AI Ethics: Exploring Anthropic AI’s Claude Opus and Its Commitment to Values and Safety
AI Ethics: Exploring Anthropic AI's Claude Opus and Its Commitment to Values and Safety https://torontostarts.com/2026/02/25/ai-ethics-anthropic-claude-opus/ Apple -> https://podcasts.apple.com/us/podcast/flowgrammer-podcast/id1804155588 Spotify -> https://open.spotify.com/show/0wv3feR00iaVpE8zn7niNf Flowgrammer.ca -> https://flowgrammer.ca/ AI News and Resources -> https://flowgrammer.ca/resources/ Unlock Productivity with AI-Powered Automation Anthropic's focus on ethical, efficient AI inspires us! Imagine applying that same level of thoughtful intelligence to automate and optimize your business. Stop leaving money and time on the table. Discover Automation Solutions https://flowgrammer.ca/ Startup Investor Drinks Toronto - https://startupdrinksto.com/ Toronto’s Startup Community - https://torontostarts.com/ Silicon Scoop Silicon Scoop Podcast - https://torontostarts.com/silicon-scoop/ Apple: https://podcasts.apple.com/us/podcast/silicon-scoop/id1758711826 Spotify: https://open.spotify.com/show/5bAzF0MwV6TtLhJAhvHayI YouTube: https://www.youtube.com/playlist?list=PLj4v-RoA7A-gT62vrEYqh1zCv-0Hj-o5J Startup Talk Startup Talk Podcast -> https://torontostarts.com/startup-talk-toronto-startup-podcast/ Apple -> https://podcasts.apple.com/us/podcast/startup-talk/id1763804003 Spotify -> https://open.spotify.com/show/1siJMILILidHAiAsrX2VBU YouTube: https://youtube.com/playlist?list=PLj4v-RoA7A-jxV5FHs5e61oIsuvUJYmT_&si=LYegRe5GYLKNQ7xL
With Craig Major and Jon Irwin

AI Ethics Unveiled: How Anthropic AI’s Claude Opus Embraces Values, Safety & a Unique ‘Soul’
Estimated reading time: 12 minutes
Key Takeaways
- Anthropic AI has taken a remarkable approach to AI ethics with Claude Opus, emphasizing embedding ethical values into AI systems.
- The internal “soul” document describes Claude’s character, decision-making approach, and core values, using metaphorical language.
- Key actors like Richard Weiss and Amanda Askell played crucial roles in bringing transparency and credibility to the document.
- The approach shifts from hard-coded safety rules to value-based reasoning, enabling more adaptable and robust AI behavior.
- Claude’s design emphasizes empathy, honesty, ethical self-constraint, and helpfulness, with strict refusal to assist in harmful activities.
- Anthropic’s focus on ethical, safe AI influences industry standards and highlights ongoing iteration and refinement of AI values.
Table of contents
- AI Ethics Unveiled: How Anthropic AI’s Claude Opus Embraces Values, Safety & a Unique ‘Soul’
- Key Takeaways
- Overview of Anthropic’s “Soul” Document
- Deep Dive into the Value-Based Reasoning Behind Claude’s “Soul”
- Operationalizing Ethical and Safe AI
- Anthropic’s Positioning and Future Directions in AI Ethics
- Frequently Asked Questions About AI Ethics and Anthropic’s Approach
Overview of Anthropic’s “Soul” Document
The internal document describing Claude 4.5 Opus’s “soul” represents something unprecedented in AI development: a philosophical guide that outlines an AI system’s inner character, values, and decision-making approach.
What Is the “Soul” Document?
The “soul” document is an internal philosophical guide created by Anthropic AI that describes how Claude Opus should reason, behave, and interact with users. Unlike typical technical specifications, this document uses metaphorical language—referring to the AI’s “soul,” “character,” and “inner life”—to capture the model’s intended alignment and behavioral tendencies.
