Handling Context When Building Complex Agentic Systems @ai-science
Handling Context When Building Complex Agentic Systems  @ai-science
Uploaded December 2025 | Updated September 2026, 2 weeks ago
Managing context is one of the hardest problems in complex, agentic AI systems. In this video, I share practical techniques that actually work: start with a manual dry run in ChatGPT or Gemini, then ask the model to reverse-engineer the ideal prompt that would have produced the result. Learn why letting LLMs help design better prompts reduces hallucinations, how to transform human-language outputs into agent-ready structured inputs, and how selective context injection (toggling what agents see) improves performance.


#AgenticAI #LLM #ContextManagement #MultiAgentSystems #PromptEngineering #AIEngineering #GenAI #ArtificialIntelligence
Handling Context When Building Complex Agentic Systems​Diving Into Document Question and Answering Systems with LLMsWhat is the relationship between language and intelligence?Before Building an AI Agent, answer these Questions.The Tension Between AI Governance and InnovationStrengths, Challenges, and Problem Formulation in RLWhat Comes After RAG?  The Future of Knowledge Work with LLM AgentsKey Learnings from Building AI Agents: How Open Source Shaped Our ArchitectureRelationship between Reasoning and CausalityUsing Open Source Framework Versus Industry Standard Like LangChainBuilding Software with AI: Why a Simple Task Can Go WrongXAI for LLMs: looking under the hood of Large Language Models
LLMs Explained - Aggregate Intellect - AI.SCIENCE |

Handling Context When Building Complex Agentic Systems

SHARE TO X SHARE TO REDDIT SHARE TO FACEBOOK WALLPAPER