1.0Megagonhttps://megagon.ai/jp/Natalie Nunohttps://megagon.ai/jp/author/natalie/rich600338<blockquote class="wp-embedded-content" data-secret="Tk9dnTzstj"><a href="https://megagon.ai/jp/publications/l-a-k-e-logic-agent/">L.A.K.E.: Logic Agent for Knowledge Extraction in Data Planning</a></blockquote><iframe sandbox="allow-scripts" security="restricted" src="https://megagon.ai/jp/publications/l-a-k-e-logic-agent/embed/#?secret=Tk9dnTzstj" width="600" height="338" title="“L.A.K.E.: Logic Agent for Knowledge Extraction in Data Planning” — Megagon" data-secret="Tk9dnTzstj" frameborder="0" marginwidth="0" marginheight="0" scrolling="no" class="wp-embedded-content"></iframe><script> /*! This file is auto-generated */ !function(d,l){"use strict";l.querySelector&&d.addEventListener&&"undefined"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!/[^a-zA-Z0-9]/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret="'+t.secret+'"]'),o=l.querySelectorAll('blockquote[data-secret="'+t.secret+'"]'),c=new RegExp("^https?:$","i"),i=0;i<o.length;i++)o[i].style.display="none";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute("style"),"height"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):"link"===t.message&&(r=new URL(s.getAttribute("src")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener("message",d.wp.receiveEmbedMessage,!1),l.addEventListener("DOMContentLoaded",function(){for(var e,t,s=l.querySelectorAll("iframe.wp-embedded-content"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute("data-secret"))||(t=Math.random().toString(36).substring(2,12),e.src+="#?secret="+t,e.setAttribute("data-secret",t)),e.contentWindow.postMessage({message:"ready",secret:t},"*")},!1)))}(window,document); //# sourceURL=https://megagon.ai/wp-includes/js/wp-embed.min.js </script> L.A.K.E. (Logic Agent for Knowledge Extraction) introduces an agentic data planning framework that maps natural language questions into executable workflows. L.A.K.E. helps developers understand, evaluate, and optimize how AI agents operate over complex enterprise data environments.https://megagon.ai/wp-content/uploads/2026/05/LakePublication.png1600900