How to pick the Agentic Coding Tool

First, be clear about what you’ll use it for. A product leader’s agentic coding tool does four things, in this order of frequency:

Reading. “How does the invite flow actually work?” answered from the real code in two minutes, instead of a Slack thread.
Data. Writing the SQL, running the analysis, making the chart.
Internal tools. The bet scorer, the synthesizer — things you’ll use, not ship to customers.
Prototypes. Eventually replacing the prototyping tool, once you’re fluent.

You are almost never using it to write production features. If a tool is optimized for senior engineers doing that, it may be more than you need.

The three families:

Terminal agents — Claude Code, Codex CLI, Gemini CLI. You describe a task in plain language, the agent reads the codebase, makes a plan, runs commands, edits files. Highest autonomy, least visual. Best for reading and for building small tools end to end.
IDE agents — Cursor, Windsurf, Copilot in VS Code. Same capability inside a code editor. Better if you want to see and edit the code as it goes. More setup, more intimidating for non-engineers.
Cloud agents — assign a task, it works in the background and comes back with a result. Useful once you trust it; wrong place to start.

For a PM who isn’t from engineering, terminal agents have the lowest floor: it’s a conversation, not an IDE.

The test. Clone one real repo — your company’s, or an open-source app in your domain. Then, in each candidate:

Ask a question only the code can answer. “What happens when a user’s subscription lapses?” Judge whether the answer is right and cites the files, and whether you’d have gotten it faster from an engineer.
Ask for a small change. Add a field, change a rule. Does it explain what it’s doing before it does it? Can you stop it?
Build something from nothing. A script that reads a CSV of tickets and groups them by theme. Does it run first time?
Watch how it handles being wrong. Give it a bad instruction. Does it push back, or comply and break things?
Check the leash. Does it ask permission before running commands and editing files? For a non-engineer this is the safety feature that matters.

What to weigh:

Ecosystem with your reasoning partner — same model means the same judgment across tools and no re-explaining context.
Memory and project context: does it remember your codebase’s conventions between sessions?
Cost model: per-seat flat is safer for someone who’ll leave it running while thinking.

Two honest cautions:

The first week is uncomfortable. You’ll feel like you’re pretending to be an engineer. That passes around the time you build your first useful tool.
Never point it at production without an engineer beside you. Not because it can’t, but because you don’t yet know what you don’t know about deploys, secrets, and data. Internal tools and reads are your lane for the first few months.

For you, the practical path: start with a terminal agent on your own tool projects — the bet scorer is a perfect first build — and let it become your prototyping tool as your confidence grows. That’s the path most product people who’ve made this shift describe.