Tech News
I think I have LLM burnout
A developer describes LLM burnout from constant pressure to use AI-generated outputs, while another user notes frustration with AI companies downgrading models to cut costs.
Rewriting Bun in Rust
Jarred Sumner has been promising this blog post ( since May 9th ) about his Zig to Rust rewrite of Bun for significantly longer than it took him to finish the rewrite. Honestly, it was worth the wait. This is a detail.
Building and connecting a production-ready ecommerce MCP server using Amazon Bedrock AgentCore and Mistral AI Studio
In this post, you build and connect that server end to end. You will implement MCP tools, set up two-layer JSON Web Token (JWT) authentication, deploy with AWS Cloud Development Kit (AWS CDK), and connect the result.
Create a LangChain Deep Agents Harness Profile for NVIDIA Nemotron 3 Ultra to Improve Performance
Agentic systems often face a trade-off between accuracy and cost. The highest-performing proprietary frontier models and harnesses provide top accuracy but are.
Data for Agents
NVIDIA released a dataset to improve agentic AI performance by providing structured training data for tool use and reasoning.
GitHub Repos
code-yeongyu/oh-my-openagent
omo/lazycodex: The coding agent for tokenmaxxers;the one and only agent harness for complex codebases.
# TypeScript# ai# ai agentssickn33/agentic-awesome-skills
Installable GitHub library of 1,935+ agentic skills for Claude Code, Cursor, Codex CLI, Autohand Code, Gemini CLI, Antigravity, and more.
# Python# agent skills# agentic skillsascending-llc/jarvis-registry
Connect any AI copilot or autonomous agent to your enterprise tools — through a single, secure MCP/Agent gateway with built-in identity, access control, and full observability.
# Python# agent# agent gatewayResearch Papers
TimEE: End-to-end Time Series Classification via In-Context Learning
TimEE is a small 4.5M-parameter model that classifies time series in one forward pass using in-context learning, trained only on synthetic data, yet performs competitively on real-world benchmarks.
SpaCellAgent: A Self-Evolving LLM-Based Multi-Agent Framework for Trajectory Analysis
SpaCellAgent uses multiple LLM agents to automate trajectory analysis in spatial transcriptomics, reducing manual effort by 40% while maintaining expert-level accuracy.
InductWave: Inductive Multi-Hop Logical Query Answering on Knowledge Graphs
Logical Multi-Hop Query Answering over Knowledge Graphs (KGs) can be formulated as querying, with an implicit completeness assumption. Current works mainly focus on Existential First Order Logic (EFO) queries.