Speaker

Elliot Margot

Elliot Margot

Microsoft MVP M365 Copilot & Copilot Studio

Microsoft MVP M365 Copilot & Copilot Studio

Lausanne, Switzerland

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Elliot Margot leads enterprise Copilot and agent engagements at a Microsoft partner, one of roughly fifteen European partners certified to deliver Microsoft's Jumpstart program.

Based in Lausanne, he takes generative AI and automation solutions from scoping through to production: multi-agent architectures, enterprise RAG pipelines, and custom MCP integrations. More than 60 use cases designed across 17 industries, around fifteen AI architectures running in production, and a procurement agent featured by Microsoft as an official Customer Story.

He works natively in German, English and French, and spends most of his time fixing agents that were shipped too early.

Elliot Margot dirige les engagements Copilot et agents d'entreprise chez un partenaire Microsoft, l'un de la quinzaine de partenaires européens habilités à délivrer le programme Jumpstart de Microsoft.

Basé à Lausanne, il mène les solutions d'IA générative et d'automatisation du cadrage jusqu'à la production : architectures multi-agents, pipelines RAG d'entreprise, intégrations MCP sur mesure. Plus de 60 cas d'usage conçus dans 17 secteurs, une quinzaine d'architectures IA en production, et un agent d'appel d'offres retenu par Microsoft comme Customer Story officielle.

Trilingue allemand, anglais, français, il passe l'essentiel de son temps à réparer des agents mis en production trop tôt.

Area of Expertise

  • Business & Management
  • Information & Communications Technology

Topics

  • Copilot Studio
  • Microsoft Copilot
  • AI Agents
  • Power Platform
  • Generative AI
  • Multi-Agent Systems
  • Power Automate
  • Azure AI
  • Microsoft 365
  • Conversational AI
  • RAG
  • Agentic Workflows

Agents that died in production: 5 Copilot Studio failures and what we learned

Most Copilot Studio talks show the build, the demo, the applause. This one shows the graveyard. Five real agents from real Jumpstart engagements that shipped, struggled, and got pulled. No vendor names, no client names, just the patterns that keep killing internal AI projects. The knowledge soup: an agent grounded on an entire SharePoint site that confidently returned policy from 2019 alongside policy from 2025 - why broad RAG without hygiene is a hallucination factory and what to scope instead. The over-trusting agent: a procurement assistant that took the user's word on their approval level and called the back-end API anyway - how agents inherit privilege confusion from the prompt and the simple identity check that fixes it. The expensive intern: an agent that worked beautifully and burned through tokens and Copilot Studio messages faster than the team it was meant to assist - how to instrument cost from day one and what to do when the curve goes vertical. The forgotten agent: built in two weeks, launched on a Friday, dead by month two - why 'we'll add adoption later' never works and the three things that make agents actually used. The frankenstein: sixteen Power Automate flows, four custom connectors, three knowledge sources - one upstream API change took the whole thing down, and how to design for the failure mode you will absolutely have. You leave with an honest mental model of what breaks, a 5-point pre-deployment checklist, and the confidence to say no when an agent is not ready to ship.

Live Build: 3 IT Helpdesk Agents in 60 Minutes

The promise: walk in with a laptop, walk out with three working Copilot Studio agents shipped to your tenant. Zero theory, pure keyboard.

We skip the "what is Copilot Studio" intro (you can Google that) and ship three production-style agents in one room, live, with the screen visible and the gotchas called out as they happen.

Agent 1 - Password Reset Assistant (15 min): Adaptive Card welcome, knowledge connection to a self-service KB, Power Automate action to trigger Entra Self-Service Password Reset, fallback hand-off to L1 if validation fails.

Agent 2 - Software Request Triage (20 min): Topic with branching logic, DLP-aware data handling, connector to ITSM (ServiceNow / Jira), approval flow with manager check, audit logging.

Agent 3 - Device Enrollment Helper (15 min): Intune docs as knowledge source, decision tree for Windows / iOS / Android, Adaptive Card with QR-coded enrollment link per platform, telemetry hooks for analytics.

Final 10 minutes: ALM patterns to promote from sandbox to production, environment strategy, the gotchas the docs do not publish, Q and A.

This is not a workshop where you build along. It is a live build demo with screen, code, and decisions visible the whole time, designed so you can replicate every step in your own tenant after the session.

Cut RFP response time from days to hours with Copilot Studio

Your sales team spends 2 days on every RFP. 80% of the answers already exist in past proposals. Nobody can find them fast enough. This workshop builds the agent that changes that - no code, no IT ticket, no waiting.

We build together using Copilot Studio's no-code canvas. Starting point: a folder of past proposals in SharePoint. End state: an agent your sales team can use today to upload an RFP, extract the key requirements, and get a draft response grounded in your own content - in under 5 minutes.

What we configure together: connect the knowledge source (your SharePoint proposals folder), write the system prompt in plain English that tells the agent what to do with an RFP, test it against a real document, and publish it to Teams so anyone on the sales team can use it without a Copilot Studio license.

Just Copilot Studio, SharePoint, and a system prompt that does the heavy lifting. We also wire one Power Automate action: the agent exports the draft directly to a Word document ready for review. You leave with a working agent, the exact prompt template, and a reusable flow pattern to adapt for your own use case.

Power Conference 2026 Sessionize Event Upcoming

December 2026 Prague, Czechia

Elliot Margot

Microsoft MVP M365 Copilot & Copilot Studio

Lausanne, Switzerland

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