Samsung Takes Its Browser Beyond Mobile, Extending Agentic AI Across Devices - samsung.com
<a href="https://news.google.com/rss/articles/CBMilwFBVV95cUxPcmZCaVBpVUNQdE5LOU4tdjB0RkJjSlB6OFBaZDRUQW1LN29wVVJETTZhQ205YzdQTTdxeGdPWTdJNXVXbGpIa0h3cUNvdUdnMzJySlp1ZkoxQ0JHdGFoN19kTW1kT1VCY2xqNDdPUV9ZTFlidmtMSC04MVNsdGJVdFBaa2VKRHdmcFc2ZWt1M0dfd1VxLU93?oc=5" target="_blank">Samsung Takes Its Browser Beyond Mobile, Extending Agentic AI Across Devices</a> <font color="#6f6f6f">samsung.com</font>
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Cortex Code in Snowflake: How to Use It Without Burning Credits
Snowflake Cortex Code (CoCo) is like an AI assistant inside Snowsight (and CLI also). You can ask it to write SQL, create dbt models, explore data, help in ML work, and even do some admin tasks. But one thing people don’t realise early — this tool is powerful, but also costly if used wrongly. Bad prompts → more tokens → more credits → surprise bill. Prompt Engineering (this directly impacts cost) CoCo works on token consumption. what you type → counted 2. what it replies → counted If your prompt is vague → more tool calls → more cost. Example: Bad: Help me with my data Good: Create staging model for RAW.SALES.ORDERS with not_null on ORDER_ID Best Practices: Use full table names 2. Be clear about output 3. Keep prompts small 4. Provide business logic upfront 5. Use AGENTS.md for consistency
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