AI-First for Restaurants

It was just three weeks ago that we were breaking down the battle of the LLMs around the Super Bowl.

GPT vs. Claude vs. Gemini. Bigger models. Better benchmarks. Faster releases.

But that game is over. And for restaurant leaders and operators, the question isn’t who has the smartest model.

It’s this:

Scheduling. Labor forecasting. Inventory. Marketing calendars. Guest feedback. CRM. Approvals. Reporting.

We’ve officially moved from the battle of the models….to the battle of the agent platforms.

And this week, those platforms started putting real points on the board.

If this shift from model wars to agent platforms feels big — it is.

And if you’re wondering what all this buzz around AI and agents actually means for restaurants, that’s exactly why we’re hosting tomorrow’s restaurant-only roundtable — it’s time to lean in, connect the dots between AI and the future of work, and what it really means to lead a restaurant business in this next phase.

We hope you’ll join us!

For restaurants, this new wave of AI could be a reset of the playing field. Every major player just revealed their blueprint for the agent era and it’s all about control, orchestration, governance, and integration.

On February 5th, OpenAI launched Frontier — a full enterprise platform for building, deploying, and managing agents with governance and control.

Early customers include Uber, State Farm, Intuit, Thermo Fisher.

The bold move? Frontier is model-agnostic. It supports agents built on Google, Microsoft — even Anthropic.

For restaurants, that’s significant.

If an agent can reconcile marketing performance, update CRM segments, forecast demand, and generate reports, without someone manually logging into five different systems, the entire way work gets done changes.

The rollout has already rattled traditional SaaS players. If an agent can execute workflows without a human ever touching your CRM (or any other system), what happens to per-seat licensing?

Fortune called Frontier a bid to become the “operating system of the enterprise.”

Read more about Frontier here:

While OpenAI is playing infrastructure, Anthropic is leaning into daily utility.

And for restaurant leaders, that matters.

Claude Cowork has moved from impressive demo to something much more practical:

Weekly performance reports.
Recurring briefs for GMs.
Organizing shared drive files.
Multi-step workflows that normally require three people and a follow-up email chain.
Memory portability across systems.

For multi-unit operators juggling labor, marketing, guest feedback, and vendor coordination, this isn’t about novelty. It’s about time back.

Underneath it all is something bigger: MCP (Model Context Protocol).

MCP is becoming the plumbing of the agent economy — a universal way for agents to connect to Slack, Drive, databases, and internal tools without building one-off integrations every time.

And for restaurant brands running on fragmented tech stacks, that plumbing is everything.

Here’s an 8 minute video that walks thru Claude’s recent update:

Perplexity’s “Computer” may be the most forward-looking move of the bunch, and for restaurant leaders, it points to where this is heading.

Instead of relying on one model, it coordinates 19 different AI models into a single system.

Claude for reasoning.
Gemini for research.
GPT for long context.
Specialized models for image and video.

But the important part isn’t the model list. It’s the orchestration.

For example, you can now describe the outcome:

Behind the scenes, a coordinated group of specialized agents divides the work, shares context, and hands tasks off automatically.

That’s what a swarm of agents really means — a digital team with defined roles working toward one objective.

Imagine this in a restaurant context:

You see one clean output. Under the hood, multiple agents handled different parts of the workflow.

CEO Aravind Srinivas described it this way:

For restaurant operators managing multiple systems, vendors, and data sources, this is the real unlock.

It’s using the right brain for the right job — at the right moment.

Read more about Perplexity Computer here:

Then there’s OpenClaw. The fastest-growing open-source AI project ever.

145,000 GitHub stars in weeks.
Mac mini shortages.
A rebrand war.
An OpenAI acqui-hire.

Imagine agents that:

One user wrote:

And OpenAI’s move to bring the founder in, while committing to keep it model-agnostic under a foundation, signals something bigger:

The future is multi-agent. And open-source will be part of it.

As agents move from suggesting to doing, the risk profile changes immensely.

This isn’t just text generation anymore. It’s execution.

The right approach is practical and disciplined:

Start in a sandbox (if you can).
Limit permissions. Isolate the environment. Don’t give an agent access to guest data, payroll, or POS systems on day one.

Always supervise.
Begin read-only. Then suggested actions. Then supervised execution.

Experiment small first.
Draft the report. Summarize the inbox or guest feedback. Flag labor anomalies.

We’re still early in this shift and the tools aren’t perfect. The playbook is still being written and changing every day.

Go slow, start small, and be safe.

For restaurant leaders, this is no longer a wait and see.

The models got us onto the field, but the agent platforms will shape how work actually gets done around and inside your restaurants.

And if the last few weeks are any indication, the pace isn’t slowing down.

So buckle up.

We’re only a few minutes into the first quarter — and the teams that lean in now will be the ones setting the pace for the rest of the industry.

Onward.