Creating good content with AI still needs good amount of iteration if you CARE
I keep getting excited about the future and the new set of problems that are coming with assisted deep content creation.
Iteration is the key! like most of the conversational agents, keeping what is relevant in the context without bloating is more important in non textual contents, it sometimes needs language as a medium, it sometimes need differently trained models to understand the context -> pass it to another nicely -> store it in a common memory -> let users iterate nicely.
- no rush. I tried solving it with lesser turns and efficiency, but getting inspired from coding agents, i realised its about the quality, slow is fine so that content creators will get enough time to think and try to match the pace with the assistant, like we do in a team.
My attempt to solve this is constantly changing! When I started, it looked like very simple dots to connect, but when I actually tried, it is difficult.
I tried solving it like a programmer first by making more agent tools, but what AI cares about more is raw capabilities and excellent examples, you don't have to wrap everything in tools, I feel agents fundamentally works better if tools can do broader tasks than creating numerous focused tasks, I could be wrong in other aspects, but with my current experiments and the given context requirements thats what i learned.
I hope I should be able to show this once I am satisfied of sharing it!(definition of "satisfied" here is that when it delivers value - when i am able to fully iterate and publish on a long form content myself -podcast/long paper/video, it needs to stand out with the one shot content created with currently available tools)
the journey of building AI tools that actually help creators is messier and more iterative than i thought. but worth every token spent though.