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Dev Interrupted

Agentic AI: Dissecting the Future of AI Workflows | Memra's Founder Amir Behbehani

17 Sep 2024

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Engineering teams are already seeing efficiency gains by leveraging Gen AI solutions like Copilot, but the next wave of AI workflows has the potential to 10X productivity.This week, we’re exploring the world of Agentic AI with Amir Behbehani, Chief AI Engineer and Founder of Memra. Agentic AI can be defined as AI agents or systems that have the capacity to make decisions or take actions on their own based on the objectives they are programmed to achieve. These AI systems act independently, gathering information, processing it, and then choosing or executing actions without direct human intervention.Amir shares how Memra is leading the way in developing AI agents capable of handling complex tasks, decision-making, and improving productivity across industries. He also discusses the implications of AI in reshaping how businesses operate, and how organizations can prepare for a future where AI plays a central role in both day-to-day operations and high-level strategic decisions.Whether you're an AI enthusiast, an engineering leader, or curious about the future of automation, this episode offers a deep dive into the possibilities and challenges of Agentic AI and what it means for the future of work.Chapters:01:23 Defining Agentic AI 07:02 Frameworks for thinking about Agentic AI 12:52 Unpacking AI as a black box 13:58 How Agentic AI will benefit software engineers 22:55 What would be a good starting point to leverage agents on an engineering team?26:46 Will agents replace freelancers and the gig economy?36:20 What is the synthetic marketplace?40:11 How Agentic AI impacts writing codeLinks:Supercharge Your Operations with AI-Powered Agents | MemraAmir BehbehaniManaging Bot-Generated PRs & Reducing Team Workload by 6%OFFERS Start Free Trial: Get started with LinearB's AI productivity platform for free. Book a Demo: Learn how you can ship faster, improve DevEx, and lead with confidence in the AI era. LEARN ABOUT LINEARB AI Code Reviews: Automate reviews to catch bugs, security risks, and performance issues before they hit production. AI & Productivity Insights: Go beyond DORA with AI-powered recommendations and dashboards to measure and improve performance. AI-Powered Workflow Automations: Use AI-generated PR descriptions, smart routing, and other automations to reduce developer toil. MCP Server: Interact with your engineering data using natural language to build custom reports and get answers on the fly.

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