25:26
From MCP to Scale: Pipelines That Build Themselves — Rafael Levi, Bright Data
In this AI Engineer conference session, Rafael Levi from Bright Data demonstrates how to build self-maintaining web scraping pipeline...
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16:30
SWE-rebench: Lessons from Evaluating Coding Agents — Ibragim Badertdinov, Nebius
Ibragim Badertdinov, an AI researcher at Nebius with an unconventional background—a trained dentist turned NeurIPS and ICML author—pr...
16:32
How to Actually Use Claude Code Dynamic Workflows
Nate Herk provides one of the most practical breakdowns available of Claude Code's dynamic workflows feature, introduced alongside Cl...
08:23
Claude Opus 4.8 Just Made AI Agents Reliable
Stephanie Nyarko examines Claude Opus 4.8 through its benchmark performance, pricing structure, and practical positioning relative to...
31:40
Picking the right model
Lucas from Anthropicʼs applied AI team delivers a practical framework for selecting the right Claude model in production — addressing...
29:53
AI Dev 26 x SF | David Park: Building Production Grade Agentic Systems with ADE
David Park, head of applied AI engineering at Landing AI, presented at AI Dev 26 in San Francisco on the architectural principles beh...
43:17
Every Claude Cowork Feature Explained for Normal People
Ben AI delivers a structured feature-by-feature walkthrough of Claude's Co-work environment, organized into three categories: memory...
19:42
AI with Claude on AWS: From code to orchestration
AWS developer advocate Antonio Rodriguez presents a hands-on session on deploying Claude applications to production on Amazon Web Ser...
19:22
Replacing 12K LoC with a 200 LoC Skill — David Gomes, Cursor
David Gomes, an engineer at Cursor, delivers a conference talk explaining how the team replaced approximately 15,000 lines of code po...
40:52
The Ultimate Non-Technical Guide to Claude Code
Futurepedia's comprehensive walkthrough positions itself as the definitive non-technical guide to Claude Code, Anthropic's agentic co...