February 2026

Most common-sense explanations of time quietly assume what they are supposed to explain. We say time moves forward because clocks tick. But clocks only measure something, they do not explain why it has a direction. n We say time moves forward because the universe started in a special state. But that just pushes the mystery to the beginning and calls it a solution. The arrow of time still looks like a narrative patch. A story we tell to […]

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If I asked a hundred people to define twenty words, no two persons would give identical definitions for all twenty. If each word has just three possible interpretations (the actual number is far higher), that’s 3^20 = 3.4 billion possible combinations. Your definition of “intelligence” was shaped by every smart and stupid person you’ve met, every test you’ve taken, every moment you felt quick or slow. Mine was shaped by different people, different tests, different moments. When you […]

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I do not think I would hire a butler who’s hypnotizable. The idea of a butler is a pretty strange thing. What if someone hypnotized the butler to do something ? I think it would be better to have a butler who can think for themselves and make choices. A hypnotizable butler would not be very good, at keeping secrets or taking care of things. I would want a butler who’s smart and can stay in control not […]

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Manual image editing for product retail often bottlenecks creative teams with repetitive tasks like background removal and resizing. This article introduces Combo Banana, a prototype that automates these workflows by allowing designers to define reusable “combos”—sequences of AI-driven operations executed in seconds. Built on a modern stack featuring Gradio for the interface, Nano Banana for advanced AI processing, and Google Cloud Run for serverless scalability, the tool demonstrates how powerful models can be abstracted into practical, user-friendly solutions. […]

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Physics-informed neural networks and neural operators often suffer from severe optimization difficulties caused by ill-conditioned gradients, multi-scale spectral behavior, and stiffness induced by physical constraints. Recently, the Muon optimizer has shown promise by performing orthogonalized updates in the singular-vector basis of the gradient, thereby improving geometric conditioning. However, its unit-singular-value updates may lead to overly aggressive steps and lack explicit stability guarantees when applied to physics-informed learning. In this work, we propose SpecMuon, a spectral-aware optimizer that integrates […]

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Every product I have worked on has features that cost more to keep than they are worth. Not broken features. Not controversial ones. Features that work fine, get used by almost nobody, and sit there quietly taking up space. I have kept features like that alive for years. Not because they added value, but because removing them felt like more work than leaving them in place. They worked. They were not hurting anyone. Why bother? That reasoning felt […]

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In Part 1, we built the engine. A small set of EODHD-backed tools, an agent with strict rules, and a single run_brief() function that returns two outputs: the markdown brief and the structured artifacts. This part is about turning that into something you can actually demo. We’ll build a simple Streamlit app that feels like a real feature: a query box on the left, a brief in the main view, and the tool-backed numbers rendered next to it. […]

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Training LLMs as interactive agents for multi-turn decision-making remains challenging, particularly in long-horizon tasks with sparse and delayed rewards, where agents must execute extended sequences of actions before receiving meaningful feedback. Most existing reinforcement learning (RL) approaches model LLM agents as flat policies operating at a single time scale, selecting one action at each turn. In sparse-reward settings, such flat policies must propagate credit across the entire trajectory without explicit temporal abstraction, which often leads to unstable optimization […]

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In this article you’ll learn how CPython lists actually work under the hood: how a static array model explains fast indexing and “no holes” behavior why contiguity matters, and how indexing reduces to one computation what really happens when the list grows: allocate → copy → repoint how size vs capacity drives CPython’s over-allocation strategy why append() is amortized O(1), even though resizes are sometimes O(N) why insert() / delete-from-middle are O(N) due to shifting how the list is structured (metadata “head” […]

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Try signing up for any SaaS product right now. You’ll click buttons, fill forms, verify your email, maybe solve a CAPTCHA. Takes 30 seconds, no big deal. Now imagine you’re an AI agent. You don’t have a browser. You don’t have fingers. You don’t have an email inbox. That 30-second flow? It’s a wall. This is the state of the agentic internet in 2026. Agents can discover tools via MCP. They can pay for things via x402. They […]

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