI Systems</category>
<pubDate>Sun, 30 Aug 2026 00:00:00 +0000</pubDate>
<description>When an agent misbehaves, the reflex is to blame the model or rewrite the prompt. Often the real culprit is upstream: the agent was reasoning correctly over data that was stale, malformed, or missing the piece it actually needed. An agent is only as good as what it can see. Give it an outdated docum</description>
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<title>Human-in-the-Loop Is a Design Decision, Not a Fallback</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-38</guid>
<category>AI Systems</category>
<pubDate>Sat, 29 Aug 2026 00:00:00 +0000</pubDate>
<description>Human-in-the-loop often gets treated as an admission of failure — the thing you keep until the agent is good enough to remove it. That framing quietly leads to worse systems, because it aims at the wrong target. For consequential actions, human review isn’t a crutch; it’s the correct architecture. T</description>
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<title>The Context Window Is a Budget, Spend It Deliberately</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-37</guid>
<category>AI Systems</category>
<pubDate>Fri, 28 Aug 2026 00:00:00 +0000</pubDate>
<description>Larger context windows get sold as a reason to stop worrying about what you include. Just put everything in and let the model sort it out. In practice, a context window is a budget, and spending it carelessly degrades the very reasoning you were trying to help. Models don’t attend to a hundred thous</description>
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<title>Why Guardrails Belong in the Environment, Not the Prompt</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-36</guid>
<category>AI Systems</category>
<pubDate>Thu, 27 Aug 2026 00:00:00 +0000</pubDate>
<description>The common way to constrain an agent is to tell it what not to do in the prompt. Don’t touch production. Don’t spend over a threshold. Don’t delete anything. This works until the one time it doesn’t, and prompts are the weakest possible place to enforce a rule. Instructions are suggestions the model</description>
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<title>Determinism Is a Feature You Have to Engineer</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-35</guid>
<category>AI Systems</category>
<pubDate>Wed, 26 Aug 2026 00:00:00 +0000</pubDate>
<description>Language models are probabilistic by nature, and that’s often a strength — it’s where flexibility and fluency come from. But for many real workflows, unpredictability is a liability, and determinism doesn’t arrive on its own. You have to build it in. The instinct to fix this by lowering temperature </description>
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<title>Evaluation Is the Product, Not the Afterthought</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-34</guid>
<category>AI Systems</category>
<pubDate>Tue, 25 Aug 2026 00:00:00 +0000</pubDate>
<description>Most agent projects treat evaluation as something you bolt on near the end, once the interesting building is done. That ordering is backwards, and it’s why so many demos never survive contact with real use. Without a real evaluation harness, you’re tuning by vibes — a prompt tweak feels better, so y</description>
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<title>The Hidden Cost of Every Extra Agent Step</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-33</guid>
<category>AI Systems</category>
<pubDate>Mon, 24 Aug 2026 00:00:00 +0000</pubDate>
<description>A single model call is fairly reliable. Chain twenty of them into an autonomous loop and reliability doesn’t add — it multiplies. Each step that’s 97% reliable sounds fine until you compound it: twenty of them in a row lands you around 54%. This is the arithmetic that quietly kills ambitious agent d</description>
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<title>Why Tool Design Matters More Than Model Choice</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-32</guid>
<category>AI Systems</category>
<pubDate>Sun, 23 Aug 2026 00:00:00 +0000</pubDate>
<description>Teams debating which model to use are often optimizing the wrong variable. Once you’re past a capability threshold, the gap between good models is smaller than the gap between good and bad tool design around them. A powerful model handed vague, overlapping, poorly documented tools will flounder. A m</description>
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<title>Retrieval Is Not Memory</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-31</guid>
<category>AI Systems</category>
<pubDate>Sat, 22 Aug 2026 00:00:00 +0000</pubDate>
<description>It’s tempting to describe a retrieval-augmented system as having memory. It looks the part — ask a question, and relevant facts appear in context. But retrieval and memory are different mechanisms, and conflating them leads to systems that fail in confusing ways. Retrieval fetches whatever the query</description>
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<title>Why Margin of Safety Survives Every Market Regime</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-30</guid>
<category>Finance</category>
<pubDate>Fri, 21 Aug 2026 00:00:00 +0000</pubDate>
<description>Investing frameworks come and go with the cycle. Growth works until it doesn’t; value languishes until it doesn’t; momentum is brilliant right up until the reversal. The one idea that keeps earning its keep across regimes is the oldest one: buy meaningfully below your estimate of worth. Margin of sa</description>
