6 Engineers, 10× Speed: Fix the Process, Not the Tool
6 elite devs spill AI workflows that 10× output—no new tools, just smarter process. Steal their guardrails, prompts & tool stack now.
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Yash Poojary: Balancing Execution and Exploration Through a Dual-Mode Approach
Core Strategy: Balance delivery and experimentation through a morning execution, afternoon exploration pattern. Mornings focus exclusively on core tasks using mature tools (Codex, Claude Code); afternoons are reserved for testing new tools.
Tool Stack:
Comparative Testing: Run Claude Code and Codex simultaneously on two machines (Mac Studio + laptop).
Figma MCP: Claude can directly connect to Figma files, read design systems, and generate code.
Warp: A modern command-line tool.
AgentWatch (Self-developed): Sends alerts when Claude Code sessions complete, enabling simultaneous running of multiple sessions.
Workflow:
Design to Code: Direct integration through Figma MCP, allowing Claude to read design systems and convert them to code.
Context Management: When using Warp, maintains learning documentation to provide AI with recent context.
Preventing Deviation: Strictly divides tasks and sets guardrails to avoid being led astray by AI suggestions.
He discovered that Claude Code plays the role of a “friendly developer.” This model’s strength lies in its ability to break down complex problems and clearly explain the reasoning behind its approach. This makes Claude Code highly suitable for exploratory tasks, understanding legacy code, or learning new programming paradigms. It’s more like a pair programming partner, emphasizing process and understanding.
In contrast, Codex is a “technical developer.” Its characteristic is being more literal and precise, not (particularly) adept at explaining, but tends to provide technically correct solutions on the first attempt. This makes Codex the preferred tool for executing clear, well-defined tasks, where its value lies in speed and accuracy. Yash’s workflow has become more intelligent as a result: he selects the appropriate AI “colleague” based on the nature of the task (whether it requires exploration or execution).
