Ranking AI Agents for Coding: Strengths and Weaknesses

If you’re using AI to just write code, you’re missing out.

Two engineers at Every shipped six features, five bug fixes, and three infrastructure updates in one week—and they did it by designing workflows with AI agents, where each task makes the next one easier, faster, and more reliable.

In this episode of AI & I, Dan Shipper interviewed the pair—Kieran Klaassen, general manager of Cora, our inbox management tool, and Cora engineer Nityesh Agarwal—about how they’re compounding their engineering with AI. They walk Dan through their workflow in Anthropic’s agentic coding tool, Claude Code, and the mental models they’ve developed for making AI agents truly useful. Kieran, our resident AI-agent aficionado, also ranked all the AI coding assistants he’s used.

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Timestamps:

1. Introduction: 00:01:16
2. Why Kieran believes agents are turning a corner: 00:03:18
3. Why Claude Code stands out from other agents: 00:06:36
4. What makes agentic coding different from using tools like Cursor: 00:11:58
5. The Cora team’s workflow to turn tasks into momentum: 00:15:20
6. How to build a prompt that turns ideas into plans: 00:23:07
7. The new mental models for this age of software engineering: 00:34:00
8. Why traditional tests and evals still matter: 00:39:13
9. Kieran ranks all the AI coding agents he’s used: 00:42:00

Links to resources mentioned in the episode:

• Try Cora, our AI email assistant: https://cora.computer/  
• Kieran Klaassen: @kieranklaassen
• Nityesh Agarwal: @nityeshaga
• The book that helps Nityesh form mental models to work with AI agents: High Output Management
• A guide to Anthropic’s prompt improver: https://www.anthropic.com/news/prompt-improver