planning mode
3 videos across 2 channels
Planning mode in AI development emphasizes structured, ongoing workflows for agentic systems, focusing on how to reuse existing tooling, translate domain knowledge, and invent new solutions. From three-part frameworks for legal work to an Agentic Development Life Cycle that treats deployment as continuous monitoring and adaptation, it highlights how non-deterministic agents require phased validation, governance, and multi-agent orchestration. The conversation also weighs real-world development needs—usability, memory, and debugging—against evolving planning strategies to keep systems safe, cost-effective, and responsive.
What legal agents inherit from coding agents: Lessons from Legora
A speaker from Legora explains how lessons from coding agents can be translated to legal work, outlining a three-part fr
ADLC: Claude Code's New Lifecycle for AI Coding
The video explains why traditional SDLC is inadequate for agentic AI systems and introduces the Agentic Development Life
It’s Broken… The Claude Code Vs Codex Debate Is Finally Over
The video pits Opus 4.7 against GPT 5.5 across usability, planning, building, debugging, memory, and agent capabilities