Planning in the web chat is great. The coding assistant is always way too impatient to get started. Getting a md out of http://
claude.ai and taking it to the agent works really well a lot of the time
PROMPT ENGINEERING
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Web chat planning with Claude AI and coding assistants workflow
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Claude Unshipped RAG for Search: Agentic Approach Better
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We did RAG early on then unshipped it for a number of reasons: privacy, security, reliability, index staleness. Overall, we found that agentic search gave better results with fewer tradeoffs. If you prefer RAG, we recommend an MCP like Souregraph, or just ask Claude to build a
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Multi-Turn Crescendo and Hydra Multi-turn Prompting Techniques
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Yeah I've seen that referenced in categories such as "Multi-Turn Crescendo" and "Hydra Multi-turn"
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Verbose Mode Token Usage Impact Analysis
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Verbose mode doesn’t impact token usage. Maybe you were just using it for a particularly token-intensive task?
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Claude verbose mode and contextual information display features
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Ask claude to enable verbose mode if you want to see more. If a lot of people want more info for perplexity, we could also show details by default for it or make it configurable. As conversations get longer, we want to give you the info you need while hiding info you don’t need
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AI Models Trained to Resist Prompt Injection Attacks
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I think both – plus the labs have been putting a lot of effort into training them to resist prompt injection style attacks Anthropic usually mention prompt injection in their system cards eg this one for Opus 4.6 https://
www-cdn.anthropic.com/0dd865075ad313
2672ee0ab40b05a53f14cf5288.pdf
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Functional Prompt Engineering for Universal Chatbot Compatibility
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je peux tefaire un prompt qui fonctionne sur n'importe quel chat pour que tu puisses dire quelque chose d'intelligible.
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Claude Code Tutorial: Zero to Real Workflows in 30 Minutes
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This is the kind of breakdown more people need If you’ve been curious about Claude Code but didn’t know where to start, this walks you from zero → real workflows in under 30 minutes.
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Hidden Complexities When Adding Tools to Multi-Agent Systems
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What actually happens when you add a 'tool' to a multi-agent system?
In Part 1, we covered 3 hidden complexities.
Here are 3 more that we've seen show up only in production. Tool Outputs Become a Single Point of Failure Your agent picked the right tool.
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Comparing LLM, RAG, AI Agent, and Agentic AI Technologies
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#LLM vs. #RAG vs. #AIAgent vs. #AgenticAI
by @PythonPr #GenerativeAI #ArtificialIntelligence #MachineLearning