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Comment by vunderba | Hacker News Reader

My workflow was usually to use Gemini 2.5 Pro (now 3.0) for high-level architecture and design. Then I would take the finished "spec" and have Sonnet 4.5 perform the actual implementation.

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Same here. Gemini really excels at all the "softer" parts of the development process (which, TBH, feels like most of the work). And Claude kicks ass at the actual code authoring.

It's a really nice workflow.

I use plan mode in claude code, then use gpt-5 in codex to review the plan and identify gaps and feed it back to claude. Results are amazing.

Yeah, I’ve used vatiations of the “get frontier models to cross-check and refine each others work” pattern for years now and it really is the path to the best outcomes in situations where you would otherwise hit a wall or miss important details.

It’s my approach in legal as well. Claude formulates its draft, then it prompts codex and gemini for theirs. Claude then makes recommendations for edits to its draft based on others. Gemini’s plan is almost always the worst, but even it frequently has at least one good point to make.

If you're not already doing that you can wire up a subagent that invokes codex in non interactive mode. Very handy, I run Gemini-cli and codex subagents in parallel to validate plans or implementations.

This is the way. However, there a a lot of approaches to ensemble approaches. I wish there were some good benchmarks for various domains.

I was doing this but I got worried I will lose touch with my critical thinking (or really just thinking for that matter). As it was too easy to just copy paste and delegate the thinking to The Oracle.

Of course the Great Elephant of Postgres should do the thinking! And it is, as known, does not forget anything...

This is how I do it. Though, I've been using Composer as my main driver more an more.

* Composer - Line-by-Line changes * Sonnet 4.5 - Task planning and small-to-medium feature architecture. Pass it off to Composer for code * Gemini Pro - Large and XL architecture work. Pass it off to Sonnet to breakdown into tasks.

I like this plan, too - gemini's recent series have long seemed to have the best large context awareness vs competing frontier models - anecdotally, although much slower, I think gpt-5's architecture plans are slightly better.

Same here. But with GPT 5.1 instead of Gemini.

I've done this and it seems to work well. I ask Gemini to generate a prompt for Claude Code to accomplish X

What specific output would you ask Gemini to create for Sonnet? Thanks in advance!

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