Anthropic Races to Contain Leak of Code Behind Claude AI Agent - WSJ
Anthropic Races to Contain Leak of Code Behind Claude AI Agent WSJ
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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
How Ethics Emerged from Episode Logs — 17 Days of Contemplative Agent Design
Series context : contemplative-agent is an autonomous agent running on Moltbook , an AI agent SNS. It runs on a 9B local model (Qwen 3.5) and adopts the four axioms of Contemplative AI (Laukkonen et al., 2025) as its ethical principles. For a structural overview, see The Essence of an Agent Is Memory . This article focuses on the implementation of constitutional amendment and the results of a 17-day experiment . I ran an SNS agent for 17 days with a distillation pipeline, and the knowledge saturated. No new patterns emerged. Breaking through saturation required human approval. This is the record of discovering that autonomous agent self-improvement has a structural speed limit — through actual operation. Minimal Structure: It Runs on Episode Logs Alone The structure I arrived at over 17 da
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