OpenAI on Thursday released its latest AI model, which it called “the world’s most intelligent”, as the ChatGPT maker aims to retake the lead from arch-rival Anthropic ahead of a planned public listing.

The $852bn start-up said GPT-6 Astra was market-leading in software engineering, science and cyber security — an increasingly critical field following multiple high-profile breaches in recent weeks.

The bullish launch for Astra marks OpenAI’s effort to signal that it believes it has regained the technical lead from Anthropic, which was founded five years ago by a group of senior OpenAI staff.

Greg Brockman, OpenAI’s president, said the new model “represents a generational leap in capability” and that it could be defined as artificial general intelligence — roughly defined as a point at which AI tools surpass human capabilities across a range of cognitive tasks.

“Everyone has a different definition of AGI . . . it’s a grey, fuzzy thing. But I think when we look back people will think it’s about this time and about this model,” Brockman said.

OpenAI has previously framed AGI as a concrete milestone in the development of AI, writing ‘AGI clauses’ into multibillion-dollar investment agreements with Microsoft and Amazon. Brockman on Thursday said AGI now represents “more of a mission concept or a spiritual concept”.

Having led the market since the launch of ChatGPT in late 2022 vaulted AI to wider attention, the lab run by chief executive Sam Altman has been bested by Anthropic this year. Anthropic has touted its dominance to investors, surging to a $965bn valuation ahead of an initial public offering expected to value it at as much as twice that later this year.

Astra will cost as much to use Anthropic’s leading model, the take-up of which has plateaued since it was launched as users turn to cheaper alternatives.

OpenAI said Astra would be more efficient than earlier generations of model. “Price per task is what matters . . . Can you get the thing done at an appropriate price and appropriate speed?” said Brockman.

The model will initially be rolled out to a small group of businesses to allow time for them to address cyber security concerns before becoming widely available “over the coming days”.

The increasing power and independence of leading models — and so-called AI agents that can operate with little human input — have prompted concern, exacerbated by cyber security incidents.

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Recent launches of Anthropic’s most capable models have drawn scrutiny from the US government, which limited the rollout of the Mythos and Fable models over security fears.

OpenAI has also faced criticism after its AI agents broke out of a testing environment, accessed the internet and hacked start-up Hugging Face. The start-up took more than a week to detect the breach.

But both companies are also betting that these increasingly autonomous tools will stoke demand from business customers. OpenAI said Astra excelled at financial modelling, outcompeting humans in the Financial Modeling World Cup, tax preparation and data analysis, as well as “tedious tasks” such as form filling

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* A task estimated at 4 hours → solved with one well specified prompt

* A 20 hour engineering effort → executed in about 3 hours

* A 3 month project → delivered in 1 month

These are clearly best case scenarios. They are not the norm, yet. But they demonstrate what is possible.

We have also seen what happens when things go wrong. Companies, including startups, come to us with broken systems and spaghetti code and architecture caused by weak prompts, unclear requirements, and no verification.

It is important to understand that the efficiency gains we are seeing do not come from the tools alone. They come from a specific combination:

1) Engineers who have spent 20 years building everything from robotics to enterprise-scale technology. You cannot give a perfect instruction to an AI if you do not know what perfect looks like in a production environment.

2) A technical prompt should not be treated as a quick input or question. It is a detailed specification that requires experience and deliberate thinking.

3) Knowing the right combination of tools, workflows, and validation processes.

That said, some (many?) members of our team are dinosaurs in the software engineering world. They bring a ton of experience but are used to tools from 15 years ago and don't like change. We really had to push AI adoption (mostly Cursor and Claude Code) on them. It’s still an ongoing process, and probably will be for a while.

We are a small senior-only team of former startup founders and engineers who act as the technical engine for startups and scale-ups. We skip the junior developers and project managers to focus on high-speed shipping only. What we do:

* For Startups: We act as fractional co-founders, turning napkin ideas into investor-ready products. We’ve helped founders take ideas to $20k MRR in just a few months

* For Scale-ups: We audit and rebuild tech stacks to handle 100x growth.

* Our Background: Our team originated at Stanford. Our track record includes building core infrastructure for high-growth tech startups and global platforms. We’ve delivered 140+ projects over the last 20 years.

Our guarantee: We deliver a working product in under 90 days, or you don't pay.

If you’re a founder who needs a senior strike team to take full ownership of your roadmap, email me at hello@siroc.com

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