Coding Was Never the Hard Part: What I Wish Every Business Leader Knew About AI
The article explains that while AI tools are improving coding efficiency, they address only a small portion of the engineering workflow, as most of the work involves problem-solving, planning, and maintenance rather than writing code. It emphasizes that business leaders often misunderstand engineering as task-based, when it actually follows a scientific, iterative process. The author argues that AI's impact on overall productivity is limited unless it supports the broader engineering lifecycle, not just the coding phase.
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Engineering LeadershipAISoftware Engineering Coding Was Never the Hard Part Posted on April 28, 2026 by Koushik Dasika · 17 min read What I Wish Every Business Leader Knew About AI and LLMs Image credit: CommitStrip There’s a lot of excitement right now about AI making software development faster. Agentic coding is real, Claude Code, OpenAI Codex, and Gemini are real, and so are the open source alternatives running locally via Ollama: DeepSeek, Qwen, Gemma, Llama, and more. The productivity gains are real [1]. The marketing around these tools promises that they solve everything. And in the background, AI is getting blamed — or credited, depending on who you ask — for a wave of engineering layoffs.
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