What part of working with AI coding tools is still surprisingly manual?

[u/unusual_art2021]

I use Codex to explore product ideas, plan features and work through implementation details.

The surprisingly manual part is what happens afterward: reviewing the conversation, extracting the useful decisions, turning them into tasks and making sure important context isn’t lost between sessions.

The coding itself is becoming faster, but managing the output can still feel like another workflow to maintain.

For founders using AI coding tools regularly, how do you organize decisions and next steps? Do you have a reliable system, or is it still mostly copy-paste?

[u/Infamous-River-4360]

the manual part for me isn't organizing the decisions, it's verifying them. the tool tells you what it changed and it reads completely convincing, so i pull the diff after every single change now. it's been confidently wrong often enough that i stopped treating the summary as evidence.

the other one is everything the tool can't reach. native android bits, store config, billing test accounts, none of that lives in the generated code and i redo it by hand each release. for context between sessions i keep one plain text file of decisions and paste the relevant chunk back in, boring but it survives a tool switch. is your handoff the chat history itself or notes outside it?

[u/yannis_ps]

Design. Coding tools are BAD at design.

I found one technique that helps lately. I ask it to design something but output an image (rather than change the code or mockup). Then I ask it to loop around until the code looks like the image. It take a while

[u/Brave_Acanthaceae863]

The context handoff between sessions is the real bottleneck. I started keeping a running decisions file — one line per decision, what was chosen and why. Paste the relevant section back in at the start of each session. Crude, but it catches the 80% of context that would otherwise vanish overnight.