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When Anthropic's CFO revealed that over 90 per cent of the company's code is now written by its own AI, it landed as a milestone.
Tasks that once consumed hours now take 30 minutes. The productivity gains are significant.
But Anthropic is an AI-native company with some of the world's best engineering talent.
For most enterprises, the question isn't whether AI can generate code at that speed. It's whether they can govern what it generates.
Shadow AI: The new shadow IT"Vibe coding", the term for generating code via AI, has moved into the mainstream. By some estimates, almost half of all new global code is now AI-generated. Developer productivity is up. So is debt that nobody fully understands.
Part of what's driving this is necessity. AI is helping close the engineering talent gap. Teams that lack experienced developers are using it to build at the pace the business demands. The problem is that the same shortage that makes AI indispensable also means there aren't enough senior engineers to review AI-generated code.
Research across Fortune 50 enterprises found that AI-assisted developers introduce security vulnerabilities at ten times the rate of their peers. Forty-five per cent of AI-generated code contains OWASP Top 10 vulnerabilities. Independent analyses indicate that technical debt increases by 30–41 per cent following the adoption of AI tools.
Traditional technical debt is at least visible. Engineers who cut corners know they did it. Vibe coding debt is different: developers often don't realize they have incurred it, because the code looks correct – right up until it doesn't.
We used to worry about Shadow IT. The new threat is Shadow AI: code generated at pace without architectural review, security auditing or institutional understanding of what's been built.
Unlike Shadow IT, which was typically contained within a department, Shadow AI compounds across organizational boundaries. In enterprises where systems are still deeply siloed, complex problems span multiple departments and platforms; no single team has a complete picture of what's been generated or what it depends on.
Enterprises have spent decades paying for yesterday's shortcuts. AI risks creating the next generation of legacy systems, only much faster.
Repeating the COBOL mistakeThe market is flooded with tools promising to read millions of lines of COBOL or Java and convert the functionality into a modern language. This is technically impressive, but strategically flawed.
Legacy systems are full of inefficiencies, redundancies and “swivel chair” workarounds baked in years ago to compensate for other systems' limitations. Translating code line-by-line replicates that bad logic in a newer language, now running on cloud infrastructure with a modern interface on top of old code and dated processes.
To get modernization right, organizations should avoid treating it as a technical exercise. Instead, they should step back and ask whether a process is still valid, not just how to replicate it.
True modernization is about reinventing how work gets done, designed around the employee and customer experience rather than the constraints of systems built decades ago. It is a state of consistent change, and it must be driven by the North Star of clear business objectives.
The agility layerProbabilistic AI needs to operate within deterministic boundaries to be safe and useful at enterprise scale. AI that can generate anything is not the same as AI that generates the right thing reliably with full traceability, in a context where every decision might be scrutinized by a regulator.
This is why high-stakes organizations are looking for an agility layer: a governed process platform that imposes structure, ensures auditability and keeps AI outputs within maintainable boundaries. The US Army followed this approach for security with agility to operate with certainty at speed.
Ordering ammunition in disconnected field conditions is mission-critical, with zero tolerance for ungoverned outputs. Similarly, pharmaceutical giant Merck's clinical supply chain, where regulatory scrutiny is intense and errors have patient safety consequences, required a platform that could accelerate delivery without sacrificing auditability.
These are examples of organizations trying to address the hardest part of modernization: discovery. They are using AI to extract specifications from even the most poorly documented legacy applications, converting them into visual plans covering UI, data models and process flows.
They're generating software components rather than custom code to reuse in other applications, accelerating development time and reducing technical debt. AI agents then build against those specs under human supervision, with developers assigning tasks and iterating throughout – at roughly 25 per cent of the time traditional approaches require.
The future is bespoke, not general-purposeThere is a temptation to conclude that general-purpose AI will soon render enterprise platforms obsolete. This is premature and in regulated environments, dangerous. General-purpose models are extraordinary at generating plausible outputs. They are not equipped to ensure those outputs are auditable, compliant or maintainable by teams that did not generate them.
The vibe coding wave is real, and so is the debt it is creating. The organizations that navigate the next decade successfully and avoid falling into the same old legacy traps will not be the ones that generated code the fastest in 2025 and 2026.
They'll be the ones to build governance and process boundaries into how AI was used from the start – so what was built quickly can still be understood, maintained and trusted years later.
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- Forescout’s Vedere Labs found 15 flaws in TP‑Link Omada business networking gear, exploitable for RCE when chained with prior CVEs
- Weak trust shortcuts in zero‑touch provisioning exposed devices to client‑side code execution, hijacking, spoofing, and encrypted comms compromise
- TP‑Link released firmware updates; admins should patch immediately, with 1,800+ Omada controllers exposed online
TP-Link has patched more than a dozen vulnerabilities across multiple business networking products which could have been chained to achieve remote code execution (RCE).
Security researchers at Vedere Labs from Forescout found the flaws and published an in-depth report on the issues, which particularly affect TP-Link Omada, the company’s business networking platform for centrally managing enterprise and small-business network infrastructure.
It includes cloud-managed Wi-Fi access points, routers, switches, gateways, and controllers, all of which can be monitored and configured from a single interface.
Enabling "concrete attacks"These support zero-touch provisioning (ZTP), a mechanism that allows IT managers to deploy and maintain devices without needing to configure each one manually and on site.
However, ZTP has to establish trust between a factory-fresh device, and a controller with no human involved, so TP-Link used different shortcuts: from hard-coded keys and certificates shared across multiple devices, to default credentials, and from guessable serial numbers as “identity”, to weak session-key randomness.
