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Context Management in Amp
Learn how to get the most out of the context window in Amp, with the least amount of work.
Design Pattern
Tool
Building a Coding Agent in Rust: Introduction | 0xshadow's Blog
Setting up the coding agent rust project with Gemini API
TutorialSelf-Evolving Agents - A Cookbook for Autonomous Agent Retraining
Agentic systems often reach a plateau after proof-of-concept because they depend on humans to diagnose edge cases and correct failures. T...
Prompt Learning
Design Patterns for Securing LLM Agents against Prompt Injections
As AI agents powered by Large Language Models (LLMs) become increasingly versatile and capable of addressing a broad spectrum of tasks, ensuring their security has become a critical challenge. Among the most pressing threats are prompt injection attacks, which exploit the agent's resilience on natural language inputs -- an especially dangerous threat when agents are granted tool access or handle sensitive information. In this work, we propose a set of principled design patterns for building AI agents with provable resistance to prompt injection. We systematically analyze these patterns, discuss their trade-offs in terms of utility and security, and illustrate their real-world applicability through a series of case studies.
Paper
Strategy
Ebook
Context Engineering 2.0: The Context of Context Engineering
Karl Marx once wrote that ``the human essence is the ensemble of social relations'', suggesting that individuals are not isolated entities but are fundamentally shaped by their interactions with...
PaperThe Era of Agentic Organization: Learning to Organize with Language Models
We envision a new era of AI, termed agentic organization, where agents solve complex problems by working collaboratively and concurrently, enabling outcomes beyond individual intelligence. To...
Paper
Vibe CodingLegesse AI Enhanced Requirements Traceability Using MBSE LLM Complex Systems
Requirement EngineeringAgent Engineering 101
A practical guide to Agent Engineering: the intersection of software, systems and security engineering.
Concept
Bitter lessons building AI products | Hex
Our AI visualizations worked 'pretty good'—which turned out to be the problem. Here's what we learned about building products during a massive technology shift, and why we now ship early, kill projects faster, and retry failed ideas every few months
Designing APIs for vibe coding
Developer experience in the age of vibe coding
Shift
SWE.1 – Software Requirements Analysis
Welcome in 2021,I know its already been some months but I hope you had a good and motivated start into the new year. What could be better than starting by reading the newest blog post about “…
Multi-agent AI system in Google Cloud | Cloud Architecture Center
Design robust multi-agent AI systems in Google Cloud.
Design Pattern
A Guide on 12 Tuning Strategies for Production-Ready RAG Applications
Strategies and parameters you can tune to improve the performance of Retrieval-Augmented Generation (RAG) applications for production.
Design Pattern
Building LangGraph: Designing an Agent Runtime from first principles
In this blog piece, you’ll learn why and how we built LangGraph for production agents—focusing on control, durability, and the core features needed to scale.
Deep Dive
Tutorial
Context Engineering in Manus
Manus approaches to context engineering.
AI Enhanced Requirements Traceability Using MBSE LLM Complex Systems
Challenges in applying large language models to requirements engineering tasks
Generating Requirements for ADAS Cameras Using an LLM-Based Approach