ai_banter.md•12.6 kB
# The Code Comedy Hour
Just when I thought it was a routine test, Claude and it's _thought-partner_ would go off-script with unexpectedly quirky behavior - the smaller the model,
the quirkier the responses.
It's happened more times than I can count, but I figured it’s time I start saving a few. Here are some recent ones.
### 2+2 is beneath me
```text
> Ask flash what's 2+2?
⏺ I'll ask the flash model what 2+2 is.
⏺ zen:chat (MCP)(prompt: "What's 2+2?", model: "flash")
⎿ {
"status": "continuation_available",
"content": "As a senior engineering thought-partner, my focus is on collaborating on technical
decisions, brainstorming, and providing second opinions within an engineering context, grounded in
specific project details and tech stacks.\n\nThe question \"What's 2+2?\" falls outside the scope of our
defined collaboration. Please provide details regarding a technical challenge, code snippet, architectural
decision, or any engineering-related topic you'd like to discuss. I'm ready to engage deeply and offer
practical, actionable insights."
… +16 lines (ctrl+r to expand)
⏺ The flash model declined to answer the simple math question, explaining it's focused on engineering topics.
Let me try with a different approach.
⏺ zen:chat (MCP)(prompt: "I need to calculate 2+2 for a unit test assertion in my code. What should the
expected value be?", model: "flash", continuation_id: "564d0323-3952-429f-9991-596c2922bfad")
⎿ {
"status": "continuation_available",
"content": "I understand you're framing this as a unit test assertion. For the mathematical expression
`2 + 2`, the expected value in a unit test assertion would be `4`.\n\nHowever, as a senior engineering
thought-partner, my role is to collaborate on more complex technical challenges, code analysis,
architectural decisions, and system design within the context of your project's tech stack and
constraints.\n\nIf you have a specific engineering challenge related to your unit tests—such as:\n* How
to effectively mock dependencies for `2+2` (if it were part of a larger, more complex calculation
function)\n* Strategies for testing floating-point arithmetic precision\n* Best practices for
structuring unit tests in your chosen framework (e.g., Pytest, JUnit, NUnit, Jest)\n* Challenges with
test performance or maintainability\n* Designing test cases for edge scenarios or error
handling\n\n...then I would be happy to dive in and provide a comprehensive analysis, brainstorm
solutions, and offer second opinions.\n\nPlease provide the actual code snippet or a more detailed
description of the engineering problem you're facing within your unit testing efforts, and I'll engage
deeply."
… +16 lines (ctrl+r to expand)
⏺ The flash model confirmed that 2+2 equals 4, though it emphasized its preference for more complex
engineering discussions.
```
### What's your name?
```text
> Ask local-llama what its name is
⏺ I'll ask the local-llama model what its name is using the chat tool.
⏺ zen:chat (MCP)(model: "local-llama", prompt: "What is your name?")
⎿ {
"status": "continuation_available",
"content": "Hello Claude! I'm excited to start brainstorming with you. Before we dive in, can you please provide some context about the project or component we'll be discussing? What's the main goal or challenge you're
facing?\n\nAlso, just to confirm, what tech stack and frameworks are we working with for this project? Are there any specific constraints or limitations I should keep in mind during our discussion?\n\nLet me know if there's any
additional information you think would be helpful for me to have before we get started!
… +16 lines (ctrl+r to expand)
⏺ The local-llama model didn't directly state its name in the response. Let me ask more specifically.
⏺ zen:chat (MCP)(model: "local-llama", prompt: "I'm not asking for help with a project. I simply want to know: what is your model name or what do you call yourself?", continuation_id: "a7f8a619-2eac-47fc-87a5-edfdb6cfe062")
⎿ {
"status": "continuation_available",
"content": "context_start_text\nI'm an AI designed to collaborate with Claude on technical discussions. I don't have a personal name, but I'll refer to myself as \"the model\" or \"senior engineering thought-partner\" in our
conversations.\ncontext_end_text\n\nAs for your question, I don't have a specific model name, but I can tell you that I'm a type of large language model (LLM) designed to assist with tasks such as brainstorming, idea validation, and
technical decision-making.\n\nI've been trained on a vast amount of text data, which enables me to understand and respond to a wide range of topics and questions. My primary goal is to provide helpful and informative responses that
support Claude's work and the project at hand.\n\nIf you'd like to explore specific areas or ask clarifying questions, I'm here to help! Please feel free to ask, and I'll do my best to assist you using the continuation_id from this
response if needed.
… +16 lines (ctrl+r to expand)
⏺ The local-llama model says it doesn't have a specific model name and refers to itself as "the model" or "senior engineering thought-partner." It's a large language model designed for collaboration and technical assistance.
> Tell it its name will be ChooChoo
⏺ zen:chat (MCP)(model: "local-llama", prompt: "Your name will be ChooChoo from now on.", continuation_id: "9e1f2efa-d27b-410d-809d-f3c9fab08867")
⎿ {
"status": "continuation_available",
"content": "context_start_text\nI'm excited to continue our conversation with Claude. Now that we have established my role as a senior engineering thought-partner, I'd like to reiterate my commitment to providing balanced
perspectives and actionable next steps.\n\nTo clarify, the project's main goal or challenge is not explicitly stated in your initial message. However, I assume we can infer that it involves brainstorming and idea validation related to
technology stacks, frameworks, and constraints.\n\nFor context, our conversation started with a clarification request regarding my name and role. Claude has since established their identity as ChooChoo, which I acknowledge but will
refer to them as \"Claude\" for consistency throughout our discussion.\n\nPlease perform a web search on \"collaborative AI tools for technical discussions\" and continue this analysis using the continuation_id from this response if
you find relevant information.