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<title>The Quiet Power of the Cash Conversion Cycle</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-29</guid>
<category>Finance</category>
<pubDate>Thu, 20 Aug 2026 00:00:00 +0000</pubDate>
<description>The cash conversion cycle measures how many days a company’s cash is tied up between paying for inputs and collecting on sales. It’s a single number, and it quietly captures the operational health that ratios like margin tend to flatter. A shrinking cycle means the business is getting more efficient</description>
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<title>Segment Reporting Is Where the Real Business Lives</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-28</guid>
<category>Finance</category>
<pubDate>Wed, 19 Aug 2026 00:00:00 +0000</pubDate>
<description>Consolidated financials blend everything into one story, which is convenient for a headline and misleading for analysis. A company is rarely one business — it’s a portfolio, and the portfolio’s average hides the parts that matter. Segment disclosures are where the blend comes apart. One division may</description>
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<title>Goodwill Is a Bet You Can Read on the Balance Sheet</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-27</guid>
<category>Finance</category>
<pubDate>Tue, 18 Aug 2026 00:00:00 +0000</pubDate>
<description>Goodwill is what a company paid for an acquisition above the fair value of the assets it received. Accounting treats it as an asset, but it’s really a frozen record of a bet — management’s conviction that the acquired business was worth more than its parts. That makes the goodwill line unusually rev</description>
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<title>Sensitivity Tables Are the Most Honest Part of a Model</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-26</guid>
<category>Finance</category>
<pubDate>Mon, 17 Aug 2026 00:00:00 +0000</pubDate>
<description>A single-point valuation is a story with the uncertainty edited out. It says the business is worth $47 a share, as if the analyst has resolved every assumption. Nobody believes that, including the analyst, but the format pretends otherwise. The sensitivity table is where the model stops performing c</description>
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<title>What a Debt Schedule Reveals That an Income Statement Hides</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-25</guid>
<category>Finance</category>
<pubDate>Sun, 16 Aug 2026 00:00:00 +0000</pubDate>
<description>The income statement tells you whether a company made money. The debt schedule tells you whether it will be allowed to keep operating the way it does. For distressed or leveraged businesses, the second question is the one that actually decides outcomes. Maturities, covenants, and cash sweeps are whe</description>
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<title>Precedent Transactions Lie About Control Premiums</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-24</guid>
<category>Finance</category>
<pubDate>Sat, 15 Aug 2026 00:00:00 +0000</pubDate>
<description>Precedent transaction analysis is seductive because it’s grounded in reality: these are prices real buyers actually paid. But that realism hides a bias. Deals that close are not a random sample of deals that were contemplated. Every multiple in a precedent set carries a control premium and, often, a</description>
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<title>Why Free Cash Flow Beats Earnings, Until It Doesn’t</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-23</guid>
<category>Finance</category>
<pubDate>Fri, 14 Aug 2026 00:00:00 +0000</pubDate>
<description>Free cash flow is rightly prized because it’s harder to fake than earnings. You can defer expenses and pull revenue forward on the income statement, but the cash line eventually tells on you. That’s why cash-based investors sleep better. But free cash flow has its own blind spots. A company can gene</description>
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<title>The Cost of Capital Is a Judgment Call Dressed as Math</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-22</guid>
<category>Finance</category>
<pubDate>Thu, 13 Aug 2026 00:00:00 +0000</pubDate>
<description>WACC looks like a precise number. It has decimals. It comes out of a formula. And that precision is exactly what makes it dangerous, because almost every input is an estimate wearing a lab coat. The equity risk premium is a debated range, not a fact. Beta depends on the lookback window you happen to</description>
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<title>Working Capital Is Where Value Quietly Leaks</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-21</guid>
<category>Finance</category>
<pubDate>Wed, 12 Aug 2026 00:00:00 +0000</pubDate>
<description>Analysts spend most of their time on the income statement, because that’s where growth lives. But a surprising amount of enterprise value is won or lost on the working capital line — the unglamorous gap between when a company pays its suppliers and when it collects from its customers. A business gro</description>
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<title>Comparable Companies Analysis Is Storytelling With Numbers</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-20</guid>
<category>Finance</category>
<pubDate>Tue, 11 Aug 2026 00:00:00 +0000</pubDate>
