Definition
Guardrails
Rules built into an AI product to detect risk and route users to proper help.
From the episode “AI Relationship Coach That Sends You Back to Real Life”How founders on the podcast use it
Pre-set constraints inside a workflow, such as pricing rules and scope limits, that make fast automated output safe to send.
Why Your AI-Designed Brand Is Invisible, and the 3-Step FixPredefined limits on what an AI system can do, including escalation paths and human gates. Ross Barnes treats defining them as step one, not a compliance afterthought.
From $80M To $1B: The Scaling Lesson That Now Applies To Every AI WorkflowConstraints, checks, and permission boundaries that keep autonomous agents inside acceptable behavior. Without them, the system falls apart.
Vibe Coding Your MVP Is a Time Bomb: AI Workflows for Founders Who Want to Ship TwiceThe rules and limits that keep an AI's outputs accurate, safe, and inside its intended scope.
AI Heart Doctor, and 150 Fortune 500s Are BuyingHear it on the podcast5 episodes
AI Relationship Coach That Sends You Back to Real LifeWhy Your AI-Designed Brand Is Invisible, and the 3-Step FixFrom $80M To $1B: The Scaling Lesson That Now Applies To Every AI WorkflowVibe Coding Your MVP Is a Time Bomb: AI Workflows for Founders Who Want to Ship TwiceAI Heart Doctor, and 150 Fortune 500s Are Buying
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Related terms in AI Fundamentals
GPT (Generative Pre-trained Transformer)A family of large language models built on the transformer architecture and trained to generate human-like text from a prompt.GPT WrapperA thin AI product built on top of a foundational LLM without proprietary data, unique distribution, or genuine differentiation. The category of AI product most founders are building and fewest investors want to fund as foundational models grow more capable. Lacks the defensible IP or distribution moat required for long-term pricing power.Grounded Training DataTraining data derived directly from real-world, timestamped sources - internal Slack channels, company reports, PDFs, emails, public news archives - rather than generated synthetically by AI. Ben Turtle of LightningRod AI defines grounded data as the antidote to synthetic slop: it contains information the model doesn't already have, sourced from events that actually happened in a specific domain. Grounded training data is what enables a small model to outperform a frontier model on domain-specific tasks - not because the small model is smarter, but because it was taught things the frontier model was never shown.GroundingStanding barefoot on soil or grass. The claimed mechanism involves electron transfer from the earth; the claim isn't established science, and Steve Phillips says so himself.HallucinationWhen an AI model produces information that is false or made up but presents it as fact.Hallucination ToleranceThe acceptable error rate for AI outputs in a given system context. In consumer chatbots, high hallucination tolerance is acceptable — wrong answers are annoying but not dangerous. In healthcare eligibility determinations, medication routing, or financial compliance, the tolerance is zero — errors create legal liability, financial harm, or patient safety risks. Designing for zero hallucination tolerance requires architectural decisions (human-in-the-loop checkpoints, output traceability, auditability standards) rather than simply selecting better models. Softheon's target: 99.9999999% accuracy — exceeding air traffic control standards.Hallucination-Free AIAn AI system constrained to answer only from a specified data set, with no access to the broader internet or general training data. Eliminates invented or inaccurate responses by removing the source of uncertainty — the model can only cite what actually exists in the collection.Human-centered AIAn approach to building AI that puts people's needs, values, and wellbeing first throughout design and deployment.