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The court's decision means Cook can stay in her position as her challenge to her dismissal plays out in the lower courts.

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In a 6-3 decision, the Supreme Court struck down a 91-year-old precedent that has prevented presidents from removing members of independent agencies meant to be a check on his power.

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Enterprise AI has entered a new operational phase, moving rapidly from experimentation into production systems integrated into customer experiences, workflows, and software delivery pipelines.

However, as organizations operationalize AI, they are also introducing new complexity around infrastructure, governance, debugging, capacity planning, and cost control.

This complexity introduces new operational risks.

AI systems continuously evolve as prompts change, models are updated, agents become more autonomous, and infrastructure dependencies shift over time.

Without end-to-end visibility across the full AI stack, issues related to reliability, latency, output quality, or cost efficiency can gradually slip into production unnoticed: resulting in what many teams refer to as “invisible drift.”

As AI adoption scales, observability is becoming essential for helping engineering teams maintain operational control, reliability, and resilience in rapidly changing environments.

Multi-provider AI brings a new wave of platform engineering challenges

Organizations are increasingly adopting multi-model AI strategies rather than relying on a single provider. Recent research shows that more than 70 per cent of organizations now use three or more models in their production environments. This reflects a broader shift toward diversified model libraries, with teams are selecting models based on specific workload requirements such as latency, reasoning ability, operational risk, and cost efficiency.

This shift is creating a new generation of platform engineering challenges. AI environments now span evolving ecosystems of models, agents, orchestration frameworks, APIs, vector databases and infrastructure layers. As coding agents accelerate development, organizations are generating more code, dependencies, and operational overhead than teams can realistically manage manually.

At the same time, enterprises are accumulating significant LLM technical debt as they rapidly integrate new tools and frameworks. Tool sprawl, fragmented visibility, and constantly evolving AI architectures are making systems harder to govern, troubleshoot, optimize and secure. This makes AI observability essential, providing centralized visibility into model behavior, prompts, latency, hallucinations, token usage, infrastructure performance, and operational bottlenecks across complex multi-model environments.

Scaling AI safely, reliably and at speed requires control

As organizations race to scale their AI initiatives, operational failures are becoming more visible. Recent analysis shows that two per cent of all LLM calls returned errors, with rate limit issues accounting for almost a third of these (equating to approximately 8.4 million rate limit errors in total). This highlights the operational strain on systems as AI adoption accelerates.

At the same time, pressure to remain competitive is pushing organizations to move projects into production before operational controls have fully matured. Scaling too quickly introduces significant reliability, resilience, and governance risks. Real-time observability across the AI stack gives engineering teams the visibility needed to move quickly while maintaining high performance standards.

AI agents are adding yet another layer of complexity. Adoption of agent frameworks has doubled in the past year, leading to increased “agent sprawl”. These agents autonomously interact with multiple tools, systems, APIs, and datasets, making it harder for organizations to monitor behavior, diagnose faults, manage security risks, and maintain governance controls without deeper telemetry.

To manage this complexity, organizations need enterprise-grade observability that delivers end-to-end visibility across the AI stack (from development through to production). This includes visibility into prompts, model interactions, inference pipelines, infrastructure performance, latency, failures, and downstream dependencies. With comprehensive telemetry in place, teams can accelerate AI innovation while improving reliability, security, and operational controls at scale.

Four ways observability helps organizations scale AI more reliably

Organizations moving AI into production are increasingly treating observability as a foundational operational discipline, rather than simply a monitoring capability. Four practices are becoming particularly important as enterprises scale multi-model AI environments:

1.Managing multi-model environments more effectively

Teams are implementing gateways, routing layers, and evaluation frameworks that enhance their ability to select, assess, and manage multi-model environments effectively. These systems enable organizations to compare model behaviors, evaluate outputs, optimize workload placement, and enforce governance policies across various providers. AI observability provides the real-time data needed to support these decisions.

2.Reducing operational overhead and tech debt

Centralized visibility across prompts, models, inference pipelines, and infrastructure helps teams manage increasingly distributed environments. Observability reduces operational overhead and limits the accumulation of LLM technical debt as tools and frameworks evolve.

3.Improving agent reliability and preventing infrastructure failures

AI observability improves agent reliability and helps organizations eliminate failures caused by capacity constraints and infrastructure bottlenecks. Real-time monitoring of GPU utilization, throughput, latency, request failures, and workload behavior enables engineering teams to identify emerging scaling limitations before they impact production systems or user experiences.