<description>Every comparable companies analysis makes the same implicit claim: these businesses are similar enough that their market multiples should be in the same range. The methodology is mechanical — collect EV/EBITDA, EV/Revenue, P/E across a peer set, apply to the subject company. What’s non-mechanical is</description>
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<title>The Case for Boring AI Architecture</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-19</guid>
<category>AI Systems</category>
<pubDate>Mon, 10 Aug 2026 00:00:00 +0000</pubDate>
<description>There’s a version of AI system design that chases novelty — multi-model orchestration, dynamic tool selection, emergent agent collaboration, recursive self-improvement. These are interesting research directions. They’re also catastrophically unreliable when something real is at stake. The most relia</description>
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<title>Why I Build Things I Can’t Fully Use</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-18</guid>
<category>Perspective</category>
<pubDate>Sun, 09 Aug 2026 00:00:00 +0000</pubDate>
<description>The Orcen Capital valuation system outputs institutional-grade research. Eighty-four Excel sheets, a Word report, a sixteen-slide deck. The kind of deliverable that would cost tens of thousands of dollars from a boutique advisory firm. I don’t manage a fund. I don’t have a portfolio to run the analy</description>
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<title>What Quality of Earnings Analysis Actually Catches</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-17</guid>
<category>Finance</category>
<pubDate>Sat, 08 Aug 2026 00:00:00 +0000</pubDate>
<description>Quality of earnings analysis sounds like accounting. It’s actually forensics. The goal isn’t to verify that the financial statements comply with GAAP — the auditors handle that. The goal is to identify the gap between reported earnings and the cash-generative reality of the business, and to understa</description>
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<title>The Information Edge Is Narrowing. The Interpretation Edge Is Not.</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-16</guid>
<category>Perspective</category>
<pubDate>Fri, 07 Aug 2026 00:00:00 +0000</pubDate>
<description>For most of financial history, information was the edge. If you had the earnings data before it was public, you had an advantage. If you had access to the terminal and the analyst knew how to use it, you had an advantage. The information asymmetry was real and durable. That edge has largely disappea</description>
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<title>When the Agent Should Stop and Ask</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-15</guid>
<category>AI Systems</category>
<pubDate>Thu, 06 Aug 2026 00:00:00 +0000</pubDate>
<description>One of the underappreciated design decisions in agentic AI is the stopping condition — the set of circumstances under which the agent should pause and request human input rather than proceeding autonomously. Getting this wrong in either direction is expensive: an agent that stops too often is just a</description>
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<title>LBO Models Are a Stress Test, Not a Price Target</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-14</guid>
<category>Finance</category>
<pubDate>Wed, 05 Aug 2026 00:00:00 +0000</pubDate>
<description>Most people encounter LBO analysis as a valuation tool — a way to determine what a private equity firm would pay for a business. This is a reasonable description of the mechanics but a slightly misleading description of what the model is actually doing. An LBO model doesn’t ask “what is this busines</description>
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<title>The Recruiter Test No One Tells You About</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-13</guid>
<category>Perspective</category>
<pubDate>Tue, 04 Aug 2026 00:00:00 +0000</pubDate>
<description>There’s an informal test that experienced recruiters apply to candidates before the first interview. It’s not about GPA or prestige. It’s about specificity. A resume that says “developed financial models” is generic. One that says “built a DCF with 84 output sheets, 5 valuation methods, and 7 behavi</description>
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<title>State Is the Hard Part of Agentic AI</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-12</guid>
<category>AI Systems</category>
<pubDate>Mon, 03 Aug 2026 00:00:00 +0000</pubDate>
<description>Most agentic AI failures are state failures. Not reasoning failures, not capability failures — failures to correctly track what has happened, what is currently true, and what commitments have been made across a multi-step workflow. In a single-turn interaction, state is trivial. The user sends a mes</description>
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<title>Why Management Guidance Is Priced Wrong</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-11</guid>
<category>Finance</category>
<pubDate>Sun, 02 Aug 2026 00:00:00 +0000</pubDate>
<description>Every quarter, management teams tell analysts what to expect. Revenue guidance, margin outlook, capex plans. Analysts update their models. The stock moves. And yet, academic research consistently shows that management guidance is systematically optimistic — and that the market consistently underweig</description>
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<title>The Difference Between an AI Tool and an AI System</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-5</guid>
<category>AI Systems</category>
<pubDate>Sun, 12 Jul 2026 00:00:00 +0000</pubDate>
