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Aakash Sharan
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Category: Agentic AI

Deep explorations of agent behavior, SRAL analysis, failure patterns, and the architectural foundations of autonomous AI systems. Understanding what agents do and why they fail.

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Posts in Agentic AI

Applying SRAL to LangChain: An Architectural Evaluation

Applying SRAL to LangChain: An Architectural Evaluation

A systematic evaluation of LangChain's architectural foundations using the SRAL framework Scorecard Summary Component Score Key Finding State ⚠️ Weak-to-Moderate Memory is optional, not architectural....

Agentic AI
02/01/2026
PART II — ReAct: The Architecture That Unified Agentic Reasoning

PART II — ReAct: The Architecture That Unified Agentic Reasoning

Most discussions of ReAct frame it as a clever prompting technique. It isn’t. ReAct is the first time we gave language models a structure for...

Agentic AI
19/12/2025
Machine Learning Types Are the Wrong Abstraction for Agentic Systems

Machine Learning Types Are the Wrong Abstraction for Agentic Systems

Executive Summary We still classify machine learning systems by how they are trained. Supervised. Unsupervised. Reinforcement learning. That taxonomy made sense when models were static....

Agentic AI
14/12/2025
PART I — Why Most Agents Fail: The Architectural Blind Spots Behind CoT and Tool-Only Models

PART I — Why Most Agents Fail: The Architectural Blind Spots Behind CoT and Tool-Only Models

Modern agent demos look impressive until you load them with real work. Real constraints. Real ambiguity. Real environments. That’s when most agents collapse. And the...

Agentic AI
12/12/2025

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