Outlines three generations: Gen 1.0 (autocomplete), Gen 2.0 (chat-based, agentic coding), and the anticipated Gen 3.0 (command-driven agent workflow)
Gen 1.0: Autocomplete offered productivity increase but wasn't transformative
Gen 2.0: Chat agents allowed more code generation, particularly empowering junior developers, but created code review challenges and quality concerns
Gen 3.0: The forthcoming shift is command-line control over agents, enabling comprehensive end-to-end workflows in the software development lifecycle (SDLC)
Differentiates "noobs" (new developers) and "enterprise" (experienced, complex environments)
For less experienced users, end-to-end can mean turn-key software generation
For enterprise, true value requires AI support for versatile, reliable workflows across the SDLC—code generation, testing, quality review, refactoring, etc.
Current tools offer siloed AI capabilities; the next game changer will holistically integrate workflows, especially red-team (review, quality, testing) processes
AI tools perform well in greenfield (brand new) projects, but struggle with large, legacy codebases due to maintainability, testing, and review demands
Codto aims to address these challenges holistically using a multi-agent architecture for research, code review, and best practices integration
Codto Multi-Agent Architecture and CLI Tool Demo 12:33
Brief overview of Codto agents: deep research agent, code review agent (codemerge), and context/best practice gathering (codaware)
The newly launched CLI tool is designed to integrate workflows and agents directly into developers' processes, with a soft launch announced during the talk
The CLI enables creation and customization of agents and workflows that automate research, code generation, coverage improvement, and code review tasks
Codto's CLI tool allows enforcement of organizational best practices, coverage criteria, and integration with pre-/post-commit hooks for confidence-inspiring development
CLI facilitates automatic generation of task-specific interfaces, reducing dependency on traditional IDEs
Friedman predicts a near future (2025–2026) where swarms of specialized agents, via flexible interfaces like CLI, will dominate advanced software development workflows