Unified Gemini Integration for LangChainJS Made by the LangChain Community Consolidates 6+ packages into @langchain/google. Simplifies authentication for AI Studio and Vertex AI with cross-platform support and LangChainJS 1.0 multimodal for Gemini 3. Alpha in early January
GENERATIVE AI
-
GLM-4.7 ranks 6th on AI Index
By
–
ICYMI: GLM-4.7 lands in 6th place on the Artificial Analysis Intelligence Index, surpassing Kimi K2.
-
Corporate hiring freeze driven by AI job replacement concerns
By
–
https://
wsj.com/economy/jobs/2
026-job-hiring-growth-plans-10bc3470?st=ti41CG
… via @WSJ The corporate playbook for next year? Don’t hire. "we’re not hiring because we’re waiting to try to figure out what happens with #AI. What jobs can we replace?"
#RiseoftheRobots -
OpenAI GPT5-Codex-Max Year End Recap Podcast
By
–
Good time to share that we're releasing some great end of year recap pods every day for your holiday listening! just posted: a great end of year convo recapping @OpenAI Codex and GPT5-Codex-Max with @bfioca and @realchillben
! -
Builders using Anthropic Claude are the future, not emotional support
By
–
Meanwhile all the smartest people I follow are posting about things they are building with Anthropic Claude. The builders are the future. Those who hang onto models for emotional support are not. I'd rather help the builders figure things out. And I know that makes me tone
-
Nostalgia for Sonnet 3.5: AI coding progress evolution
By
–
Do you remember how people losing their minds over Sonnet 3.5 for coding? What innocent times
-
Human-Machine Studies for Remarkable Product Design
By
–
If you want to design and develop a product successfully, utilize humachineology studies to realize what makes it remarkable.
-
Prompt engineering is about psychology, not precision
By
–
I used to think prompt engineering was about precision. It's actually about psychology. You're not instructing a computer. You're activating patterns in a language model trained on billions of human decisions, consequences, and stakes. Treat it like that.
-
Framing consequences for high-stakes LLM responses
By
–
Think about it: When you write an email to a friend → casual
When you write an email that could get you fired → every word matters LLMs learned from both types of text. By framing consequences, you're telling the model: "use the high-stakes mode." -
Why LLMs Respond to Stakes in Text
By
–
You would ask me…Why does this work bro? LLMs are trained on human text and human text is full of stakes. When you add consequences, you're not just giving instructions. You're activating the model's training on how humans think and write when something actually matters.