The Right Way To Build AI Agents — With Nvidia's Adel El Hallak and ServiceNow's Joe Davis
TL;DR
ServiceNow claims a 90% automation rate for its own support desk — Joe Davis says ServiceNow now resolves most L1 IT requests automatically, with some resolution times dropping by as much as 99% when an AI can act in minutes instead of waiting days for a human queue.
The production agent stack is multi-model, not one giant brain — Adel El Hallak describes ServiceNow’s deep-research setup as at least seven agents: an orchestrator, a planner, and several specialized sub-agents fine-tuned on Nvidia’s open NeMoTron models for tasks like critique, fact gathering, and forecasting.
OpenAI or Anthropic may orchestrate, but Nvidia provides the runtime and safety rails — the partnership centers on Open Shell, Nvidia’s open-source secure runtime that sandboxes agents, enforces permissions at runtime, and starts from a “deny by default” posture.
The enterprise risk is the ‘lethal trifecta’ — Hallak says CISOs get nervous when an agent has all three of these at once: access to the open internet, access to the company knowledge base, and access to a coding terminal.
Harness engineering is becoming as important as model quality — both guests argue that an agent’s performance now depends heavily on the tooling around the model: file access, code interpreters, MCP tools, skills, integrations, governance, and orchestration loops.
The next frontier is broader enterprise adoption — and eventually physical AI — Davis expects the next few years to be about deploying agents into complex business workflows like HR and CRM, while Hallak thinks the same governance layer will eventually extend from humans and agents to robots and physical assets.
The Breakdown
ServiceNow says it has already automated 90% of its own L1 support requests by pairing Nvidia’s secure agent runtime with tightly governed enterprise workflows. The big idea is that useful AI agents aren’t single models or free-range “Claudes” on a spare Mac Mini — they’re multi-model systems wrapped in deny-by-default controls, sandboxes, and policy enforcement.
Was This Useful?
Share
Keep Reading
Make Alcreon Yours
Tune your feedFive quick questions, and the feed ranks what matters to you first.Or just get notified
The weekly Echo. Signal worth keeping in your inbox.
Every new piece, announced on X.
Read Next
See all
Playbook
Tasteful Skills
“Tasteful Skills” argues that the best agent skills are not documentation or best-practice lists.

Playbook
The Art of Tasteful Prompting
Learn how tasteful prompting helps you move beyond generic AI output by shaping context, style, and judgment from the start.

Playbook
The Codex /goal Playbook
OpenAI shipped /goal for the Codex CLI. It turns a prompt into a persisted, self-continuing contract.