4.Diagnosing faults and understanding agent behavior

Detailed tracing across prompts, workflows, APIs, orchestration layers, and infrastructure dependencies provides the operational context needed to investigate anomalies and identify root causes. This is critical for understanding how AI agents behave in real-world production environments.

Moving to a state of production-ready AI

Enterprise AI is now entering its operational era. As organizations move from experimentation to production, observability becomes the backbone for managing the growing complexity of multi-model architectures, autonomous agents, and distributed AI systems.

Without deep visibility into how these systems operate in production, organizations risk increasing operational failures, accumulating technical debt, and allowing invisible drift to undermine performance, reliability and governance over time.

AI observability provides the control needed to scale AI safely and effectively. Visibility across models, prompts, infrastructure, agents, and workflows helps teams build more governable, resilient and cost-effective AI systems.

Success in the next phase of AI adoption will depend on transforming experimental AI systems into disciplined production platforms that can be continuously evaluated, improved and trusted at scale.

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Searching for secure cloud storage often comes with navigating monthly subscriptions and trying to calculate exactly how much storage you need, often with upgrades later down the line that raise your monthly costs.

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pCloud offers real time synchronization and backup across every mode of access. You can also set select files and folders to be automatically backed up, ensuring you have access from everywhere on any device.

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Invite both pCloud and non-pCloud collaborators to view and edit files in real time using secure shared links, folder invitations, and file requests.

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• Take a look at our full guide to the best cloud storage

Constant Contact Lead Gen & CRM’s (formerly SharpSpring) is a powerful yet user-friendly marketing automation and CRM platform that caters to the needs of small to mid-sized businesses. As an all-in-one solution, it offers a solid set of features, including lead management, email marketing, social media management, and a built-in CRM at no extra cost.

Lead Gen & CRM’s key strength lies in its intuitive interface, which makes it easy to create complex automation workflows without requiring extensive technical knowledge. The visual campaign builder allows marketers to design multi-step campaigns with ease, while the opportunity management and task tracking features enable sales teams to stay on top of their pipeline.

However, Lead Gen & CRM is not without its drawbacks. Some users have reported occasional glitches and slower performance compared to other platforms. Additionally, while the feature set is comprehensive, it may not be as advanced as some enterprise-level solutions. Despite these minor shortcomings, Lead Gen & CRM remains a solid choice for businesses seeking an integrated marketing automation tool with CRM features.

Lead Gen & CRM core capabilties

Constant Contact Lead Gen & CRM marks a massive structural evolution for the software platform formerly known as SharpSpring. Following its acquisition by email marketing pioneer Constant Contact, the software dropped the legacy SharpSpring moniker to align completely with its parent company’s massive digital outreach ecosystem.

Lead Gen & CRM packs a powerful punch when it comes to its core CRM capabilities. At the heart of its CRM functionality is robust lead generation and management. The platform allows you to track, score, qualify, and convert leads, giving you a 360-degree view of your prospects' journey.

A standout feature is Lead Gen & CRM's ability to de-anonymize website visitors and track their behavior, enabling deep personalization. You can tailor experiences to each lead contextually based on their interests and actions.

The CRM also excels at email management, with tools to build custom emails and automate personalized outreach at scale. You can set up targeted campaigns triggered by specific lead behaviors or statuses.

For lead capture, Lead Gen & CRM provides flexible form and landing page builders. These allow you to craft custom assets that feed prospects' information directly into the CRM. Progressive profiling helps gradually build out lead profiles over time.

I'm impressed by how Lead Gen & CRM has seamlessly integrated core CRM functionality with its marketing automation capabilities. Having both in a single platform streamlines operations and aligns sales and marketing, which is great for tightly-knit startups.

However, some long-term users indicate that it may lack a few of the more advanced features you'd find in a standalone system. For many small or midsize companies, though, Lead Gen & CRM's CRM will be more than sufficient for their use case.

Overall, Lead Gen & CRM delivers on the CRM essentials — lead management, email outreach, and custom form capture — while surrounding them with strong marketing automation. This combination makes it a compelling central revenue platform for SMBs.

How easy is Lead Gen & CRM to use?

Lead Gen & CRM's user interface aims to simplify navigation and reduce the learning curve for new users. Key customization options allow the platform to adapt to various business needs and use cases.

I found Lead Gen & CRM's visual campaign builder to be very intuitive once you get oriented. However, for non-marketers or those new to marketing automation, the workflow may be a bit overwhelming at first. Lead Gen & CRM does provide an excellent knowledge base to help users get up to speed, though.

