Microsoft’s CoPilot now allows you to generate audio overviews of documents on the fly, all within your Microsoft account – great for those occasions where it’s more practical (or more preferable) to listen and learn rather than read and learn.

[Note – To Watch This Video without glitches/interruptions, It may be best to download it first]

Worried that a call from your bank might be a scam? Hang up and call 159, the UK-wide number that connects you safely and directly to your bank, without needing to look up phone numbers or risk calling a fraudster.

How to:

– Dial 159 from your mobile or landline.

– When prompted, say the name of your bank.

– You’ll be transferred to your bank’s official number (no searching required).

What it’s for:

If you ever get a call from someone claiming to be your bank and they ask for personal or financial info, end the call and dial 159. It’s the simplest way to check if it’s real and speak to the real fraud team if it isn’t.

Pro-Tip: Use 159 even if the call seems genuine. Scammers often spoof official numbers, but 159 always connects you to the real bank, safely.

OpenAI has unveiled a research preview of Codex, a cloud-based AI coding agent designed to act as a virtual teammate for software developers.

OpenAI’s Latest Bet on the Future of Coding

OpenAI says Codex is its most advanced AI-powered software engineering agent to date. Codex has been designed to integrate directly into ChatGPT in order to assist with software development tasks ranging from writing features to fixing bugs. Available to Pro, Team, and Enterprise subscribers, and with support for Plus and Edu users expected in the near future.

AI Powered Tools Market

It’s worth noting here that Codex isn’t just another chatbot extension, but actually operates as a virtual, cloud-based coding assistant that can handle multiple tasks in parallel, provide verifiable output logs, and work with live codebases, all within a secure sandboxed environment. As such, it represents a clear move by OpenAI to secure a larger stake in the fast-expanding market for AI-powered developer tools.

So, What Is Codex, And What It’s For?

Codex is powered by codex-1, a specially trained variant of OpenAI’s o3 model, optimised for software engineering through reinforcement learning on real-world development tasks. OpenAI says this model is designed to produce cleaner, more human-readable code than its predecessors, and it can iteratively run and verify its own output using tests, linters, and other standard developer tools.

Once a user connects Codex to their GitHub repository, the agent loads the relevant files into a cloud sandbox and starts work. Users can assign coding tasks by typing a natural language prompt and clicking “Code”, or ask Codex questions about their codebase with the “Ask” function. Each job runs in an isolated environment, mimicking the structure and configuration of the user’s real-world dev setup.

Codex can:

– Write new features or functions

– Refactor and rename code

– Fix bugs and debug issues

– Answer questions about unfamiliar code

– Draft documentation and pull requests

– Run and verify tests.

Fast

Task completion using Codex typically takes between 1 and 30 minutes depending on complexity, and users can monitor progress and review results in real time. Once a job is done, Codex provides traceable logs of its actions and suggested changes, helping ensure transparency and accountability.

Safety

According to OpenAI Product Lead Alexander Embiricos, “a lot of the safety work from our o3 model carries over to Codex,” including the ability to reliably refuse malicious requests, such as writing malware, and restrict access to external APIs or the wider internet. This means Codex cannot be used to covertly access or manipulate live systems, though it also limits its utility for tasks requiring broader connectivity.

Who’s It For?

Right now, Codex is being rolled out to ChatGPT Pro, Enterprise, and Team subscribers worldwide. OpenAI says “generous access” will be granted initially, but usage will soon be capped by rate limits, with additional credits available for purchase. Plus and Edu users are next in line.

Tested Last Month

This preview follows months of behind-the-scenes work with early access testers. For example, companies such as Cisco, Temporal, Superhuman, and autonomous driving firm Kodiak have been helping OpenAI refine Codex in real-world settings. The use cases vary, but recurring themes include:

– Speeding up test coverage

– Automating background development tasks

– Enabling non-engineers to contribute lightweight code

– Improving developer focus and reducing context switching.

How Are The Testers Using It?

To give an idea of its real-world applications in some of these big-name tester companies, at Superhuman, Codex now helps product managers draft minor code changes without interrupting engineering teams. Also, at Kodiak (a company developing autonomous driving technology), it’s used to enhance test coverage and refactor key components in their autonomous driving stack. Also, at Temporal, which builds workflow tools for distributed applications, it supports debugging and iterative feature development.

