Andrej Karpathy shares his experience with Claude coding over the past few weeks, noting a dramatic shift in his development workflow. He describes moving from roughly 80% manual coding with autocomplete and 20% agent-assisted coding in November to an inverted ratio of 80% agent coding with only 20% manual edits and touchups by January 2026.
The post reflects a broader trend among developers rapidly adopting LLM-powered coding agents as their capabilities have improved significantly. Karpathy's firsthand account underscores how quickly AI-assisted development is becoming the dominant workflow for experienced programmers, signaling a major shift in software engineering practices.
A developer working in a corporate environment using GitHub Copilot asks the Reddit community what AI coding tools are worth exploring in 2026, noting that Copilot's agent mode with model switching (e.g., Claude Opus) already handles full end-to-end tasks including frontend/backend implementation, MCP server connections, and multi-step orchestration. The discussion centers on whether tools like Cursor, Claude Code, Codex, and Gemini CLI offer meaningful advantages beyond what Copilot now provides.
Commenters draw important distinctions between inline completion and agentic task-level tools. Several users highlight Claude Code as the standout for complex refactors and multi-file navigation, citing its 80.8% SWE-bench score and features like skills, hooks, and subagents. Cursor receives praise for its sub-agent orchestration and unlimited Auto mode at $20/month. For corporate environments prioritizing privacy, open-source BYOK tools like Aider and OpenCode are recommended, allowing teams to bring their own API keys without routing data through third-party infrastructure.
A recurring theme is the emergence of planning and tooling workflows — tools like GSD (Get Shit Done) and BMAD that layer structured planning on top of CLI agents, enabling a discuss-plan-execute-verify loop. Multiple users emphasize that the real productivity gains come not from better autocomplete but from terminal-based agents that can edit files, run tests, and iterate autonomously, with some developers reporting they no longer use traditional IDEs at all.
OpenAI Developers highlights the integration of GPT-5.4's computer use and coding capabilities with developers. The post showcases a browser game built using the Playwright skill in Codex, emphasizing how the tool can be used for playtesting and iterative game development. This demonstrates OpenAI's continued push toward agentic coding workflows where AI models can directly interact with browsers and development environments to build and test software autonomously.
Aaron Levie, CEO of Box, observes a significant shift in software pricing dynamics driven by AI. He notes that traditional software has typically been priced between $10–50 per user per month, but AI coding agents are already commanding prices reaching thousands of dollars per month. He frames this as a "revealed preference" — meaning users are demonstrating through their spending that the value delivered by these tools justifies the dramatically higher cost.
Levie suggests that AI coding possesses unique qualities enabling it to scale rapidly, though the full thread elaborating on these qualities is truncated in this excerpt. The observation highlights a potential inflection point in how software is valued and monetized, shifting from seat-based commodity pricing to outcome-based or value-based pricing as AI agents deliver substantially more productivity per dollar spent.