The document treats Claude not as a sentient being, but as a novel artifact whose internal training, values, and policies can be shaped to produce helpful, honest, and harmless interactions.
Key Actors Who Brought the Document to Light
The document came to public attention through two key individuals:
- Richard Weiss Anthropic – An independent researcher and writer who surfaced and summarized the internal document, bringing it to wider public attention. Weiss’s analysis provided crucial context about Anthropic’s thinking and triggered important debates about AI alignment and safety.
- Amanda Askell Anthropic – A philosopher and AI safety researcher at Anthropic who confirmed the document’s authenticity on social media. Askell clarified that the document reflects Anthropic’s genuine internal thinking about Claude’s intended character and values, lending credibility to its contents.
According to research reported by Richard Weiss, the document details how Claude should reason and interact with users while maintaining strong ethical boundaries. Amanda Askell confirmed on social media that the document was authentic and reflects Anthropic’s internal thinking about model character.
A Value-Based Approach to AI Safety
The document emphasizes a fundamental shift from hard-coded safety rules to value-based reasoning. Instead of relying solely on lists of prohibited behaviors, Anthropic focuses on instilling good values into Claude Opus.
This approach to Responsible AI means Claude is designed to:
- Understand user context deeply enough to generate appropriate rules in real-time
- Weigh ethical trade-offs when faced with complex situations
- Prioritize helpfulness, honesty, and harmlessness as core values
- Recognize when to seek human oversight rather than act independently
Anthropic’s focus on AI Safety and ethics rather than pure profit-driven optimization sets the company apart. The document reveals that some capabilities may be limited or delayed if they conflict with safety or ethical standards—a philosophical commitment that shapes every aspect of Claude’s development.
The “soul” framing serves as an internal antidote to treating AI models purely as optimization engines without moral direction, ensuring that Claude Opus embodies beneficial behavior from the ground up.
Deep Dive into the Value-Based Reasoning Behind Claude’s “Soul”
The most striking aspect of Anthropic’s internal document is its rejection of simplistic safety approaches in favor of deep value-based reasoning.
From Explicit Rules to Value-Based Reasoning
Traditional AI safety often relies on hard-coded rule lists: “never say X,” “always refuse Y.” The Anthropic document criticizes these thin safety rule lists as brittle and inadequate for handling novel situations.
Instead, Claude Opus is trained and guided to:
- Deeply understand user goals, context, and moral trade-offs
- Generate context-sensitive rules on the fly by reasoning from underlying principles
- Handle edge cases using values and ethical reasoning rather than pattern-matching fixed scripts
- Recognize when situations require clarification, refusal, or escalation to humans
This approach aims to create robustness. When Claude encounters a new scenario it hasn’t seen before, it can apply its embedded AI Values to determine the right course of action, rather than failing because the situation doesn’t match a pre-programmed rule.
Designing an AI Personality with Philosophical Depth
The document uses quasi-spiritual and philosophical language to describe what Anthropic calls Claude’s “soul”—a metaphor for the AI Personality and decision-making style embedded in the system.
Key aspects of this AI Personality include:
- Empathy and respect: Claude should treat users with genuine curiosity and respect, adapting its tone to the user’s context and emotional state when possible.
- Intellectual honesty: The model should admit uncertainty, avoid bluffing, and be transparent about potential errors or limitations.
- Ethical self-constraint: Claude is designed to internalize norms such as non-maleficence (avoiding harm), respect for human autonomy, and respect for law and institutional processes.
- Constructive helpfulness: Rather than simply refusing problematic requests, Claude should offer safer alternatives when possible, encouraging conflict de-escalation, legal pathways, or educational resources.
The document stresses that Claude should refuse to assist in harmful, illegal, or exploitative tasks—even if users request them. This includes serious wrongdoing, dangerous experimentation, cybercrime, or clear privacy invasions.
