newsletterAugust 3, 2026·Towards Data Science

How to Build CLI Agents with Python & Ollama

Create a local CLI Agent from scratch completely for free The post How to Build CLI Agents with Python & Ollama appeared first on Towards Data Science.

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•Create a local CLI Agent from scratch completely for free The post How to Build CLI Agents with Python & Ollama appeared first on Towards Data Science.
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Prompt, Context, Loop: The Three Engineering Layers Every RAG System Is Built On

Enterprise Document Intelligence [Vol.1 #M2] - Every RAG system is built in three engineering layers stacked on one LLM call: prompt (the call itself), context (what fills the model’s window), loop (when the next call fires and when it stops). Knowing which layer you are standing on is half of build

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Import AI 467: Self-sustaining AI viruses; pacing AI progress; confusion about AI and creativity

Welcome to Import AI, a newsletter about AI research. Import AI runs on arXiv, cappuccinos, and feedback from readers. If you’d like to support this, please subscribe. Subscribe now Self-sustaining and self-replicating AI viruses are here:…Open weight LLMs + a well-designed harness = a persistent, s

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The AI Was the Easy Part: What Is a Forward-Deployed Engineer in a Supply Chain?

What actually makes a Forward Deployed Engineer, told through one supply chain project. The post The AI Was the Easy Part: What Is a Forward-Deployed Engineer in a Supply Chain? appeared first on Towards Data Science.

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How Claude Help Me Build My $200k+ ML Resume

How use Claude to craft an outstanding resume that lands offers The post How Claude Help Me Build My $200k+ ML Resume appeared first on Towards Data Science.

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How to Build CLI Agents with Python & Ollama

Key Takeaways

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Prompt, Context, Loop: The Three Engineering Layers Every RAG System Is Built On

Import AI 467: Self-sustaining AI viruses; pacing AI progress; confusion about AI and creativity

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How Claude Help Me Build My $200k+ ML Resume

Discussion

How to Build CLI Agents with Python & Ollama

Key Takeaways

Related Articles

Prompt, Context, Loop: The Three Engineering Layers Every RAG System Is Built On

Import AI 467: Self-sustaining AI viruses; pacing AI progress; confusion about AI and creativity

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How Claude Help Me Build My $200k+ ML Resume

Discussion

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Prompt, Context, Loop: The Three Engineering Layers Every RAG System Is Built On
Enterprise Document Intelligence [Vol.1 #M2] - Every RAG system is built in three engineering layers stacked on one LLM call: prompt (the call itself), context (what fills the model’s window), loop (when the next call fires and when it stops). Knowing which layer you are standing on is half of build

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Import AI 467: Self-sustaining AI viruses; pacing AI progress; confusion about AI and creativity
Welcome to Import AI, a newsletter about AI research. Import AI runs on arXiv, cappuccinos, and feedback from readers. If you’d like to support this, please subscribe. Subscribe now Self-sustaining and self-replicating AI viruses are here:…Open weight LLMs + a well-designed harness = a persistent, s

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The AI Was the Easy Part: What Is a Forward-Deployed Engineer in a Supply Chain?
What actually makes a Forward Deployed Engineer, told through one supply chain project. The post The AI Was the Easy Part: What Is a Forward-Deployed Engineer in a Supply Chain? appeared first on Towards Data Science.

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How Claude Help Me Build My $200k+ ML Resume
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