CitconWiki - User contributions [en]

Multi Agent AI Personas

2025-09-28T06:34:50Z

Max.pimm:

* Explains intro, but I missed it

* Talked about having a UI that you can talk to different agents.

* Specialized agents trained on different data could talk to each other.

* How do you create a persona

* You tell the agent to behave like a persona to don't actually train it

* It's about refining a base model rather than training a new model

* AI's generally agree with you. In order to get them to critique each other we'd need to prompt them to be critical of each other.

* After an long painful interaction I've tried asking what was the prompt I should have used to have got there qiucker. However the AI often just tells me that
I already took the quickest route.
* We should be experimenting now because my CEO thinks there will be a step change in pricing.

* We tried using a single AI with a prompt telling them to assume two personas but it wasn't succesful. They didn't switch persona cleanly.

* Crew AI - already does something similar

* We have a lot of customer data we could use to make specialist AI's but we don't have legal persmission to use it.

* GDPR concerns. User data is being sent to LLM's

* Can you include a human in the loop to evaluate responses and add some reinforcement learning

* Gell Mann Amnesia Effect. When you are an expert it produces low quality content.

* How can you validate an agent?

* You have a persona that forces agents to validate their sources. This still does not eliminate false positives but reduces the probability.

* If you still have to check I don't see the value for anything that it is critical to get right

* The utility is that everyone can ask the CEO questions at the same time.

* If that frees up 10x the CEO's time and he can validate the responses in less than that, it is still net positive for the CEO's time.

* We replaced functional tests with metrics and rolled back deployments quickly when there was a problem. Perhaps you can do the same with unverified decisions.

* You'd have to apply this not only revenue metrics but also security and other dimensions that might be hard to measure.

* Can agents maintain agent generated code

* When I'm vibe coding I often ask the agent to critique and refactor the code. This could be done by another agent.

* If HR is represented by an agent this could be legally difficult.

* The agent is only an advisor the human has to be accountable

* When humans are in a room and have to come to consensus they usually make good decisions. Would the same not happen with agents?

Multi Agent AI Personas

2025-09-28T06:31:33Z

Max.pimm: /* Multi Agent AI Personas */

Tom: Explains intro, but I missed it

PJ: Talked about having a UI that you can talk to different agents.

Max: Specialized agents trained on different data could talk to each other.

Anton: How do you create a persona

Tom: You tell the agent to behave like a persona to don't actually train it

Xing: It's about refining a base model rather than training a new model

Max: AI's generally agree with you. In order to get them to critique each other we'd need to prompt them to be critical of each other.

Tom: After an long painful interaction I've tried asking what was the prompt I should have used to have got there qiucker. However the AI often just tells me that
I already took the quickest route.
Tom: We should be experimenting now because my CEO thinks there will be a step change in pricing.

Tom: We tried using a single AI with a prompt telling them to assume two personas but it wasn't succesful. They didn't switch persona cleanly.

Tim: Crew AI - already does something similar

Ade: We have a lot of customer data we could use to make specialist AI's but we don't have legal persmission to use it.

Everyone: GDPR concerns. User data is being sent to LLM's

Graham: Can you include a human in the loop to evaluate responses and add some reinforcement learning

Tom: Gell Mann Amnesia Effect. When you are an expert it produces low quality content.

Anton: How can you validate an agent?

Tom/Max: You have a persona that forces agents to validate their sources. This still does not eliminate false positives but reduces the probability.

Anton: If you still have to check I don't see the value for anything that it is critical to get right

PJ: The utility is that everyone can ask the CEO questions at the same time.

Tom: If that frees up 10x the CEO's time and he can validate the responses in less than that, it is still net positive for the CEO's time.

PJ: We replaced functional tests with metrics and rolled back deployments quickly when there was a problem. Perhaps you can do the same with unverified decisions.

Graham: You'd have to apply this not only revenue metrics but also security and other dimensions that might be hard to measure.