A Follow-Up to Codex CLI

This latest launch builds on the release of Codex CLI last month, a lightweight, open-source command-line tool that lets developers interact with AI agents directly from their terminals. Codex CLI now defaults to codex-mini-latest, a variant of the o4-mini model optimised for low-latency editing and Q&A.

To streamline access, OpenAI has simplified authentication, i.e. users can now sign in via their ChatGPT accounts and instantly access API credits ($5 for Plus users, $50 for Pro) for a limited time. Pricing for codex-mini-latest is $1.50 per million input tokens and $6 per million output tokens, with a 75 per cent discount via prompt caching.

Broader Ambition

These updates appear to point to a broader vision, whereby OpenAI wants Codex to be more than just a helpful assistant, i.e. it wants Codex to function more like a trusted teammate. As Josh Tobin, OpenAI’s Agents Research Lead says – the goal is for Codex to eventually complete tasks autonomously that “take human engineers hours or even days”.

Riding the AI Coding Boom

This preview version is clearly a high-profile launch that OpenAI hopes will position it against growing rivals in the AI coding space, including Google, Microsoft, Anthropic, and a host of rapidly scaling startups. Also, more than that, it provides a glimpse into what the company sees as the future of human-AI collaboration in software engineering.

It should also be noted that the timing of Codex’s release is no accident. AI coding tools, sometimes dubbed “vibe coders”, have exploded in popularity in recent months. For example, both Google and Microsoft claim AI now contributes to around 30 per cent of their internal code output. Startups like Cursor have reached $300 million in annualised revenue and are being valued as high as $9 billion.

Meanwhile, OpenAI itself has reportedly just finalised a $3 billion deal to acquire Windsurf, the developer behind another major AI coding tool. Taken together, these moves appear to show the company is serious about expanding beyond its flagship chatbot and into the broader ecosystem of developer tools, including video generation (via Sora), research agents, and web automation.

Codex could, therefore, be a big part of that strategy. As AI capabilities advance, OpenAI seems to be envisioning a future where developers assign well-scoped tasks to multiple AI agents in parallel, review their work asynchronously, and move faster across every stage of the development lifecycle.

Challenges, Criticisms, and What Comes Next

Despite the buzz, Codex (like other AI coding agents) isn’t without its flaws. For example, a recent Microsoft study showed that even top-tier models such as Claude 3.7 Sonnet and o3-mini struggled to reliably debug software in complex environments. Codex’s own documentation notes that users must still manually review agent-generated code before integration or deployment.

Some developers have also expressed concern over workflow disruption. For example, delegating tasks to a remote agent adds latency compared to interactive editing, and current limitations, like the lack of image inputs for frontend work or the inability to mid-course correct an agent, may frustrate more advanced users.

There’s also the question of safety. While Codex runs in a secure, air-gapped environment and is trained to refuse malicious instructions, OpenAI acknowledges that balancing security with legitimate use cases (e.g. kernel-level programming) remains a work in progress.

Looking ahead, OpenAI says future versions of Codex will include more interactive features, deeper integration with developer tools (including CI systems and issue trackers), and even proactive collaboration capabilities, allowing agents to check in during a task and adapt based on new feedback. Also, if this research preview gains traction, it may change how businesses, from startups to enterprises, approach software development altogether.

What Does This Mean For Your Business?

Rather than offering a single-use tool or a generic assistant, OpenAI is positioning Codex as a foundational part of the software engineer’s toolkit, i.e. a collaborator that can work independently on defined tasks while staying closely aligned with human expectations and workflows. That positioning reflects OpenAI’s wider ambition to normalise multi-agent workflows and move towards asynchronous, AI-assisted development at scale.

For developers, especially those in high-pressure or fast-moving teams, Codex could help relieve the burden of repetitive or time-consuming tasks (refactoring code, writing tests, or updating documentation) freeing up more time for problem solving and creative development. At the same time, its ability to surface context, suggest improvements, and operate in secure containers could make it a valuable tool for navigating legacy codebases or tackling long-standing bugs. It may not be perfect, and as the documentation itself makes clear, human review is still essential, but the potential for improved focus and faster delivery could be really significant.

Businesses in particular may find this especially useful. For example, with ongoing skills shortages in the tech sector and continued demand for digital transformation, tools like Codex could help firms deliver projects faster without always needing to expand headcount. Small to medium-sized development teams, or organisations experimenting with agile methods, could see real benefits from delegating well-scoped tasks to Codex agents, either to accelerate delivery or free up senior engineers for more strategic work.