Now, Forescout says 15 vulnerabilities its researchers discovered all allow for different ways of exploiting these shortcuts, meaning a flaw anywhere in the onboarding chain can compromise every device that goes through it. These bugs would need to be combined with two previously disclosed command-injection flaws, though.
“The vulnerabilities fall into four impact categories: client-side code execution, information disclosure, device hijacking and spoofing, and compromise of encrypted communications,” Forescout said. “Combined with two previously disclosed CVEs (CVE-2025-7850 and CVE-2025-7851), these flaws enable concrete attacks that let attackers infiltrate networks through controllers and client devices.”
Out of the 15 discovered flaws, 11 received CVE identifiers, and the rest did not receive a tracking number.
Forescout said there are more than 1,800 Omada controllers accessible from the wider internet. If you are using any of the devices from the platform, you should head over to TP-Link’s download portal and grab the latest firmware for your device model.
- Gigabyte graphics cards are rumored to be set for a big price rise
- It could be a hike of 20% to 40%, and other rumors are also pointing to major price hikes for GPUs more broadly
- This means now is likely a good time to make a purchase, particularly with certain cards which have avoided the worst of the hikes so far
Desktop GPU prices are set to rise if the rumor mill is right – with yet another prediction to that end being aired – and while graphics cards are already costly in some cases, now might be the time to buy certain models, based on a fresh roundup of average pricing.
First off, let's deal with the latest gloom nugget from the grapevine regarding GPU pricing, courtesy of @momomo_us on X (via Wccftech) who picked up a notice from CFD (a Japanese components supplier) warning of substantial price hikes on Gigabyte graphics cards.
The claimed rise (add seasoning, of course) is in the order of 20% to 40%, so at the latter end of that scale, we're looking at prices shooting up by almost a half in some cases. Existing orders from retailers buying boards from CFD may even be cancelled, the notice states.
I perhaps wouldn't put as much stock in this, except that it echoes a rash of recent reports contending that large price hikes are about to happen in the GPU world, which makes it all the more believable.
Only yesterday I reported on the situation in South Korea where RTX 5000 models are rumored to be getting price increases of up to 30%. So again, that's a hefty hike, and it follows other speculation about Nvidia charging its partners more for video RAM (which will push up costs, of course).
This apparent Gigabyte move will affect both Nvidia and AMD graphics cards in Japan, and there have been rumors about Team Red having Radeon price hikes in the pipeline due to more expensive VRAM, too. That only makes sense, as if VRAM is getting more costly for Nvidia, it will be for AMD too. And while some of these reports are based on regional activity, the cost issues will surely apply globally – none of these markets exist in a bubble.
Analysis: I think it's time to buy – especially with certain GPUs(Image credit: Gigabyte)The RAM crisis has a lot to answer for, and it very much looks like graphics card prices are going to be jacked up considerably during the remainder of 2026, with video memory being the primary driver here. Given that, it seems that if you are thinking about a GPU upgrade, now is likely the time to go for it, rather than waiting and being hit by price hikes.
That's especially true if you're considering a 16GB graphics card (as more gamers are these days), as the products with more VRAM are going to get hit the hardest for price rises as memory modules become even more expensive.
If we want a snapshot of the current GPU market as price tags stand, fortunately enough, TechSpot has just furnished us with an extensive (multi-region) pricing roundup as of the end of July which highlights some key points.
Firstly, low-end GPUs are still relatively unscathed, with offerings like the RTX 5050 and RTX 5060 8GB, and the 8GB spin on the 5060 Ti, not having been bumped up by all that much in the RAM crisis thus far. However, as for the 16GB incarnation of the RTX 5060 Ti, that has seen major price bumps, reinforcing that observation on 16GB pain (this card is up over 40% since November 2025 in the US, for example – and shows a 14% rise since April 2026).
In the tier above that, the RTX 5070 is holding at a reasonable price, and even if the sub-MSRP levels of late last year are well and truly gone, it remains a decent buy. (As long as you can stomach 12GB of VRAM at this price bracket, of course – and that's one of the reasons why this GPU hasn't been hit so hard, no doubt).
Above this level, Nvidia GPUs have witnessed some of the nastier price increases, as you've probably noticed.
On the AMD side, matters look more promising, particularly in the case of the Radeon RX 9070 and RX 9070 XT, with TechSpot finding that the 16GB models in the RDNA 4 family haven't suffered as much as Nvidia's GeForce offerings. The price of both these 9070 models has remained steady over the last few months, and in many regions, they're only up 10% or so compared to late 2025. (The 9070 XT is an exception in the US, mind, where it has risen by closing on 20% since last year).
If you're inclined towards one of these Radeon mid-rangers, or Nvidia's RTX 5070, I'd strongly suggest you buy now rather than wait based on what we're hearing from the rumor mill. Lower-priced graphics cards are likely worth grabbing, too, because they may be heading upwards in the pricing stakes before long – although notably the RX 9060 XT with 16GB has already become a good deal more costly, much like its RTX 5060 Ti 16GB rival.
As noted, Nvidia's higher-end graphics cards (RTX 5070 Ti and upwards) have already been hit with alarming price hikes, but they're likely to get even worse. So, this could be a case of keeping your wallet shut and holding out for possibly a lengthy time, as I can't really recommend them even at the current pricing.
The trouble is, we don't know how long the RAM crisis will continue, and some of the guesswork on that front is very bleak indeed – suggesting it might be the rest of this decade effectively. At this point, I'm inclined to believe we're in it for the long haul with PC component pricing woes, which is why I think it's best to buy a GPU now, at least with the mentioned models, assuming you're in a position to do so.