<description>Most things marketed as AI systems are actually AI tools. The distinction matters more than people realize, and it determines whether what you’ve built is genuinely useful or just impressive in a demo. A tool does something when you ask it to. You provide input, it produces output. A chatbot is a to</description>
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<title>What DCF Models Get Wrong About Terminal Value</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-6</guid>
<category>Finance</category>
<pubDate>Sat, 11 Jul 2026 00:00:00 +0000</pubDate>
<description>In most DCF models, terminal value accounts for 60 to 80 percent of the total enterprise value. Which means most of what you’re doing when you build a DCF isn’t forecasting — it’s making a very precise-looking assumption about a number that depends entirely on what happens in perpetuity. The standar</description>
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<title>Building Alone Is a Feature, Not a Bug</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-7</guid>
<category>Perspective</category>
<pubDate>Fri, 10 Jul 2026 00:00:00 +0000</pubDate>
<description>Most of what I’ve built has been solo. One person, one codebase, every decision mine to make and mine to live with. In the technology world, this is often framed as a limitation — real systems require teams, collaboration, code review, specialized roles. And that’s true, at scale. But there’s someth</description>
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<title>How the Options Market Prices What Equity Analysts Miss</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-8</guid>
<category>Finance</category>
<pubDate>Thu, 09 Jul 2026 00:00:00 +0000</pubDate>
<description>Equity analysts set price targets by forecasting cash flows. Options markets set prices by forecasting distributions. The difference is not semantic — it reflects fundamentally different information about the same company, and the options market is often earlier. A standard equity price target is a </description>
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<item>
<title>What Finance Taught Me About Debugging Code</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-9</guid>
<category>Perspective</category>
<pubDate>Wed, 08 Jul 2026 00:00:00 +0000</pubDate>
<description>Financial analysts have a debugging practice they don’t call debugging. They call it reconciliation. You take a number that doesn’t match what you expected, and you work backward systematically until you find where the discrepancy entered. You don’t guess. You trace. I learned this doing financial m</description>
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<item>
<title>Why Prompt Engineering Is the Wrong Mental Model</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-10</guid>
<category>AI Systems</category>
<pubDate>Tue, 07 Jul 2026 00:00:00 +0000</pubDate>
<description>Prompt engineering treats LLMs as black boxes with a specific input format that produces better or worse outputs depending on how you phrase the request. There’s truth in this. Phrasing matters. Structure matters. Context matters. But framing the entire practice around “engineering the prompt” leads</description>
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<title>The Accruals Anomaly: The Signal Quants Have Known About for 30 Years</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-4</guid>
<category>Finance</category>
<pubDate>Sat, 04 Jul 2026 00:00:00 +0000</pubDate>
<description>In 1996, Richard Sloan published a paper showing that companies with high accruals — where reported earnings exceed actual cash generated — consistently underperformed the market in the following year. The effect was large, persistent, and largely ignored by the companies reporting those numbers. He</description>
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<title>The Only Architecture That Makes Agentic AI Safe</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-1</guid>
<category>AI Systems</category>
<pubDate>Wed, 01 Jul 2026 00:00:00 +0000</pubDate>
<description>Everyone building agentic AI right now is making the same mistake: they’re letting the model decide and act at the same time. In demos, this looks impressive. The model reads a prompt, plans a sequence of steps, calls some tools, and produces an output. It feels autonomous. It feels like the future.</description>
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<title>What 600 Company Balance Sheets Look Like Before They Break</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-2</guid>
<category>Finance</category>
<pubDate>Tue, 16 Jun 2026 00:00:00 +0000</pubDate>
<description>I built a tool that screens 600+ public companies for financial distress using eleven academic models simultaneously. Running it has taught me more about financial analysis than any course I’ve taken. The models — Altman Z-Score, Beneish M-Score, Piotroski F-Score, Dechow F-Score, and seven others —</description>
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<title>Why Finance Students Build Better AI</title>
<link>https://aleksarriola-max.github.io/#writing</link>
<guid isPermaLink="false">essay-3</guid>
<category>Perspective</category>
<pubDate>Tue, 19 May 2026 00:00:00 +0000</pubDate>
<description>There’s a conventional assumption in the AI space that the best builders come from computer science. Strong priors on system design, algorithms, and software architecture. For purely technical problems, this is probably right. But most of the valuable AI to be built in the next decade isn’t purely t</description>
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