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GPT-5 Is Less About Revolution, More About Refinement
This article explores OpenAI’s development of GPT-5, focusing on improving user experience by unifying AI tools and reducing the need for manual model switching. It includes insights from VP of Research Jerry Tworek on token growth, benchmarks, and the evolving role of humans in the AI era.
OpenAI’s next model isn’t chasing headlines—it’s building a smoother, smarter user experience with fewer interruptions the launch of GPT-5 unified tools.
TL;DR — What You Need To Know
- GPT-5 aims to unify OpenAI’s tools, reducing the need for switching between models
- The Operator screen agent is due for an upgrade, with a push towards becoming a desktop-level assistant
- Token usage continues to rise, suggesting growing AI utility and infrastructure demand
- Benchmarks are losing their relevance, with real-world use cases taking centre stage
- OpenAI believes AI won’t replace humans but may reshape human labour roles
A more cohesive AI experience, not a leap forward
While GPT-4 dazzled with its capabilities, GPT-5 appears to be a quieter force, according to OpenAI’s VP of Research, Jerry Tworek. Speaking during a recent Reddit Q&A with the Codex team, Tworek described the new model as a unifier—not a disruptor.
“We just want to make everything our models can currently do better and with less model switching,” Tworek said. That means streamlining the experience so users aren’t constantly toggling between tools like Codex, Operator, Deep Research and memory functions.
For OpenAI, the future lies in integration over invention. Instead of introducing radically new features, GPT-5 focuses on making the existing stack work together more fluidly. This approach marks a clear departure from the hype-heavy rollouts often associated with new model versions.
Operator: from browser control to desktop companion
One of the most interesting pieces in this puzzle is Operator, OpenAI’s still-experimental screen agent. Currently capable of basic browser navigation, it’s more novelty than necessity. But that may soon change.
An update to Operator is expected “soon,” with Tworek hinting it could evolve into a “very useful tool.” The goal? A kind of AI assistant that handles your screen like a power user, automating online tasks without constantly needing user prompts.
The update is part of a broader push to make AI tools feel like one system, rather than a toolkit you have to learn to assemble. That shift could make screen agents like Operator truly indispensable—especially in Asia, where mobile-first behaviour and app fragmentation often define the user journey.
Integration efforts hit reality checks
Originally, OpenAI promised that GPT-5 would merge the GPT and “o” model series into a single omnipotent system. But as with many grand plans in AI, the reality was less elegant.
In April, CEO Sam Altman admitted the challenge: full integration proved more complex than expected. Instead, the company released o3 and o4-mini as standalone models, tailored for reasoning.
Tworek confirmed that the vision of reduced model switching is still alive—but not at the cost of model performance. Users will still see multiple models under the hood; they just might not have to choose between them manually.
Tokens and the long road ahead
If you think the token boom is a temporary blip, think again. Tworek addressed a user scenario where AI assistants might one day process 100 tokens per second continuously, reading sensors, analysing messages, and more.
That, he says, is entirely plausible. “Even if models stopped improving,” Tworek noted, “they could still deliver a lot of value just by scaling up.”
This perspective reflects a strategic bet on infrastructure. OpenAI isn’t just building smarter models; it’s betting on broader usage. Token usage becomes a proxy for economic value—and infrastructure expansion the necessary backbone.
Goodbye benchmarks, hello real work
When asked to compare GPT with rivals like Claude or Gemini, Tworek took a deliberately contrarian stance. Benchmarks, he suggested, are increasingly irrelevant.
“They don’t reflect how people actually use these systems,” he explained, noting that many scores are skewed by targeted fine-tuning.
Instead, OpenAI is doubling down on real-world tasks as the truest test of model performance. The company’s ambition? To eliminate model choice altogether. “Our goal is to resolve this decision paralysis by making the best one.”
The human at the helm
Despite AI’s growing power, Tworek offered a thoughtful reminder: some jobs will always need humans. While roles will evolve, the need for oversight won’t go away.
“In my view, there will always be work only for humans to do,” he said. The “last job,” he suggested, might be supervising the machines themselves—a vision less dystopian, more quietly optimistic.
For Asia’s fast-modernising economies, that might be a signal to double down on education, critical thinking, and human-centred design. The jobs of tomorrow may be less about doing, and more about directing.
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