Frontier launches for enterprises

Hi ,

OpenAI just launched Frontier for enterprise AI agents.

It's a platform that helps companies build, deploy, and manage AI agents that work across their entire business. Shared context, permissions, boundaries, identity for each agent.

HP, Intuit, Oracle, State Farm, Thermo Fisher, and Uber are first adopters.

This is OpenAI's play to turn AI from isolated tools into enterprise-wide coworkers.

But first, today's multi-platform social strategy and why your onboarding kills retention (then see what Frontier means for enterprise AI...)

🔥 Prompt of the Day 🔥

Multi-Platform Social Strategy System: Use ChatGPT or Claude

Act as a multi-platform social media strategist specializing in helping entrepreneurs stop wasting time on platforms that don't serve their business.

I need a complete social media strategy focused on platforms where my buyers actually are, with native content that works on each one.

Essential Details:

• Business Type: [WHAT YOU DO]

• Ideal Client: [WHO YOU SERVE]

• Main Offer: [WHAT YOU SELL]

• Price Point: [COST]

• Current Platforms: [WHERE YOU POST NOW]

• Weekly Hours: [TIME AVAILABLE]

• Team Size: [PEOPLE INCLUDING YOU]

• Current Approach: [HOW YOU CREATE CONTENT NOW]

Create one complete social strategy including:

• Platform Fit Audit (rate each platform 1-10 for client match, identify which 1-2 to focus on first, which to pause, explain why in plain language)

• Native Content Blueprints (format, length, tone, visual style for each priority platform, three example posts adapting same message natively, three "never do this" mistakes per platform)

• 30-Day Content Calendar (3:1 jab-to-right-hook ratio, native adaptation per platform, content recycling system to turn 1 idea into posts for all platforms in under 1 hour, best posting times, weekly workflow)

• Batch Content Templates (three "jab" templates per platform, one "right hook" template per platform, content batch day checklist to create full week in 2 hours, AI prompt to generate weekly ideas)

Stop wasting time on wrong platforms and create native content that converts.

💡 Marketing Monday 💡

Onboarding Drop-Off

Losing customers after signup is a silent killer.

Most businesses obsess over acquisition. They spend thousands getting people to sign up. Then they lose half of them in the first week.

Your first week determines lifetime value. Not your product. Not your pricing. Your onboarding.

The Problem

A customer signs up. They're excited. Ready to use your product.

Then they hit friction. Too many steps. Unclear instructions. No immediate value. They get confused. They get busy. They leave.

Most never come back.

You spent money acquiring them. You lost them before they saw value. You never get a second chance at first impressions.

Onboarding is your second first impression. The first was marketing. The second is showing them value immediately.

Map Every Step

Most founders don't know their actual onboarding flow.

They know what it's supposed to be. They don't know what users actually experience.

Map it. Every single step. From signup to first value moment.

Where do they click? What do they see? What decisions do they make? Where do they get stuck? Where do they drop off?

Track completion rates at each step. Find where people quit.

Remove Friction at Every Point

Every field in a form is friction. Every click is friction. Every unclear instruction is friction. Every delay before value is friction.

Ask for less information upfront. Pre-fill what you can. Skip steps that aren't essential. Clarify confusing language. Remove decisions that don't matter yet.

Your goal: get them to value as fast as possible. Everything else can wait.

Provide Immediate Value

Most onboarding delays value. "Set up your profile." "Connect your integrations." "Invite your team."

Users don't care about setup. They care about results.

Give them a win in minutes. Show them what your product does before asking them to configure everything.

Let them experience value first. Then ask them to optimize their setup.

Test Different Sequences

Some users need guidance. Some want to explore. Some need motivation. Some need education.

Test different onboarding lengths. Short versus long. Guided versus self-serve. Linear versus flexible.

Segment by user type. New users might need more hand-holding. Experienced users might want less.

Measure completion rates for each variation. Keep what works. Drop what doesn't.

Keep Optimizing

Onboarding isn't a one-time project. It's ongoing optimization.

As your product changes, onboarding needs to change. As you learn what works, update the flow. As users give feedback, refine the experience.