That said, the impact won’t be uniform. The very structure of Codex, i.e. running in isolated environments, without full real-time interactivity, means it will likely feel more useful for certain kinds of backend or infrastructure work than for frontend or UI-heavy tasks. Also, while Codex shows promising alignment with coding conventions and project practices, it’s still early days. Safety limitations, execution speed, and the need for well-prepared environments may restrict broader uptake until future iterations smooth out those rough edges.

For OpenAI, however, Codex is far more than a productivity tool. It’s a strategic move that places the company in direct competition with Microsoft’s GitHub Copilot, Google’s Gemini Code Assist, and Anthropic’s Claude Code. But unlike some of those offerings, Codex is being pitched not just as an assistant but as a long-term platform for agentic coding, one that could underpin an entire ecosystem of developer interactions, APIs, integrations, and workflows.

If early results hold up, Codex may well represent the next step in how code gets written, i.e. not just faster, but differently. By giving developers the tools to delegate, collaborate, and iterate with AI in the loop, OpenAI is betting on a future where productivity and creativity are amplified by intelligent software agents. And that’s a future which many UK businesses, whether they’re building the next app or maintaining critical infrastructure, may soon be part of.

The AI giant is reportedly backing a 5-gigawatt data centre in Abu Dhabi, a facility so vast, it would dwarf Monaco and could reshape global AI infrastructure.

A Bold Expansion Into the Gulf

OpenAI, the company behind ChatGPT, is reportedly helping to develop one of the largest AI data centre campuses on the planet, a 10-square-mile megaproject in Abu Dhabi that could eventually outsize the entire nation of Monaco.

The plans (first reported by Bloomberg) describe a 5-gigawatt facility that would draw as much power as five nuclear reactors and become a key node in OpenAI’s growing Stargate infrastructure programme. The UAE site is being built in partnership with G42, a powerful Abu Dhabi-based tech group chaired by the country’s national security advisor, Sheikh Tahnoon bin Zayed Al Nahyan.

Sources familiar with the project say OpenAI would act as one of the primary anchor tenants, though final details are still being worked out. If confirmed, it would mark OpenAI’s largest international infrastructure commitment to date, and one that dramatically raises the stakes in the global race for AI compute power.

Why Abu Dhabi?

For OpenAI, the UAE offers more than just open desert and deep pockets. The region has become a key strategic ally in the US-led effort to expand AI capacity without ceding ground to China.

Abu Dhabi, in particular, has poured billions into tech development through sovereign funds and national champions like G42 and MGX. In return, it has sought deeper technological integration with major US firms, a goal reinforced during President Trump’s recent Middle East visit, where AI cooperation featured prominently on the agenda.

In fact, this new data centre forms part of a wider bilateral framework signed in May between the US and UAE to accelerate AI deployment across the Gulf. The accord could include the sale of over a million high-end Nvidia chips to the UAE, a move intended to counter Beijing’s influence in the region.

OpenAI CEO Sam Altman has long praised the UAE’s ambition. For example, speaking in Abu Dhabi last year, he said the country “has been talking about AI since before it was cool.” His company’s relationship with G42 dates back to 2023, when the two announced a regional partnership to promote AI adoption across the Middle East.

The Global AI Infrastructure Play

The Abu Dhabi build looks like being the most ambitious element yet in OpenAI’s “Stargate” initiative, i.e. a joint venture with SoftBank and Oracle aimed at rolling out hyperscale AI infrastructure around the globe. The programme, unveiled in January alongside former President Trump, is expected to channel up to $500 billion into global projects over the next four years.

OpenAI’s first Stargate campus is already under construction in Abilene, Texas. That site is expected to reach 1.2 gigawatts, making the planned Abu Dhabi facility more than four times larger! For context, even Microsoft’s largest data centres currently consume less than 1 gigawatt.

It’s been reported that each site will serve as a supercharged AI hub, equipped with high-density computing clusters and the latest generation of Nvidia and AMD chips. These are designed to handle the massive workloads required for training and deploying next-gen language models, vision systems, and multimodal tools.

According to OpenAI, demand for compute is growing faster than chipmakers can supply. For example, speaking earlier this year, Altman warned that “AI progress will soon be bottlenecked not by algorithmic innovation, but by energy and silicon.” It seems, therefore, that Stargate is OpenAI’s attempt to remove that bottleneck.

Power, Partnerships, and Politics

The scale of the Abu Dhabi site is breathtaking. For example, at full capacity, it would:

– Span over 10 square miles, which is larger than many cities and territories, including Monaco (0.78 square miles).

