An engineer builds an AI agent to manage his own life, decides an unrestricted "does everything" agent is too dangerous to trust, and ends up creating the internal agent platform that now runs 30 agents across his entire company.
Ori Shoshan, tech lead at Cyera, walks through the guardrails, citation system, and knowledge graph that turned "let the agent do anything" into "let the agent do exactly what it's supposed to, and nothing else."
What we cover: – Why one engineer built his own AI agent in his living room, and how it grew into Cyera's internal agent platform – Whitelisting tools instead of blacklisting them, plus the "escape hatch" that keeps agents honest – Backing every claim with a citation and using a second model to catch hallucinations before they reach a human – Trading RAG for a knowledge graph the agent can walk like a wiki – Turning "use this platform" into "build your own agent" to drive adoption across an entire engineering org – Running agents on confidential data that can investigate everything but can only ever say what's been cleared
Chapters: 00:00:00 - Introduction 00:02:04 - Meet Ori Shoshan and what Cyera does 00:06:50 - The living-room spark: why Ori built his own agent 00:11:09 - Whitelisting tools instead of blacklisting them 00:12:55 - Why every claim needs a citation 00:15:35 - Reducing hallucinations with clean-context verification 00:21:04 - Taking Borg to Slack: the first agents at work 00:25:33 - Why naming your agent drives adoption 00:39:53 - Knowledge graphs over RAG 00:52:00 - The AI Captains: scaling adoption with carrots, not sticks
🌐 Tessl: https://tessl.io 🔔 Subscribe for weekly episodes on AI-native development
Have you built guardrails like this into your own agents? Let us know what's worked (or blown up) for you in the comments.
Join the AI Native Dev Community on Discord: https://tessl.co/4ghikjh
Podden och tillhörande omslagsbild på den här sidan tillhör
Tessl. Innehållet i podden är skapat av Tessl och inte av,
eller tillsammans med, Poddtoppen.