Goblin Chieftan Rags. There was some discussion on the TWI Discord as to whether or not Rags is asexual or just rigidly focused on being the Chieftan. But here she is with an Ace pennant tied to her crossbow bolt.

18x Replay:
https://www.youtube.com/watch?v=U70vG4xLsO0

YT Short:
https://youtube.com/watch/diq76OZVnkU?si

#drawing #thewanderinginn #rags #ace #MastoArt

The workers: https://www.aurianneor.org/the-workers/

#art #automation #blockades #chain #cooperatives #decentwork #deplorables #destruction #developingcountries #dictatorship #environment #factory #fairtrade #islandbuilding #Kaizen #labor #manufacturing #millions #miner #organic #Photomontage #politics #poor #quality #rags #remuneration #reputation #rich #shareholders #social #sovereignty #struggle #ThirdWorld #toothless #uberization #UN #wage #workers #workingconditions #workingpoor

"Context engineering goes beyond earlier approaches to refining agent behavior in software development, such as prompt engineering or retrieval-augmented generation (RAG). The latter primarily helps AI retrieve one-off documents when generating a response.

At a technical level, context engineering boils down to which information and tools you expose to the large language model (LLM) at the heart of an agent. This helps the LLM enrich its responses and programmatically decide its next course of action.

The easiest way to enact context engineering is by using system prompts. These are found in most AI tools and accept instructions that help define an agent’s role, goals, and constraints. System prompts can also include few-shot examples that demonstrate target input and output behaviors.

According to experts, establishing context for AI agents involves a mix of structured and unstructured data types. Core areas include:

- System behaviors: code and documentation.
- System architecture: database schemas and deployment configurations.
- Code events: commits, pull requests, and review threads.
- Error information: tickets, failure logs, build output, and feedback from linters or compilers.
- Rationale: chat histories and design documentation.
- Business rules: compliance policies and operating procedures.
- Team behaviors: common workflows and execution patterns.

“This data is used to inform reasoning, guide execution, align with goals, and enable adaptive learning,” said Babak Hodjat, chief AI officer at Cognizant, an IT consulting company that recently announced plans to deploy over 1,000 context engineers within the next year."

https://leaddev.com/ai/what-is-context-engineering

#AI #GenerativeAI #LLMs #RAGs #ContextEngineering #PromptEngineering

Found this quote in the opening of Paper-Making by Jules Heller:

RAGS make paper,
PAPER makes money,
MONEY makes banks,
BANKS make loans,
LOANS make beggars,
BEGGARS make
RAGS.

What a great start to a book on making paper by hand.

#papermaking #rags #quotes

🇺🇦 #NowPlaying on #BBC6Music's #BLOCKPARTYWithHueyMorgan

Rags:
🎵 Ice (feat. Bambi)

#Rags

https://mikegalbraith.bandcamp.com/track/ice-box

"Without clear signposting, an agent might miss your API entirely. If it does discover it, large language models (LLMs) may stumble with undocumented behaviors, hallucinate methods or flood your servers with random calls.

So, it’s important to get it right. Thankfully, strategies are emerging to position APIs for AI agents, from new standards to underground tricks. And, it’s more than just “get an MCP server” (though that’s a crucial step).

The jury’s out on what strategy will be most effective. So I’ve structured this guide to start with broadly agreed-upon best practices, then explore ones still taking shape. Most tips apply equally to public, partner and private APIs."

https://thenewstack.io/how-to-prepare-your-api-for-ai-agents/

#AI #GenerativeAI #AIAgents #AgenticAI #LLMs #API #OpenAPI #RAGs #MCP