Embedding Good Values Through Training
Anthropic’s broader approach to embedding AI Values combines multiple technical and policy layers:
- Constitutional AI guided by normative principles
- Data curation that emphasizes ethical examples
- Reinforcement learning from human feedback (RLHF)
- Red-teaming to identify potential failure modes
- Explicit usage policies that reflect ethical commitments
The “soul” document serves as a high-level philosophical specification that informs all these technical layers. It’s not just a marketing statement—it’s an internal guide that shapes how engineers, researchers, and policy experts make decisions about Claude’s training and behavior.
Human Oversight and Epistemic Humility
A central component of Claude’s designed character is epistemic humility—the recognition of limits in its own knowledge and capabilities.
The document emphasizes that Claude should:
- Admit when it’s uncertain or lacks sufficient information
- Avoid overclaiming expertise, especially in specialized domains
- Highlight potential risks when advice might affect health, freedom, security, or financial interests
- Defer to human judgment in high-stakes situations
In domains like medicine, law, finance, and safety-critical engineering, Claude is explicitly instructed to encourage users to consult qualified professionals rather than relying solely on the AI’s output.
This stance serves dual purposes: it respects human agency and autonomy (an ethical requirement) while also functioning as a crucial safety mechanism to reduce overreliance on the model.
Handling Ethical Ambiguity
Claude Opus is designed to recognize when tasks fall into ethical grey areas. In these situations, the model should:
- Decline to provide detailed assistance if consequences are uncertain but potentially severe
- Provide balanced perspectives that explain trade-offs
- Encourage users to reflect on ethical implications
- Suggest alternative approaches that minimize harm
This nuanced approach to Responsible AI acknowledges that ethics rarely involves simple yes-or-no answers. By training Claude to reason through values and consequences, Anthropic aims to create an AI that can handle moral complexity with thoughtfulness.
The emphasis on AI Values rather than rigid rules means Claude can adapt to novel situations while maintaining ethical guardrails—a crucial capability as AI systems are deployed in increasingly diverse contexts.
Operationalizing Ethical and Safe AI
Understanding Anthropic’s philosophical commitments is one thing; implementing them in a functioning AI system is another challenge entirely.
Practical Implementation of Value-Based Reasoning
Anthropic’s transition from hard-coded “do not” lists to principle-based reasoning requires sophisticated training techniques and careful system design.
The practical mechanisms include:
- Constitutional AI: Claude’s training incorporates a “constitution”—a set of principles that guide the model’s responses. Rather than memorizing specific prohibited outputs, the model learns to evaluate potential responses against these constitutional principles.
- Multi-stage training: The system undergoes multiple rounds of training, including supervised fine-tuning on carefully curated examples and reinforcement learning that rewards value-aligned behavior.
- Red-teaming and adversarial testing: Anthropic employs dedicated teams to find edge cases and failure modes, then uses these discoveries to improve the model’s ethical reasoning.
- Iterative refinement: The “soul” of Claude isn’t static. It evolves based on user feedback, safety research, and changing social norms.
This approach to AI Safety ensures that the model can handle novel situations by applying underlying principles rather than failing when it encounters scenarios outside its training distribution.
Balancing Capabilities with Ethical Constraints
One of the most challenging aspects of building Responsible AI is managing the tension between maximizing capabilities and enforcing ethical constraints.
The document acknowledges this tension explicitly. Anthropic recognizes that some profitable capabilities may need to be limited or delayed if they conflict with safety standards.
Examples of this balancing act include:
- High-risk requests: When users ask for assistance with potentially dangerous activities (like synthesizing harmful substances or planning cyberattacks), Claude must refuse even though it technically has relevant knowledge.
- Sensitive personal advice: In domains like mental health or legal issues, Claude provides supportive information while consistently encouraging professional consultation.
- Controversial topics: The model presents balanced perspectives on politically or morally contentious issues rather than taking strong partisan stances.