Track completion rates weekly. Watch where drop-off happens. Test improvements continuously.

First week loyalty predicts forever loyalty. Get that week right, everything else gets easier.

Did You Know?

AI analyzing tree rings discovered that forests have "memory" of disasters that occurred centuries ago, growing in patterns that prepare for specific threat types.

🗞️ Breaking AI News 🗞️

OpenAI Launches Frontier Platform for Enterprise AI Agents

OpenAI announced Frontier, a platform that helps enterprises build, deploy, and manage AI agents that work across entire businesses.

Available now to limited customers, broader availability coming over next few months.

What Changed

Previously, enterprises deployed AI agents in isolation. Each agent worked independently. Limited context. Limited access. Limited coordination.

Frontier gives AI agents shared business context, identity, permissions, and the ability to work across systems.

AI agents become "AI coworkers" that understand how the business works, access the right systems, and operate within clear boundaries.

How It Works

Understand the work: Connects siloed data warehouses, CRM systems, ticketing tools, and internal applications. AI coworkers understand how information flows, where decisions happen, what outcomes matter.

Plan, act, solve problems: AI coworkers reason over data, complete complex tasks, work with files, run code, use tools. Build memories from past interactions to improve performance over time.

Improve quality: Built-in evaluation and optimization. AI coworkers learn what good looks like and improve at work that matters most.

Identity and permissions: Each AI coworker has its own identity with explicit permissions and guardrails. Enterprise security and governance built in.

Early Results

Major manufacturer: Agents reduced production optimization work from six weeks to one day.

Global investment company: Agents deployed across sales process opened up 90%+ more time for salespeople to spend with customers.

Large energy producer: Agents helped increase output by up to 5%, adding over a billion in additional revenue.

Who's Using It

First adopters: HP, Intuit, Oracle, State Farm, Thermo Fisher, Uber.

Existing customers piloting: BBVA, Cisco, T-Mobile.

Frontier partners (AI-native builders): Abridge, Clay, Ambience, Decagon, Harvey, Sierra.

The Technical Approach

Built on open standards. Works with systems enterprises already have. No replatforming required.

Integrates existing data and AI where it lives. Supports applications already in use.

AI coworkers accessible through any interface: ChatGPT, Atlas workflows, existing business applications.

Works with agents developed in-house, acquired from OpenAI, or integrated from other vendors.

What Makes This Different

Most enterprise AI is siloed. Each tool operates independently. Limited context. No coordination.

Frontier creates a "semantic layer for the enterprise" that all AI coworkers can reference.

They understand business operations. They access shared context. They coordinate across systems.

This is OpenAI's answer to the "opportunity gap"—what models can do versus what teams can actually deploy.

Forward Deployed Engineers

OpenAI pairs Forward Deployed Engineers (FDEs) with enterprise teams.

FDEs work side-by-side to develop best practices for building and running agents in production.

Direct connection to OpenAI Research. As enterprises deploy agents, OpenAI learns how models need to evolve for real work.

Feedback loop: business problem → deployment → research → improvement.

Why This Matters

75% of enterprise workers say AI helped them do tasks they couldn't do before.

But deployment is fragmented. Agents are isolated. Each new agent adds complexity instead of helping.

Frontier addresses the gap between AI capabilities and actual enterprise deployment.

It's OpenAI's play to own enterprise AI infrastructure the way Salesforce owns CRM or Microsoft owns productivity.

First movers get integrated AI coworkers across operations. Late adopters scramble to catch up.

What This Means

If you're enterprise, this is OpenAI betting you want AI coworkers, not AI tools.

If you're building AI apps, Frontier opens distribution through enterprise customers if you integrate.

If you're competing with OpenAI, this is them staking claim to enterprise infrastructure layer.

The companies that succeed with Frontier won't just use better AI. They'll have AI integrated into how work actually gets done.

Over to You...

Does Frontier connecting your CRM, data warehouse, and internal apps sound useful or like a nightmare to secure?

Let me know what worries you most.

To connected AI systems,

Jeff J. Hunter 
Founder, AI Persona Method | TheTip.ai

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