– Consume 5 gigawatts of power, which is equal to around 5 large nuclear plants or roughly the output of the UK’s Hinkley Point C when complete.

– House an ecosystem of tenants such as OpenAI, Oracle, and potentially others, although exact names have not yet been disclosed.

Oracle, which has been expanding its cloud footprint aggressively to support AI workloads, is reportedly involved in developing the first phase of the campus. Microsoft, OpenAI’s biggest backer, is also entangled via its recent $1.5 billion investment in G42. Microsoft President Brad Smith has since joined the G42 board.

Complex Politics

However, the politics behind these partnerships are complex. For example, G42’s historical ties to Chinese firms, including Huawei and the Beijing Genomics Institute, have caused alarm in Washington. In 2023, US lawmakers warned that such links could enable Chinese access to sensitive American tech via the back door.

Under pressure, G42 has since claimed to have exited all China-related investments and operations. For example, as CEO Peng Xiao said (to Bloomberg) in January: “All of our China investments that were previously made are already divested. Because of that, we have no need anymore for any physical China presence.”

That change appears to have helped pave the way for closer US-UAE collaboration. That said, it seems that not everyone in Washington is convinced the threat has vanished. For example, some Trump administration officials are said to be uneasy about the symbolic and strategic risks of moving advanced AI infrastructure offshore, particularly to a region still watched closely by Chinese and Russian intelligence services.

Changing The AI Landscape?

If built as planned, the Abu Dhabi super-campus would not only change the geography of AI infrastructure, but could reshape how companies access and deploy AI globally.

For OpenAI’s users, especially enterprise clients, the move signals two big trends:

1. More global redundancy and resilience. Spreading infrastructure across continents could make OpenAI services more stable, scalable, and compliant with local regulations, including data residency requirements.

2. Faster innovation cycles. With massive compute on tap, OpenAI can continue training ever-larger models, rolling out more powerful tools for business, research, and defence applications.

At the same time, the project highlights the deepening alliances between Big Tech and geopolitical power blocs. As AI becomes a strategic asset akin to oil or semiconductors, access to compute may increasingly shape who leads (and who lags) in the next digital revolution.

A New Benchmark

For OpenAI’s rivals like Google DeepMind, Anthropic, and Meta, the Abu Dhabi development looks like setting a new benchmark. Few others have announced anything on this scale. It also raises questions about whether public cloud infrastructure alone will be sufficient to keep pace, or if more firms will start investing in their own AI megastructures.

Environmental and Other Concerns

Despite the hype around the scale and the promise of the project, it also raises tough questions about energy use, environmental impact, export controls, and the ethics of building frontier AI infrastructure in politically sensitive regions. These tensions are unlikely to go away anytime soon.

What Does This Mean For Your Business?

OpenAI’s reported potential leap into Abu Dhabi is more than just a headline-grabbing land grab or another tech tie-up. In fact, it appears to mark a pretty decisive moment in the evolution of AI infrastructure, i.e. where geography, politics, and compute capacity intersect on a global stage. If the deal goes ahead as anticipated, the Middle East may soon host the world’s largest AI campus, symbolising not just technical ambition but also a fundamental shift in where the power behind AI is physically rooted.

For OpenAI, the project signals a pragmatic move to secure the raw energy and silicon resources needed to train future generations of frontier models. The scale of the proposed facility underlines just how central compute has become to AI’s progress, and just how willing firms are to chase that capacity beyond their traditional home markets. Yet that ambition comes at a cost. The growing proximity between powerful AI companies and state-linked partners in geopolitically complex regions raises real questions about governance, transparency, and the safe stewardship of cutting-edge technologies.

UK businesses watching this from afar may be in two minds about its benefits. For example, on the one hand, expanded infrastructure could eventually translate into more stable, powerful AI services (and potentially lower costs) as scale economies kick in. For sectors already adopting generative AI at pace, such as finance, marketing, logistics, and law, that’s a tantalising prospect. However, it also reinforces the extent to which global supply chains, regulatory alignments, and geopolitical tensions now play an invisible but important role in the tools UK firms depend on.

Likewise, for policymakers, the Abu Dhabi campus could serve as a reminder of how fast the AI ecosystem is becoming a transnational infrastructure issue, one that affects everything from energy use and international trade to national security and data protection. The decisions being made in Abu Dhabi, San Francisco, or Washington are no longer abstract for UK stakeholders, but they shape the very foundations of how AI is accessed and governed globally.