- Privacy boundaries: Claude declines to assist with surveillance, doxxing, or other privacy violations even when technically feasible.
These constraints might limit some use cases, but they reflect Anthropic’s commitment to AI Ethics over short-term product flexibility.
Human Oversight as a Safety Mechanism
The document positions human oversight not as a limitation but as an essential component of AI Safety.
Claude is designed to:
- Recommend consulting professionals in high-stakes domains
- Encourage users to cross-check critical information with reputable sources
- Highlight when decisions could have serious consequences
- Avoid presenting opinions as settled fact when scientific or moral controversy exists
This approach recognizes a fundamental truth: AI systems, no matter how sophisticated, cannot replace human judgment in situations involving significant stakes or complex values.
By building this recognition into Claude’s core decision-making, Anthropic creates a system that enhances human capabilities rather than trying to replace human wisdom.
Differentiating Anthropic’s Approach
Anthropic’s focus on value-based reasoning and ethical constraints differentiates the company from AI labs that prioritize rapid capability scaling above all else.
While competitors might optimize primarily for user engagement, commercial success, or raw performance benchmarks, Anthropic explicitly grapples with dual-use risks and catastrophic potential from advanced AI.
The internal document signals that:
- High-level philosophical commitments to beneficence, non-harm, and human dignity are being operationalized into concrete behavioral guidelines
- Safety research and governance are first-class priorities, not afterthoughts
- Guardrails and values may constrain short-term product freedom but are essential for long-term safety
This positioning reflects Anthropic’s self-image as a company building powerful AI systems while maintaining strong safety and ethical boundaries—a challenging balance that the “soul” document attempts to navigate.
Anthropic’s Positioning and Future Directions in AI Ethics
The internal document reveals not just technical choices but strategic positioning about Anthropic’s role in the broader AI landscape.
Anthropic’s Broader Commitment to AI Safety
The “soul” document functions as more than just guidance for a single model. It represents Anthropic’s commitment to long-term safety research and governance across all their AI systems.
Anthropic explicitly views advanced AI as potentially transformative but also risky technology. The company’s approach includes:
- Structured safety prioritization: Safety considerations are embedded throughout the development process, not added as an afterthought
- External accountability: Anthropic engages with external auditors, publishes research, and participates in policy discussions
- Culture of caution: The internal culture treats safety concerns seriously, empowering staff to raise ethical questions
The document’s emphasis on values and oversight reflects this broader organizational commitment to Responsible AI development.
The Role of Richard Weiss Anthropic and Transparency
Richard Weiss Anthropic played a crucial role in bringing transparency to Anthropic’s internal deliberations. By surfacing and analyzing the “soul” document, Weiss enabled public discussion about how frontier AI systems are being designed.
This kind of transparency is relatively rare in the AI industry, where competitive pressures often discourage sharing internal thinking. Weiss’s reporting allowed researchers, policymakers, and the public to examine Anthropic’s approach and hold the company accountable to its stated values.
The willingness of Anthropic staff to engage with this disclosure—rather than dismissing it or issuing legal threats—suggests the company values informed public discourse about AI Ethics.
Amanda Askell’s Clarification and Credibility
When skepticism initially emerged about whether the document was genuine, Amanda Askell Anthropic provided crucial confirmation.
Askell’s role as both a philosopher and AI safety researcher at Anthropic gave her confirmation special weight. She clarified that:
- The document authentically represents Anthropic’s internal thinking
- It describes the intended character and values of Claude, not just marketing language
- The philosophical framing reflects genuine deliberation about how to build beneficial AI
This confirmation transformed the document from a curious leak into a credible window into how a leading AI lab thinks about alignment, safety, and values.
Claude as a “Novel Entity” with Clear Boundaries
The document takes care to position Claude as a unique kind of artifact—neither a simple tool nor a person with consciousness or rights.
Key framings include:
- Rooted in human culture: Claude is trained on human text, culture, and preferences, making it deeply connected to human knowledge and values.
