@grok redo this image but it's Thierry Breton showing off a laptop and saying "wow this is an impressive piece of innovation"
PROMPT ENGINEERING
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Context engineering is the new bottleneck
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the broader observation matters more than this specific paper. context engineering is quietly becoming the real bottleneck. not model capability, not training data, not inference cost. the unglamorous plumbing of what information reaches the model, when, and how. Anthropic
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Three-Stage Pipeline Between Filesystem and Token Window
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between the filesystem and the token window sits a three-stage pipeline. the context constructor selects and compresses context from the filesystem into a token-budget-aware input. it queries recency and relevance metadata, applies summarization, and produces a manifest
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Three Tiers of Persistent Context Explained
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the paper defines three tiers of persistent context, each with different lifecycles. scratchpads (/context/pad/) are temporary working notes scoped to a task. think of them as the agent's rough draft space. episodic memory (/context/memory/episodic/) holds session-bounded
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Agent frameworks’ context handling flaws
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the problem is real and underappreciated. right now, most agent frameworks handle context like this: load memory at session start. stuff it into the prompt. when the window fills, summarize and compress. hope the important parts survive. the paper calls this out directly. once
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Unix principle applied to AI context
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"everything is a file" becomes "everything is context." CSIRO Data61 and ArcBlock published a paper applying the oldest Unix principle to the newest AI problem. they propose treating memory, tools, knowledge, and human input as a mounted filesystem that agents browse at runtime
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QueryWeaver GitHub Project Promotes AI-Related Categories
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QueryWeaver GitHub: (don't forget to star )
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Open-Source Text-to-SQL Solution Tackles LLM and Schema Issues
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Finally! A Text-to-SQL solution that actually works!
— Akshay 🚀 (@akshay_pachaar) 2 mars 2026
(and it's open-source)
When Text-to-SQL doesn’t work, we often blame the LLM or poor prompt engineering.
But the real issue is usually the schema.
Let me explain:
You ask: “Which publishers have received royalty payments… pic.twitter.com/OCa7S8Z3v0Finally! A Text-to-SQL solution that actually works! (and it's open-source) When Text-to-SQL doesn’t work, we often blame the LLM or poor prompt engineering. But the real issue is usually the schema. Let me explain: You ask: “Which publishers have received royalty payments
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Understanding Temperature in AI Models: Beyond Creativity vs. Determinism
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Great breakdown! One thing worth adding: temperature isn't just about creativity vs. determinism. It fundamentally reshapes the probability distribution over the entire vocabulary. A practical tip: instead of jumping straight to high temperature for 'creativity,' try
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Free Anthropic courses on Claude with certificates
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stop satisfying yourself with random youtube tutorials. Anthropic just released free courses on building with Claude. with certificates. prompt engineering, tool use, RAG, evaluations. built by the people who made the model. not some influencer who read the docs once. $0.00.