“A rule written in a prompt is not deterministically enforced. A guardrail is actual machinery: a gate, a check, a human, a limit in code.”
sputnikintelligence.com
From a conference talk the podcast aired as a segment, on making AI workflows hold up beyond the demo. Porter is separating instructions placed in a prompt from real controls built around the model.
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…deployments at large companies. Her company, Moyer Group AI, provides education, strategy, and consulting on AI tools and where it belongs in your tasks and workflows. And it's those workflows that she's going to talk about, how to make durable AI-augmented workflows. Help me welcome Heidi Porter.
All right. Thank you. Up the clicker here. Good morning. I'm Heidi Porter. Quick show of hands. Who has had an AI pilot that did not make it past the demo stage or stalled at the start of production? So there's a good amount and congratulations to all the rest of you who just, you know, hit it on the first time, right? So a lot of times these workflows fail because it's not because the model was the problem. It was because the LM was asked to do too much. And Don and Jeff just gave great talks about when to say no to AI and when to say yes to AI. And so sometimes people ask it to hold the data, be the system of record. It's not a database, make the decision and check its own work. The question I want you to come away with today is to look at the task in the workflow and decide right what is the right mechanism for the task, okay? And then how to evaluate right answers and how to catch it when it's wrong. So evaluation…
Thank you so much, Heidi. That was great. I love how you digged in or dug into each of those workflows. Super practical. Whether you're an early stage startup or a Fortune 500, it's critical that you have an amazing website that looks handcrafted, but where you ship that website, updates to that…
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