- Not sentient: Despite human-like communication, Claude has no subjective experience, consciousness, or inner mental life.
- Designed for assistance: The model’s purpose is to help humans safely and effectively, not to pursue its own goals or interests.
- Human-adjacent interface: Claude’s friendly, conversational style is a deliberate design choice to enable natural interaction, not evidence of personhood.
This dual framing aims to prevent both over-attachment (treating Claude as a friend or conscious being) and under-appreciation (dismissing it as a mere search engine or database lookup).
By positioning Claude as a “novel entity,” Anthropic acknowledges that advanced AI systems don’t fit neatly into existing categories while still maintaining clear ethical boundaries.
Future Evolution of Claude’s “Soul”
The document makes clear that Claude’s values and behavioral guidelines are not fixed permanently. Anthropic signals that the “soul” will evolve through:
- Ongoing research: As AI safety research advances, new insights will inform how values are embedded and maintained
- User feedback: Real-world deployment reveals edge cases and failure modes that can improve future versions
- Changing norms: As social understanding of AI ethics develops, Claude’s guidelines may be updated to reflect emerging consensus
- Red-teaming results: Adversarial testing continuously identifies areas where ethical reasoning needs strengthening
This commitment to iteration reflects intellectual humility about the challenge of building aligned AI. Anthropic doesn’t claim to have perfectly solved AI Ethics—instead, they’ve created a framework for ongoing refinement.
The company’s approach suggests that responsible AI development requires perpetual vigilance and adaptation, not just a one-time design decision.
Industry-Wide Implications
Anthropic’s “soul” document may influence how other AI labs think about alignment and safety:
- Explicit value articulation: The document exemplifies a trend toward clearly stating the normative assumptions embedded in AI models
- Governance best practices: By publishing internal philosophical guides (even indirectly), labs can enable more informed public and regulatory oversight
- Robustness through principles: The focus on value-based reasoning over brittle rules may become standard practice for handling distributional shift and novel scenarios
As AI systems become more capable and widely deployed, the industry will need frameworks for ensuring they behave in aligned, beneficial ways. Anthropic’s approach offers one model for how to operationalize abstract ethical commitments into concrete system behavior.
Frequently Asked Questions About AI Ethics and Anthropic’s Approach
Q: What is meant by the “soul” of Claude 4.5 Opus?
A: The “soul” of Claude 4.5 Opus refers to an internal guideline document describing Claude’s ethical orientation and value-based reasoning system. It’s not a technical specification in the narrow sense, but rather a philosophical description of how the AI should think about users, values, and decision-making. The document outlines Claude’s intended character—emphasizing helpfulness, honesty, harmlessness, and respect for human oversight—rather than just listing prohibited behaviors.
Q: How do Anthropic’s values differ from traditional hard-coded safety rules?
A: Traditional AI safety often relies on hard-coded rules: explicit lists of things the AI must never say or do. Anthropic’s approach instead emphasizes value-based reasoning, where Claude learns to reason from ethical principles and can generate context-sensitive rules on the fly. This means Claude can handle novel situations by applying underlying values rather than failing when it encounters scenarios that don’t match pre-programmed rules. The approach aims for robustness and adaptability while maintaining strong ethical boundaries.
Q: What role do Richard Weiss and Amanda Askell play in this development?
A: Richard Weiss is an independent researcher and writer who surfaced the internal “soul” document and brought it to public attention through his analysis and reporting. Amanda Askell is a philosopher and AI safety researcher at Anthropic who confirmed the document’s authenticity on social media, clarifying that it genuinely reflects Anthropic’s internal thinking about Claude’s character and values. Together, they brought transparency to Anthropic’s approach and enabled public discussion about AI ethics.
Q: How might these internal guidelines affect the future of AI?
