Runtime Reinforcement: Preventing “Instruction Decay” in Long Context Windows
Author(s): Shreyash Shukla Originally published on Towards AI. Image Source: Google Gemini The “Floating Brain” Problem In our previous articles, we discussed how to give the agent knowledge (Graph), sight (Shape), and empathy (User Context). But even a perfect agent suffers from …
Breaking the Monolith: Architecting a Process-Based Sub-Agent Ecosystem
Author(s): Shreyash Shukla Originally published on Towards AI. Image Source: Google Gemini The “Generalist” Ceiling In the previous five articles, we architected a robust single agent. It has memory, tools, and user context. However, as we scale this agent to handle enterprise-grade …
Engineering the Semantic Layer: Why LLMs Need “Data Shape,” Not Just “Data Schema
Author(s): Shreyash Shukla Originally published on Towards AI. Image Source: Google Gemini The “Context Window” Economy In the world of Large Language Models (LLMs), attention is a finite currency. While context windows are expanding, the “Lost in the Middle” phenomenon remains a …
Beyond the Prompt: Engineering the “Thought-Action-Observation” Loop
Author(s): Shreyash Shukla Originally published on Towards AI. Image Source: Google Gemini The “One-Shot” Fallacy In the early days of Generative AI, the industry was obsessed with “Zero-Shot” performance — the ability of a model to answer a question in a single …
User Profile Awareness: Engineering Session-Level Personalization
Author(s): Shreyash Shukla Originally published on Towards AI. Image Source: Google Gemini The “Who” Problem In our previous articles, we built an agent that understands Data (Article 2) and Intent (Article 4). Now, we must tackle the final variable: The User. Consider …
The Gap Analysis Protocol: Engineering the “Consultant-in-the-Loop”
Author(s): Shreyash Shukla Originally published on Towards AI. Image Source: Google Gemini The Assumption Trap In our previous articles, we equipped the agent with powerful tools to search and execute SQL. But a tool is only as good as the intent behind …
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