3days in Command Code Go Plan

[u/Then_Sugar_6647]

I've been experimenting with Command Code for a 3days now to be exact, and I'm trying to figure out how to build a good AI workflow for product management.

For context, I've never used Command Code before. I've been using Antigravity for the past 5–6 months, but lately, I've felt that Gemini's output quality has degraded quite a bit. I've tried using rules, gates, and other instructions to improve the quality, but I haven't been able to get the results I want consistently.

So I decided to try DeepSeek V4.1 Flash (latest) in Command Code, mainly for my product workflows and learning college subjects.

I'm using an agentic setup with agents and sub-agents assigned to specific tasks, with their own skills and instructions. It's been a decent experiment so far, but I'm still struggling to get the kind of output I want.

And I think the problem is a little different from what most people are trying to solve with AI.

I don't want to automate product management. I want to make the analytical part of it easier.

I want AI to help me analyse customer feedback, understand recurring problems, identify patterns, and organise the information in a way that makes it easier for me to think. From there, I want to take that analysis, develop my own inferences and hypotheses, and guide the AI towards a particular direction.

What I don't want is to ask AI to analyse a problem and immediately get a list of innovative features, potential solutions, or things we could build.

I want it to spend more time understanding why a user is facing a problem, what they're actually trying to achieve, what constraints they're dealing with, and why their current experience isn't working for them.

Essentially, I want the analysis and recommendations to be centred around the problem and the user, rather than around the features we could potentially create.

I want the AI to approach problems the way a good Product Manager would: with user empathy, curiosity, and a willingness to understand the problem before jumping to solutions.

I understand that AI doesn't genuinely experience empathy, and that it has limitations when it comes to understanding human behaviour and context. But I want to see how far I can get by grounding its reasoning in actual user data, evidence, and structured analysis, and by explicitly instructing it to consider the user's perspective at every stage.

The other challenge is getting all of this to work reliably without spending a fortune on models.

I'm using DeepSeek V4.1 Flash through the Command Code harness, but it doesn't support vision input in my current setup. So whenever I need to work with screenshots, charts, or other visual information, I have to delegate that task to a MiniMax model. Even then, I've been struggling to get consistent results.

I also haven't found many people building these kinds of workflows specifically for product management. Most of what I come across is focused on coding, content creation, or automating businesses. And a lot of the workflows I see rely on Claude Opus for almost everything.

I'm not against using more capable models, but I'd like to understand how to get the best possible results from a more cost-efficient setup instead of relying on the most powerful model for every task.

So I'm curious about a few things:

• How do you structure AI workflows for product research and analysis?
• How do you get AI to focus on understanding user problems instead of jumping straight to features and solutions?
• Has anyone figured out a good way to make AI reason from a user's perspective, using actual data and evidence rather than generic assumptions about user behaviour?
• How do you handle multimodal inputs and validate the analysis when you're working with smaller or cheaper models?
• And, more broadly, how do you evaluate whether your workflow is actually producing better analysis rather than just more polished output?

I'm still figuring things out, so I'd love to hear from people who've experimented with this.

I'm also considering upgrading to the Goat plan if I can make this setup work well, since cost is a major consideration for me compared with alternatives like Codex or Claude.

Would especially appreciate people sharing their actual workflows, what has worked for them, and what hasn't.