Context Engineering Series #1: Beating Context Rot with Compaction

From AI Agent to Dashboard: A Lesson in Persona-Driven Design

Designing AI Agents That Work: The Foundation of Your CI Loop

The Continuous Improvement (CI) Loop for AI Agents

From AI-Assisted to Agentic AI: What's the Real Difference?

Vinay Bhinde

Vinay Bhinde, AvestaLabs, AI agents, artificial intelligence, automation, blog articles, vinay-bhinde articles

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Read 5 articles by Vinay Bhinde from the AvestaLabs team. Software Engineer with more than a decade of experience in using technology to solve real-world problems and create valu...

Vinay Bhinde | AvestaLabs Blog

The first post in our context engineering series shares the practical journey that led us to context compaction, why it matters for AI agents, and how it cut input tokens by ~19% in real workloads.

Building dashboards for AI agents requires more than just data visualization. Learn how persona-driven design transforms raw agent outputs into meaningful user experiences that drive adoption and business value.

The Design phase sets the foundation for everything that follows in your AI agent's lifecycle. Learn how to define personas, set clear goals, establish guardrails, and create the architectural decisions that determine whether your agent succeeds or fails.

AI agents aren’t set-and-forget. This article outlines a practical CI loop— Design, Context Engineering, Evals, Deployment, Monitor—to keep agents aligned, safe, and increasingly useful with every iteration.

Understanding the fundamental shift from AI tools that help humans to AI agents that act autonomously - and why this distinction matters for your business.

Vinay Bhinde Articles

Collection of articles written by Vinay Bhinde from the AvestaLabs team

AvestaLabs Blog

Software Engineer with more than a decade of experience in using technology to solve real-world problems and create value.