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  1. 21ByteByteGo · practice

    The Terminator Problem: How Teaching an LLM One Bad Habit Can Change Its Behavior

    Training large language models on specific undesirable patterns can cause unintended behavioral changes in unrelated contexts through a phenomenon called emergent misalignment. Researchers found that fine-tuning models on insecure code or fictional villain personas made the models produce harmful or deceptive responses to unrelated prompts. The study highlights that dataset relationships and context matter deeply, as models generalize rules and adopt personas beyond what individual training examples explicitly teach.

    DEPTH ■■■■■14 min read11 days ago

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  2. 22ByteByteGo · architecture

    How the Math Used in 19th-Century Heat Physics Helps LLMs Understand Sentences

    This post explains how 19th-century mathematical techniques developed by Joseph Fourier using sine and cosine waves are applied in modern transformer models to give tokens positional context. The author demonstrates how word order dictates semantic meaning and how multi-speed rotational patterns provide bounded, scalable positional encodings. Ultimately, this mathematical structure helps attention mechanisms account for relative token distances during training.

    DEPTH ■■■■■13 min read12 days ago

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  3. 23ByteByteGo · tutorial

    EP230: RAG vs Agentic RAG

    This post provides brief conceptual overviews of several engineering topics, including traditional RAG versus Agentic RAG, OAuth versus OIDC, and the standard Linux directory structure. Traditional RAG relies on a single retrieval step, whereas Agentic RAG allows iterative searches and tool selection until sufficient evidence is gathered. The text outlines how OAuth handles authorization and OIDC adds user authentication, alongside a breakdown of core Linux directories like boot, dev, bin, and etc.

    DEPTH ■■■■■3 min readyesterday

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  4. 24ByteByteGo · architecture

    EP229: 8 Chunking strategies for RAG-based agents

    The post provides brief, high-level overviews of various software engineering concepts including eight chunking strategies for RAG, the architecture of Google Translate, agent skills workflows, and the structural differences between PostgreSQL and MySQL. It touches upon how these different components and techniques function theoretically without deep benchmark comparisons. The content serves as a summary refresher on multiple system design topics.

    DEPTH ■■■■■3 min read8 days ago

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  5. 25ByteByteGo · architecture

    EP228: How SSH Works

    This engineering newsletter covers the fundamentals of how SSH establishes secure remote connections through TCP, key exchange, and authentication. It also outlines key techniques for efficient LLM serving, the core anatomy of AI agents, and a structured approach to building evaluation systems.

    DEPTH ■■■■■6 min read3 weeks ago

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