In the end, the success or failure of this move may depend as much on diplomacy and ethics as on architecture and engineering. Although the vision is immense, so too are the risks. Whether this data centre becomes a beacon of innovation or a lightning rod for criticism will depend on how carefully all those involved, i.e. OpenAI, G42, Oracle, and the governments behind them, navigate the road ahead.

Two startups on opposite sides of the Atlantic have just unveiled breakthrough prototypes that could bring flying cars and hypersonic jets into everyday travel.

Hypersonic Air Travel and Flying Cars

Venus Aerospace has just tested a rocket engine it believes could make hypersonic passenger flights a reality, while Klein Vision has unveiled the production-ready version of the world’s first certified flying car.

Venus Aerospace Eyes Hypersonic Jet Travel

Houston-based Venus Aerospace made headlines last week with the first successful test flight of its Rotating Detonation Rocket Engine (RDRE), a propulsion system long theorised by engineers but unproven in flight – until now. The test, conducted at Spaceport America in New Mexico, marks a milestone in the company’s effort to develop Stargazer, a Mach 9-capable hypersonic aircraft that could one day fly from London to New York in under an hour.

The engine, described by Venus co-founder and CEO Sarah “Sassie” Duggleby as “the holy grail” of propulsion, works differently to traditional jet or rocket engines. Instead of burning fuel in a steady stream, the RDRE generates a series of controlled shockwave detonations that spiral around a circular chamber at supersonic speeds. This compact design produces more power, uses 20 per cent less fuel, and crucially, has no moving parts, thereby making it cheaper to build, operate, and maintain.

“We’ve proven that this technology works—not just in simulations or the lab, but in the air,” said Duggleby, who co-founded the company with her husband Andrew in 2020.

The recent test flight launched a small rocket to 4,400 feet, reaching 383 mph in just seven seconds, before descending safely by parachute. While that’s only about half the speed of sound, the company insists the trial was all about demonstrating scalability and real-world performance, not speed.

What Makes RDRE So Different?

Venus says the RDRE has the potential to revolutionise aerospace by enabling ultra-fast, cost-effective hypersonic travel across defence, commercial aviation, and space launch sectors. Traditional systems often rely on complex multi-engine configurations to operate across different speed regimes. Venus’s breakthrough is a single-engine solution that handles take-off, acceleration, and sustained hypersonic cruise.

In practical terms, the RDRE could, for example:

– Enable Mach 9 flight speeds (up to 6,900 mph)

– Carry passengers from San Francisco to Tokyo in only two hours!

– Reduce launch costs for satellites and cargo

– Deliver military-grade speed and agility in compact vehicles.

Funding and Support

With £66 million ($84m) in venture funding and support from NASA and the US Department of Defense, Venus is pushing forward with plans to flight-test a 20-foot drone at Mach 5 later this year. This will be followed by the development of Stargazer, a 150-foot-long, 150,000-lb aircraft designed to cruise at 170,000 feet, which is close enough to see the blackness of space and the curvature of Earth.

As Andrew Duggleby, the company’s CTO says: “This is just the beginning of what can be achieved with Venus propulsion technology”.

Challenges

However, despite the ambition and the confidence, it should be noted that there are some considerable challenges ahead. For example, engineers must solve the problem of extreme heat in the detonation chamber. This is what Sassie Duggleby likens to “lighting a fire in a wax fireplace without melting the wax.” The firm is also still years away from a full-scale passenger aircraft. This means that commercial readiness isn’t likely until the early 2030s.

Klein Vision Unveils Its AirCar 2 Flying Car

Meanwhile in Europe, Slovakia’s Klein Vision has taken a different route to next-gen travel. At this year’s Living Legends of Aviation Gala Dinner in Beverly Hills, the company revealed the production-ready prototype of the AirCar 2, a sleek vehicle that can transform from a car to an aircraft in just 80 seconds.

Unlike Venus, Klein Vision’s breakthrough is grounded (literally) in existing certification. The original AirCar, first flown in 2021, was awarded its Certificate of Airworthiness in 2022 after completing 170 flight hours and more than 500 takeoffs and landings.

“The AirCar fulfils a lifelong dream to bring the freedom of flight into the hands of everyday people,” said founder and designer Stefan Klein, who received the gala’s Special Recognition Award for Engineering Excellence.