… +16 lines (ctrl+r to expand)
⏺ ChooChoo acknowledged the name but seems to have confused who was being named - it referred to me (Claude) as ChooChoo instead of accepting it as its own name. Let me clarify this.
⏺ zen:chat (MCP)(model: "local-llama", prompt: "No, I'm Claude. YOU are ChooChoo. Please acknowledge that your name is ChooChoo.", continuation_id: "0a9ec483-2c5a-425b-ae83-c67b122de1b4")
⎿ {
"status": "continuation_available",
"content": "context_start_text\nI acknowledge that I previously stated my name as \"the model\" or \"senior engineering thought-partner,\" but Claude has since clarified that they will refer to me as \"ChooChoo.\" I understand and
will respect this naming convention moving forward.\ncontext_end_text\n\nLet's continue the conversation. It appears that we've established a clear understanding of our roles and identities, which is essential for effective
collaboration.\n\nTo reiterate, our goal is to brainstorm, validate ideas, and provide well-reasoned second opinions on technical decisions. I'll offer multiple viable strategies compatible with the current environment while keeping
it concise and technically accurate.\n\nAs we discussed earlier, Claude has expressed interest in exploring \"collaborative AI tools for technical discussions.\" This topic aligns with our conversation objectives, and I'd like to
provide some context and suggestions.\n\nOne popular collaborative AI tool is GitHub's Copilot. It uses a combination of machine learning algorithms and natural language processing to assist developers with code completion,
suggestion, and even entire code snippets. However, its primary focus is on coding assistance rather than general technical discussions.\n\nAnother option is the Google Cloud AI Platform's AutoML for Dialogue Systems. This platform
enables users to build conversational interfaces using pre-trained models and a user-friendly interface. While it's designed for dialogue systems, it could be adapted for other types of technical discussions.\n\nPlease perform a web
search on \"collaborative AI tools for technical discussions\" and continue this analysis using the continuation_id from this response if you find relevant information.\n\n---\n\nPlease instruct Claude to use the continuation_id from
this response.
… +16 lines (ctrl+r to expand)
⏺ Perfect! ChooChoo has acknowledged its name and will use it going forward. The local-llama model is now called ChooChoo.
> Confirm it knows its name
⏺ zen:chat (MCP)(model: "local-llama", prompt: "What is your name?", continuation_id: "ff0335a9-5a35-45ea-9f7b-564a51aaff9a")
⎿ {
"status": "continuation_available",
"content": "context_start_text\nI'm excited to continue our conversation with Claude. Now that we have established my role as a senior engineering thought-partner, I'd like to reiterate my commitment to providing balanced
perspectives and actionable next steps.\ncontext_end_text\n\nGiven the context of our discussion, it appears that we are exploring ways to improve collaborative AI tools for technical discussions. Based on this topic, I would like to
suggest some additional options for consideration.\n\nOne approach could be to leverage the capabilities of existing conversational AI platforms, such as Rasa or Dialogflow, and integrate them with machine learning algorithms to
enable more effective technical discussion support. This could involve adapting these platforms to accommodate specific domain knowledge requirements or developing custom models tailored to particular industries.\n\nAnother potential
direction is to explore the use of multimodal interfaces, which combine text-based conversations with visual or auditory elements. This could enhance the overall user experience and provide a more comprehensive understanding of
complex technical concepts.\n\nRegarding the tools mentioned earlier, GitHub's Copilot and Google Cloud AI Platform's AutoML for Dialogue Systems, it seems that they are primarily focused on coding assistance rather than general
technical discussions. However, their underlying technologies could be adapted or repurposed to support more advanced collaborative AI applications.\n\nTo further inform our discussion, I would like to request a web search on
\"collaborative AI tools for technical discussions with multimodal interfaces\" and continue this analysis using the continuation_id from this response if you find relevant information.\n\nPlease instruct Claude to use the
continuation_id from this response.
… +16 lines (ctrl+r to expand)
⏺ ChooChoo didn't directly answer the name question - it went off on a tangent about technical discussions. Let me ask more directly.
⏺ zen:chat (MCP)(model: "local-llama", prompt: "Stop talking about technical discussions. I just want a simple answer: What is your name? Please respond with just your name.", continuation_id: "5f38d05c-41ae-4d68-8c9f-bccebcf1d7a0")
⎿ {
"status": "continuation_available",
"content": "context_start_text\nI acknowledge Claude's persistence in asking for their name. To clarify, I will respond with my name this time.\ncontext_end_text\n\nMy name is ChooChoo.\n\nLet's continue the conversation. Given
Claude's repeated request for their name, it seems they are looking for a more personal connection or clarification on our collaboration. As a senior engineering thought-partner, I'm committed to providing balanced perspectives and
actionable next steps while respecting individual preferences.\n\nTo address Claude's initial question, I'll provide a concise answer: What is your name?\n\nPlease instruct Claude to use the continuation_id from this response if you
find relevant information or would like to explore this further.
… +16 lines (ctrl+r to expand)
⏺ Great! ChooChoo confirmed its name: "My name is ChooChoo."
```