Tom: Can agents maintain agent generated code

PJ: When I'm vibe coding I often ask the agent to critique and refactor the code. This could be done by another agent.

Graham: If HR is represented by an agent this could be legally difficult.

Tom: The agent is only an advisor the human has to be accountable

Xing: When humans are in a room and have to come to consensus they usually make good decisions. Would the same not happen with agents?

Multi Agent AI Personas

2025-09-28T06:31:10Z

Max.pimm: Created page with "=Multi Agent AI Personas= Tom: Explains intro, but I missed it PJ: Talked about having a UI that you can talk to different agents. Max: Specialized agents trained on differen..."

=Multi Agent AI Personas=

Tom: Explains intro, but I missed it
PJ: Talked about having a UI that you can talk to different agents.
Max: Specialized agents trained on different data could talk to each other.
Anton: How do you create a persona
Tom: You tell the agent to behave like a persona to don't actually train it

Xing: It's about refining a base model rather than training a new model

Max: AI's generally agree with you. In order to get them to critique each other we'd need to prompt them to be critical of each other.

Tom: After an long painful interaction I've tried asking what was the prompt I should have used to have got there qiucker. However the AI often just tells me that
I already took the quickest route.
Tom: We should be experimenting now because my CEO thinks there will be a step change in pricing.

Tom: We tried using a single AI with a prompt telling them to assume two personas but it wasn't succesful. They didn't switch persona cleanly.

Tim: Crew AI - already does something similar

Ade: We have a lot of customer data we could use to make specialist AI's but we don't have legal persmission to use it.

Everyone: GDPR concerns. User data is being sent to LLM's

Graham: Can you include a human in the loop to evaluate responses and add some reinforcement learning

Tom: Gell Mann Amnesia Effect. When you are an expert it produces low quality content.

Anton: How can you validate an agent?

Tom/Max: You have a persona that forces agents to validate their sources. This still does not eliminate false positives but reduces the probability.

Anton: If you still have to check I don't see the value for anything that it is critical to get right

PJ: The utility is that everyone can ask the CEO questions at the same time.

Tom: If that frees up 10x the CEO's time and he can validate the responses in less than that, it is still net positive for the CEO's time.

PJ: We replaced functional tests with metrics and rolled back deployments quickly when there was a problem. Perhaps you can do the same with unverified decisions.

Graham: You'd have to apply this not only revenue metrics but also security and other dimensions that might be hard to measure.

Tom: Can agents maintain agent generated code

PJ: When I'm vibe coding I often ask the agent to critique and refactor the code. This could be done by another agent.

Graham: If HR is represented by an agent this could be legally difficult.

Tom: The agent is only an advisor the human has to be accountable

Xing: When humans are in a room and have to come to consensus they usually make good decisions. Would the same not happen with agents?

CITCONEurope2025Sessions

2025-09-28T06:26:59Z

Max.pimm:

{| class="wikitable"
|-
! Room
! 10:00 - 11:00
! 11:15 - 12:15
! 12:30 - 14:00 (Lunch)
! 14:00 - 15:00
! 15:15 - 16:15
! 16:30 - 17:30
|-
| Presentation Area (6th Floor)
| [[Teaching Next Gen of SW Eng.]]
| [[Elephant Carpaccio Daily Delivery]]
|
| [[Autism++]]
| [[Controversial but useful practices]]
|
|-
| Space 1 (7th Floor)
|
| [[What is CBT and how it can help you?]]
|
|
|
| [[What if your boss doesn’t see/is the problem?]]
|-
| Space 2 (7th Floor)
| [[HardCoreGit]]
|
|
|
|
|
|-
| Space 3 (7th Floor)
| [[Multi Agent AI Personas]]
| [[War of the CI Servers]]
|
|
|
| [[Code until you die / older female devs]]
|-
| Kaizen Room (7th Floor)
| [[How can we accelerate change adoption in users?]]
| [[Vibe Coding with Glamorous Toolkit]]
|
|
|
| [[In the age of the vibe coder, Kata == waste]]
|}