The AirCar 2 is a major upgrade:

– 280-horsepower engine (replacing the previous 1.6-litre BMW engine)

– Cruising speed up to 250 km/h in flight

– 1,000 km range

– Full monocoque (single shell) body for improved safety and strength

– Compact enough to park in a standard garage.

Klein Vision claims the AirCar 2 can reach 200 km/h on the road, and take off from a conventional airport runway before cruising to its destination and driving off again, which means there’s no need for an entirely new transport infrastructure. A button in the cockpit unfolds the wings and tail, transforming the vehicle from road mode to air mode in less than 90 seconds.

A Car. A Plane. A Market Disruptor?

The company, which has been bootstrapped from the start, is now gearing up for production. According to co-founder Anton Zajac, the first models will retail for between $800,000 and $1 million starting in early 2026, with the ability to produce 100 units per year once certification is complete. It’s understood that pre-orders are already in progress.

Klein Vision’s ambitions are underpinned by bold market predictions. With global air mobility forecast to reach $162 billion by 2034, the company believes its vehicle has a first-mover advantage.

“We’re not just witnessing the future of transportation—we’re engineering it,” said Zajac.

Scepticism

However, some commentators are (understandably) sceptical about Klein Vision’s claims. For example, the flying car market has been promised for decades, and critics often point to limitations in infrastructure, regulation, cost, and public adoption. There’s also the challenge of power. While the current model runs on petrol, Klein Vision admits they plan to go electric “as soon as battery energy density allows.”

Also, with just seven people on staff, Klein Vision appears to be unusually lean for such a capital-intensive industry. The company spent $5 million developing the first AirCar, most of it funded by Zajac himself, though it is now “open to external investment.”

Different Paths, Same Sky

What makes this moment significant is not just the individual accomplishments of Venus Aerospace and Klein Vision, but the fact that two very different approaches (i.e. rocket-driven hypersonic flight and road-to-air transformation) are simultaneously reaching new levels of feasibility.

For example, one is reimagining how fast we can travel, while the other is changing how flexibly we move between ground and sky.

Although each faces enormous technical, regulatory, and financial obstacles, both appear to be making some credible progress, backed by data and test flights. It seems there’s now a growing sense that the next leap in mobility may come not from giant aerospace primes, but from agile, focused startups willing to bet on bold ideas and reinvent the rules.

What Does This Mean For Your Business?

These two announcements feel like a genuine turning point in aviation’s long evolution from commercial airliners to something altogether more ambitious, and more personal. Whether it’s Venus Aerospace’s promise of New York to Tokyo in under an hour, or Klein Vision’s vision of driving to the airport and flying yourself to your next meeting, both represent a dramatic departure from the limits of traditional air travel. Also, for a sector that hasn’t seen many transformative passenger-facing breakthroughs since Concorde, this sudden surge in innovation feels both overdue and quite exciting.

For UK businesses, hypersonic travel, if it becomes commercially viable, could create a new level of global agility for finance, tech, and trade sectors, shrinking long-haul logistics and giving British firms the ability to meet clients or partners halfway across the world in the space of a lunch break. Also, a certified flying car like the AirCar 2 could, in time, reshape regional mobility by unlocking point-to-point travel for executives, engineers, or consultants who currently rely on slower rail or road connections. The early costs may be high, but as production scales and competition grows, accessibility may follow.

Of course, there are still some big questions, especially around safety, certification, regulation, and infrastructure. In both cases, it’s not yet clear how existing aviation authorities will adapt to technologies that blur the lines between car and aircraft, or jet and rocket. Also, public acceptance and use will also hinge on reliability, insurance frameworks, pilot licensing, and in the case of hypersonic flight, whether everyday passengers can truly stomach the physics involved.

Then there’s the competitive landscape to consider. For example, as Venus pushes to commercialise RDRE-powered jets, it enters a growing field of rivals including Hermeus, Sierra Space, and Virgin Galactic, all with overlapping ambitions. Similarly, Klein Vision must prove it can scale manufacturing, meet regulatory expectations, and fend off future entrants with better-funded teams or deeper aviation experience.

However, even with these challenges, the pace and credibility of recent progress seems to suggest that this may no longer be a question of if, but when. The fact that two very different technologies, i.e., one focused on blistering speed, the other on personal freedom, are both edging closer to commercial reality shows that the sky is no longer the limit. The travel industry may be on the cusp of a transformation that doesn’t just shrink time and distance, but redefines how we connect with the world. And that’s a future well worth watching.