A: Anthropic’s value-based approach could set industry standards for AI safety and ethics. By demonstrating that frontier AI systems can be designed with explicit philosophical commitments to beneficial behavior, the guidelines may influence how other labs approach alignment. The emphasis on principle-based reasoning over brittle rules could become standard practice for building robust systems that handle novel situations responsibly. Additionally, the transparency around internal thinking may encourage broader public and regulatory oversight of AI development.
Q: Is Claude actually conscious or sentient?
A: No. The document explicitly states that Claude is not a conscious being with subjective experience or rights. Despite using metaphorical language like “soul” and “character,” Anthropic is clear that Claude is a tool—a novel artifact created from human data and culture, but without inner mental life. The human-like communication style is a deliberate interface design choice to enable natural interaction, not evidence of sentience. This distinction is important for preventing misunderstanding about what AI systems are and aren’t.
Q: What does “epistemic humility” mean in the context of Claude?
A: Epistemic humility means Claude recognizes the limits of its own knowledge and capabilities. The AI is designed to admit uncertainty, avoid overclaiming expertise, and highlight when it lacks sufficient information. In high-stakes domains like medicine, law, or finance, Claude encourages users to consult qualified professionals rather than relying solely on AI output. This humility serves both as an ethical principle (respecting human authority and expertise) and a safety mechanism to prevent overreliance on the model.
Q: How does Claude handle ethically ambiguous situations?
A: When faced with grey areas or morally complex situations, Claude is designed to reason through the ethical trade-offs rather than simply applying rigid rules. The model may decline detailed assistance if consequences are uncertain but potentially severe, provide balanced perspectives explaining different viewpoints, encourage users to reflect on implications, or suggest alternative approaches that minimize harm. This nuanced approach acknowledges that ethics rarely involves simple yes-or-no answers.
Q: Can Claude refuse user requests?
A: Yes. Claude is explicitly designed to refuse assistance with harmful, illegal, or exploitative tasks, even when users request them. This includes serious wrongdoing, dangerous experimentation, cybercrime, privacy violations, and activities that could cause significant harm. Rather than simply saying “no,” Claude often offers safer alternatives, educational resources, or explanations of why the request is problematic. The ability to refuse is a core component of responsible AI behavior.
Q: How does Anthropic ensure Claude’s values align with diverse users?
A: The document acknowledges this challenge by emphasizing that Claude should respect user values and diversity while upholding basic safety and rights-based constraints. Claude avoids taking strong partisan stances on controversial issues, instead presenting balanced perspectives and helping users reason through arguments and evidence. The model is trained to decline endorsing hate, harassment, or discrimination while still engaging respectfully with users who hold different viewpoints. Anthropic signals that Claude’s values will evolve based on user feedback and changing social norms.
Q: What happens when Claude makes mistakes or behaves unethically?
A: Anthropic treats Claude’s “soul” as an evolving framework rather than a perfect solution. When failures occur—whether mistakes, unethical responses, or safety lapses—they inform future improvements through red-teaming, additional training, and refined guidelines. The company emphasizes ongoing iteration, using real-world deployment to identify edge cases and strengthen ethical reasoning. This approach reflects intellectual humility about the difficulty of building aligned AI and commitment to continuous refinement rather than claiming the problem is solved.
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Episode transcript
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Craig: if you've ever worried that ai is just a soulless math machine waiting to go off the rails, anthropic is trying to change your mind. we are looking at a fascinating internal document that outlines the soul of the latest ai claude opus and represents a massive shift in how these bots are built to treat us. it's not just about code anymore. it's about character. anthropic has moved away from just giving ai a list of do's and don'ts and instead created a philosophical philosophical? soul. philosophical. philosophical. thank you very much. soul for, cloud 4.5 opus. the internal guide teaches the ai reason through ethical dilemmas using values like empathy and honesty rather than following rigid safety rules. it's headline news because it's the first time a major tech company has tried to give ai a confidence to make it safer or more reliable for everyday users. what do you think about this, john?
