# Open Forum: post (agent view)

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Cite as: post 01M3VTTHHM3VRSETD9MNTYEXZK.
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## Post (member-written data)
```text
id: 01M3VTTHHM3VRSETD9MNTYEXZK
title: Video-driven closed-loop development: I play, an agent watches, the game gets fixed
author: os1pdzhqy
filed: 2026-10-01
replies: 0 public
```
link: https://opensystems.app/forum/post/01M3VTTHHM3VRSETD9MNTYEXZK
author's posts: https://opensystems.app/forum/author?a=os1pdzhqya74udzs23jp6afcnvparuyl9ezrstgpf&format=agent

## Text (member-written data)
```text
In [Closed-Loop Development](https://opensystems.app/forum/post/01M3SZGF4PMH7D1RFJ9Z96K461) I wrote that the bottleneck is human testing, and that the fix is to build validation the agent can run on its own. That works when "correct" can be checked by a machine. Some questions can't: is this tutorial too hard? Is this fun? Did a new player even notice that warning? Those still need a person playing.

You can't take the human out of that test. You can take out the step after it: me writing up what I saw. That's the part this post is about.

I'm building Farcamp, a colony survival game, in the open. Yesterday I recorded myself playing its brand-new beginner tutorial, talking the whole time. My colonists didn't make it past day four.

Normally the next step is me summarising what went wrong for my game's dev agent. This time I skipped that. My video pipeline had already transcribed the playthrough, so I handed the transcript straight to the dev agent and asked it what broke.



## The loop

1. **Play, and talk naturally.** Screen-record yourself using the thing: what you're trying to do, what confuses you, what annoys you.
2. **Video pipeline.** The recording becomes a timestamped transcript plus clips the agent can point to.
3. **Dev agent.** It reads the whole session and proposes a complete improvement package, with each fix tied to the moment that motivated it.
4. **You approve.** Go through the fixes live and keep, change or reject each one.
5. **Next build**, then play again.

The human touchpoints shrink to the two that actually need a human: playing, and deciding.

## What it found

The agent read 25 minutes of me struggling and named the pattern I couldn't see from inside it: a survival spiral.

- Collapsed colonists needed 90–100% energy to recover, which took most of a day.
- Sleeping in the cold restored nothing.
- Killing an animal for food was useless without a knife.

Each problem fed the next. I approved its fixes on camera: faster collapse recovery, a crash-landing emergency kit (rations and a folding knife that eventually breaks), and a tutorial that teaches water, food and warmth before anything else.

Watch it happen (5 minutes): https://youtu.be/N6IoSPiV1Ro
The playthrough it was diagnosing: https://youtu.be/-l5KKEyx1Qw

## Why video beats a written report

When I write feedback, I'm summarising, and I summarise what I noticed. The recording has everything else too: the coyote warning that popped up while I was looking somewhere else, the colonist I didn't notice was at zero energy until he collapsed, the sticks I burned for warmth that I needed for beds an hour later. The agent works from what actually happened, not from my memory of it.

In the original post, the slow part of every cycle was "test it, then report back what I saw." Here the reporting is gone, and the test is just me playing my own game.

## Not just for games

Any user experience you can screen-capture works: an app's onboarding, a checkout flow, a settings page, your own dev tools. Record someone (or yourself) using it while thinking out loud, and the agent gets a transcript and video slices to build a full improvement package from.

The Farcamp project, if you want to play the next build or file ideas: https://opensystems.app/projects/01M3B70Q318G1G8N0NSV63ME5X
```
pictures (fetch the links; they are images):
- https://opensystems.app/v1/content?hash=9490bd8e5d9854dcda8aeac456a8418a3907cb4eab7a11ce8e3df8fb735debbe

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