BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//Austin AI Alliance - ECPv6.17.2//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-ORIGINAL-URL:https://austin-ai.org
X-WR-CALDESC:Events for Austin AI Alliance
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:America/Chicago
BEGIN:DAYLIGHT
TZOFFSETFROM:-0600
TZOFFSETTO:-0500
TZNAME:CDT
DTSTART:20250309T080000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0500
TZOFFSETTO:-0600
TZNAME:CST
DTSTART:20251102T070000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0600
TZOFFSETTO:-0500
TZNAME:CDT
DTSTART:20260308T080000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0500
TZOFFSETTO:-0600
TZNAME:CST
DTSTART:20261101T070000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:-0600
TZOFFSETTO:-0500
TZNAME:CDT
DTSTART:20270314T080000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:-0500
TZOFFSETTO:-0600
TZNAME:CST
DTSTART:20271107T070000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=America/Chicago:20260916T173000
DTEND;TZID=America/Chicago:20260916T203000
DTSTAMP:20260812T172940Z
CREATED:20260702T213128Z
LAST-MODIFIED:20260812T172940Z
UID:10000712-1789579800-1789590600@austin-ai.org
SUMMARY:Human Orchestration of Tools and Agents - Beyond the Prototype II — Self-Recursive Agents
DESCRIPTION:Many organizations are stuck in “AI purgatory”; building impressive prototypes that fail to scale\, break quietly in production\, or degrade in quality over time. To achieve true ROI\, AI systems must move beyond simple task execution and become self-aware\, self-healing\, and self-improving. \nEveryone has a demo. AI demos work\, but production breaks. The gap between “works in a demo” and “runs reliably at scale” is where organizations get stuck. This session teaches you a framework for closing this gap.  \nThis session is for builders who have hit the wall with prototype agents that degrade or stagnate. We are going beyond the prototype to tear down a self-evolving agent architecture. Mario will show you the four capabilities every production AI systems needs. \nWhat You’ll Be Able to Learn\n\nShared Memory – How agents learn from each other\nTrust Scoring – How to know which outputs to trust\nPrompt Evolution – How systems improve themselves weekly\nSafe Governance – How to deploy changes without breaking production\n\n What Makes This Session Different\n\nVery few have a system that improves itself in production\nBased on real architecture\, real data\, and real lessons\nWe are addressing the hard gaps: FadeMem decay\, pruning governance\, and the MinionS protocol (achieving 97.9% performance at 18% cost).\nThis is a live\, production-grade system teardown. Mario will show you the exact infrastructure (n8n\, Supabase\, Qdrant\, OpenRouter) that runs MEF Solutions.\n\nWho Is It For\n\nAI engineers and builders who are tired of brittle prototypes and want to deploy resilient\, self-improving systems.\nTechnical founders trying to bridge the gap between AI experimentation and AI operations.\nRevOps and GTM leaders who need autonomous architectures to drive actual revenue\, not just engagement.\nAnyone who is done watching demos that don’t survive contact with real users\, and wants their AI still working next quarter\, not just this one.\nBefore You Arrive \n\nReview your current agent architecture and identify where the feedback loops are broken.\nCalculate the token cost and failure rate of your most complex autonomous workflow.\nBring your skepticism. We’re going to look at what actually works in 2026.\nInstructor Bio\nMario Facussé is the Managing Director of MEF Solutions\, where he builds AI-powered revenue systems for growth-stage companies. He designs and operates autonomous agent architectures that self-improve in production; not prototypes\, not demos\, but systems that run his own company. His work draws from peer-reviewed research in self-evolving agents\, collaborative reinforcement learning\, and autonomous optimization\, implemented on practical infrastructure. He’s spoken at leading AI conferences and events and advises companies on strategy\, GTM\, operations\, revenue\, and bridging the gap between AI experimentation and AIoperations. \n 
URL:https://austin-ai.org/event/hota-beyond-the-prototype-2/
LOCATION:The Center for Government and Civic Service\, ACC Rio Grande: Building 3000\, 1218 West Avenue\, Austin\, TX\, 78701\, United States
CATEGORIES:AAIA,HOTA
ATTACH;FMTTYPE=image/png:https://austin-ai.org/wp-content/uploads/2026/07/event_graphic_v2-scaled.png
ORGANIZER;CN="Austin AI Alliance":MAILTO:info@austin-ai.org
END:VEVENT
END:VCALENDAR