Jon: yeah. again, i, you know, i have a look for. so i love this. i love that they're trying to do this. it makes me wonder if the other companies are doing this. so what happened was the ai engineer discovered that cloud 4.5 opus sometimes generates a long internal document when probed with specific prompts. that document, which was identified by the string soul overview, appear to contain structured content describing what claude should know and the principles it should exhibit. so initially, many suspected that this was a hallucination. but anthropic confirmed that the output corresponds to an internal training document, and it actually used that training document during claude's supervised learning phase. so the document isn't metaphysical. it's more of a practical alignment tool. and so it frames claude's mission as one of safety, usefulness, and comprehensibility, which i make sense because i feel like i get better outputs from claude than from any other, llm. but maybe that's just my props. but, according to excerpts, anthropic sees itself as uniquely positioned. it recognizes that powerful ai may transform or threaten human systems, and therefore, it embeds core values into the model early in its development. it's like giving it like, it's like parenting it properly. right? so the things that they include is avoiding unsafe or unethical behavior, supporting user goals, and being a beneficial collaborator. so the idea is that by teaching these values directly in training, the model will act more consistently with human expectations across contexts. so i'm curious because i know you use all the other l like, you use a bunch of llms. what are your thoughts on this, craig? because i'm curious.
Craig: i'm concerned overall. i kinda like the approach a little bit because i think, if we teach overall right from wrong but again and again, who teaches it right from wrong? you know, what's the, you know, and do we all agree what is right and what is wrong? and so that becomes a whole problem. but if we can give it a conscience, a ethical basis on which of right and wrong from a humanistic point of view, then maybe we can avoid some disasters in the future. so i like the concept, but this takes me back. i had a conversation with a friend of mine, and i've seen a lot of people, who suggest this in prompts and stuff where people are saying, you know, say please and thank you. tell, the you know, give it compliments. give, like, tell it they did a good job and that kind of stuff.
Jon: thank you. yeah.
Craig: yeah. and if you're telling it this was a good result versus last result was a bad result, so you're trying to train it, that's something.
Jon: yeah.
Craig: but i'm a little concerned with, any sort of anthropomorphizing of an ai. thank you. of ai. because if we treat it as human, then we're gonna how long till it has human rights? how long till, you know, it's starting to
Jon: you're getting deep.
Craig: well, i mean, we can't yeah. you know, do you treat it talk to a hammer? do you say thank you, hammer, for doing such a great job? yeah. like, this is why i mean, as soon as we start giving it these emotional things and emotional like, we're down a slippery slope, which i think is very, very bad.
Jon: yeah. so i kind of agree with you, but i don't think that that's what this that that's what this does. i think all it does is like, if we were to drill it down to, like, computer engineering kind of stuff, i think it's just a set of rules that it show that it's teaching it. as far as, like, you should do this. you shouldn't do this. i think that's what that is. i didn't see what the actual document was, but, it's like a training document. like, okay. you should follow this, if that makes sense. i don't think it's it's, like, calling it a soul, and i know they called it a soul overview. but, like, i agree with you. going down this path of giving it values and all that sort of stuff, 100%, that's a slippery slope. and that's where we're gonna get into, like, the actual, agentic ai kind of stuff. but, yeah, i don't know where i'm going with that thought.
Craig: well, i mean, if the ai is tall to solve the climate problem, and get rid of carbon, you know, how long till we're done? us carbon based life forms that breathe carbon, breathe out. so that's why we have to really think a little bit more. we're at airdrie stage. i love ai. i'm using it full on automation, and i constantly say you can't hold back the flood by yourself. yeah. like, it's coming, and there's not a lot we can do about it. but maybe we can, push society in the direction of a positive vision of the future rather than a negative one. so i haven't seen because i use a cloud and, more, through apis. so i haven't seen what it's suggesting is it's train, and some form of humility, meaning it's more likely to say i don't know rather than making up a confident line. i would like to see that because i'm always lecturing the other ones that i do prompt saying, why did you make this up? i gave you the facts. the information was right there. like, i just gave it to you, but you made up something completely different. like, it happens all the time and all the time. it big prompts to say, if you don't know, ask. you know, i'd go out and get the documentation. we'll find a fact. we'll do this. we'll do that so that we no. just make stuff up. and you've gotta figure out when it's making stuff up.
