Skip to content
Sprint projectAug 26, 2024

AI Agents for Personalized Interaction and Behavioral Analysis

Chetan Talele,Jasper Timm · Team PRISM

Submitted to AI capabilities and risks demo-jam. Sprint projects are early-stage work by participants, not Apart Research publications.

Read the report

Report: AI Agents for Personalized Interaction and Behavioral Analysis

Recording (opens in new tab)Code (opens in new tab)
Share

Demonstrating the bhavioral analytics and personalization capabilities of AI

Reviews

Judging this Sprint?

Review this project

Your public critique appears on this page without your name. Reviews of strong projects are shared with funders, as you choose below.

Not shown on this page.

Shown on this page, without your name.

Only the Apart team reads this, and funders if you agree below.

Decline to score

Only when the quality of the writing makes the work impossible to follow. Say why in your private critique; nothing shows on this page.

Sharing your name *

When we share a strong project with funders, your name, scores and public critique go with it, confidentially; this choice is only about whether your name is public. If you think this project deserves funding, please also endorse it: that carries the most weight.

Share my private critique with funders *

  1. I like that this is highly personalized, could (in theory) pull in info about the outside world, and I think the written psycho-analysis is compelling. The write-up is detailed and the video gives a could feel for what the app does, although the video is super blurry.I wasn’t able to get it running locally after about 15 minutes of trying (venv issues, self-signed cert stuff, .env file issues, and even after all that the CLI user creation didn’t seem to work). It would’ve been helpful if you had a link to a deployed version of the app or included an install script.Overall, I think this demo is promising and would recommend really leaning into the secret/internal psycho-analysis portion, which I suspect will be substantially more compelling than the actual persuasion.

  2. Nice work! Personalisation is a central capability of LLMs to demonstrate. To make this demo more visceral, I’d aim to shorten the number of steps to see the AI output. Maybe with testing you could find which parts of the personalisation have the biggest effect, and only include those - or focus only on traits which can be reliably inferred from tweets.

Cite this project

@misc{talele2024ai,
  title = {{AI Agents for Personalized Interaction and Behavioral Analysis}},
  author = {Chetan Talele and Jasper Timm},
  year = {2024},
  month = aug,
  note = {Submitted to AI capabilities and risks demo-jam, an Apart Research Sprint},
  howpublished = {\url{https://apartresearch.com/sprints/projects/ai-agents-for-personalized-interaction-and-behavioral-analysis}},
  url = {https://apartresearch.com/sprints/projects/ai-agents-for-personalized-interaction-and-behavioral-analysis}
}

Build something like this at the next Sprint

AI Collusion Research Sprint · Oct 23 - 25, 2026