Forget About Frontier Models (For Workflow Automation)

At present there is a hesitancy among companies to begin their AI journey as they believe that a new model with massively increased intelligence is right around the corner And, perhaps, this model will make their work so far redundant.

This hesitancy comes from a fundamental misunderstanding of how reliable AI automation works. And it's a credit to the hype frontier labs have generated in creating an almost "magical" aura around Large Language models.

Let's us demystify AI and show you why this delay is creating strategic risk that will prevent your company meaningfully realising value from AI even if AGI drops next week.

Automation Isn't About Intelligence. It's About Verification.

Let's hypothetically play out the scenario where GPT-6 is 10x as intelligent as GPT-5. It is - from an economical standpoint - AGI.

Pause and ask yourself — what is your company's move when that day arrives?

Are you just going to plug it into your systems and let it get to work? That thought likely provides...a moment of terror to most business owners.

"What if it just offers refunds to customers?"
"It could make promises about times we can't meet."
"It might provide financial advice that puts us at regulatory risk"

Now ask yourself what might make you feel more comfortable?

Clear boundaries where the AI can operate.
The ability to know when it's made a mistake and take control
The ability for it to simply ask for help when it is stuck
An audit trail of all work it has done

Real AI automation requires that you can verify your system both at deployment and in realtime, with mechanisms built in to actively trigger human intervention when the system strays outside of these boundaries.

This requires;

A suite of verifications. We call these "evals".
A method of teaching the AI when they do something wrong.
A system designed to bind these together in a positive feedback loop
Graceful handover to humans in the loop
A team that feel fully in control of the system

Frontier models don't fix these foundational requirements. Even AGI doesn't. The idea that they could is the reason 95% of companies have failed at AI automation so far.

The added noise of frontier models

Most people don't realise how rapidly frontier models change behind the scenes. They are perhaps the most unreliable technical product to ever be adopted at such scale.

Providers are enagaged in what they believe is a race to AGI which leaves no room for backwards compatability

They quietly adjust weights, safety layers, prompting rules, and tokenisation strategies. What works today might fail tomorrow—without warning. We have seen this play out over and over ever since GPT-2.

This leads to:

Broken workflows
Regression in performance
Loss of trust across stakeholders

This is amplified when the foundational verification layer is absent.

Open Source Models Are Already Good Enough

What the sales execs at Big Tech won't tell you is that there is already enough intelligence in today's open-source models to automate the majority of business operations — especially structured workflows like customer service, scheduling and policy lookups.

And unlike frontier models, these models are something you own the full lifecycle of. Nobody is going to quietly adjust the intelligence of the model based on GPU-load, creating a spike in work for your team.

Already we are seeing major companies like AirBnb adopt this approach.

Align these models to;

Clear success criteria
Robust eval coverage
A delivery model that supports version control and iteration

and you have a solution that scales gracefully and affordably.

Now when that 10x intelligence arrives? Easy. Run your evals to verify behaviour. If you're happy plug it ,see your automations improve and deliver more return on your investment.

Go Live Early. Learn Faster. Expand Confidently.

To recap, by starting now you;

Build up a foundational verification layer
Capture real-world edge cases from day one.
Educate your team in AI automation
Build proprietary advantage through your data and evals — not someone else's frontier model roadmap.

This is how you build AI automation that gets smarter over time, not riskier.

This is how you become one of the 5% realising AI value for their business.

At our consulting practice in Perth, Western Australia, we help companies manage this change. We design evaluation systems that fit their unique needs and goals. If you're creating your first AI app or want to improve current ones, we can talk about how systematic AI quality assurance can boost your competitive edge.

Email us at: hello@verticalai.com.au

Visit our website at: https://verticalai.com.au