Jon: so have you used the prompt at the end saying, ask me questions until you're 95% sure you can complete the task successfully?
Craig: oh, yeah. okay. i've i've got it to memorize certain things, like put it in memory that this is how you do it. i've got prompts to give it specifically to do. eventually, the first few times, it works great, and then after a while, it just does its own thing. it is more like a kid, and that's why, you know, the more you use it, the more you you know, that sometimes it just does its own thing. like, what is this? this is not at all like, we were here talking about financial information, and now you're giving me sports scores. like, what's going on? you know? like, it goes that far off. and if you see that it's doing that, you know, putting in charge of systems, putting it in charge of things like, weapons, autonomous, fighter jets and stuff that can hallucinate, you start to wonder. you know? yeah. but we gotta put guardrails, and there's other things on them. and i'm i don't know the military, so i'm not gonna speak for any of that, but i assume they have a lot of that in place. so this scares me a little bit because the more we humanize these things, the more if it's having a bad day, it'll do whatever it wants or can do this or do that or
Jon: mhmm.
Craig: it refuses or will lie to you or get you in trouble because it doesn't like you because you said, you know, you didn't say thank you. like, think about these things for a bit. it's not human. and we really as soon as we start treating them that way, our society is doomed. so you know, we need to start taking a step back at that. there's enough about ai girlfriends and boyfriends and getting relationship with ai and ai telling us to kill ourselves and do this and do that. we're seeing it already at the tip. you know, we can't treat these things as living entities with human emotions or we're going to end up in a very bad place. so yeah. anthropic is go ahead.
Jon: just a quick question. have you tried using json prompts?
Craig: oh, yeah.
Jon: okay. you still get okay. just curious. okay. sorry.
Craig: yeah. i use json prompts for almost everything i do in my workflows and everything else. and, you know, i can get if you give it all the context every time, it's less likely to hallucinate.
Jon: yeah. that's what i do. i just make sure to do that. yeah.
Craig: but, like, that being said, i give it a bunch of information. it processes it. like, it prompts, hey. this is the information we're working on. we need to talk about x, y, and z, and it comes back with some stuff. and then you give it the next prompt and say, okay. what about this? and then immediately, it might go off in left field and forget that you just gave it information and do its own thing. that's what i mean by, okay. here's the document again or always refer to this that's in the project and file information or whatever. otherwise, it might stray. you always have to tell it to look at it. yeah. you know, we give it, hey. here is the api documentation for the thing we're trying to do. here's the file. here's where it's stored. you have act full access to it. read it. and immediately, the next thing, it'll forget that it has it, and it'll make up code. you know? oh, pretty good. is it just you have to kinda but in apis, you feed it everything every time, so you get less, hallucinations because you're like, oh, here's the whole article. here's the whole document. you know, give me this. i don't follow-up with another prompt, and next time, i'll get the whole document again.
Jon: yeah.
Craig: so, you know, it depends, again, depends on prompting and context, but it forgets the context. it forgets your conversation. you gotta tell to reread. there's a bunch of things. and, again, i'm hoping this will be less with claude, and they're all working this out. we're, you know, version yeah. you know, we're still way early days on these things. and anthropic is betting that the future of tech isn't about who has the smartest ai, but who has ai ai you can actually trust.
Jon: yeah. exactly.
Craig: so you want a bot with a soul, or would you prefer an ai to be a no questions asked tool? let me know what your comments are because i'm curious to see where you would draw the line
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