Lead Gen & CRM's onboarding is one of its standout features. You get paired with an Onboarding Specialist who guides you through training over your first 60 days. The process starts with goal-setting and expectation-setting calls. Then you move into the thick of it with platform setup, data and system integration, as well as instance configuration.

After that, Lead Gen & CRM offers a menu of 30-60 minute training sessions on key platform capabilities that can be mixed, matched, and ordered to your needs. Topics include the CRM, marketing campaigns, landing pages, forms, automation, analytics, and more.

So while the workflow UI might not be immediately intuitive for all, Lead Gen & CRM compensates with strong training and onboarding. With guidance from the onboarding team, most users seem to gain proficiency within the first couple of months.

A potential downside is the flip side of customization; it may take more time to configure the platform to your needs than a more standardized tool. But if you want that flexibility and are willing to invest some upfront effort, it pays off in the long run.

Overall, I give Lead Gen & CRM high marks for its user interface, training resources, and customization options to fit diverse business cases. With a bit of time to orient and personalized onboarding, new users can harness its power.

Lead Gen & CRM integrations

(Image credit: SharpSpring)

Lead Gen & CRM offers a robust set of integration options to connect it with other business applications and extend its functionality. The CRM integrates with a wide variety of popular apps out of the box through its App Marketplace. Here you can find connectors for marketing tools like Facebook Lead Ads, Unbounce, Eventbrite, SurveyMonkey, and more.

I found the integration with Unbounce particularly useful, as it allows marketing leads captured on Unbounce landing pages to automatically sync into Lead Gen & CRM for follow-up. The Facebook Lead Ads integration is also handy for pulling in leads generated from social media campaigns.

For more custom integrations, Lead Gen & CRM supports popular automation platforms Zapier and Make (formerly Integromat). With these iPaaS (integration platform as a service) tools, you can connect Lead Gen & CRM to over 1000 other apps without needing to write any code. I was able to use Zapier to set up an integration that sends new leads from my website's contact form directly into Lead Gen & CRM, then creates tasks for a hypothetical sales team to reach out to.

Lead Gen & CRM also provides a full-featured REST API that allows developers to integrate the CRM with any other system. The API documentation is comprehensive, and the platform uses standard OAuth 2.0 authentication. Advanced users suggest that the API is relatively straightforward to work with when building a custom integration.

One thing I would like to see is more granular user permissions around integrations. Currently, any user can set up an integration, which could potentially lead to data being unintentionally exposed. It would be nice to have admin-level controls over what integrations and connected apps each user can access.

But in the end, Lead Gen & CRM's integration capabilities are quite strong. The combination of pre-built app connectors, iPaaS support, and a robust API means the platform can fit into most any tech stack. And based on my experience, the integrations are stable, and the data syncing between systems is reliable. Lead Gen & CRM has clearly put a lot of thought into making its CRM as extensible as possible.

How good is Lead Gen & CRM customer support?

Lead Gen & CRM provides a robust customer support experience for its CRM users. They offer a variety of channels to get help, including phone, email, and live chat support. Live chat is especially responsive and helpful for getting quick answers to questions.

The company also has a well-organized knowledge base with tutorials, training resources, and FAQs to help users self-serve and troubleshoot issues on their own. The articles are clear and include helpful screenshots. There's a handy search feature to find relevant content quickly.

However, Lead Gen & CRM could improve a few areas of its support. First, the live support channels are not 24/7 - you can generally only get real-time help during extended business hours. Off hours, you have to rely on their ticket system and wait for a response.

But, while many customers rave about the quality and friendliness of the support, some reviews mention that the first response time can occasionally be a bit slow, and complex issues may require some back and forth to fully resolve. Lead Gen & CRM doesn't publish official response time averages that I could find.

Lead Gen & CRM pricing and plans

Plan

Lite

Standard

Premium

Starting Price (500 contacts)

$12/month

$33/month

$120/month

Price at 1,000 Contacts

$35/month

$55/month

$160/month

Price at 10,000 Contacts

$80/month

$110/month

$275/month

Best for

Solopreneurs & basic list management

Growing small businesses needing automation

High-volume teams and advanced marketing

Limitations

1 user seat; single-step welcome automations; 10x contact email send limit

3 user seats; multi-step behavioral workflows; A/B testing; 12x email send limit

Unlimited user seats; custom behavioral paths; revenue attribution; 24x email send limit

Following its corporate acquisition and transition into Constant Contact Lead Gen & CRM, the platform has fundamentally abandoned its old, prohibitively expensive entry pricing structure. Rather than forcing early-stage startups to commit to a massive $449 monthly baseline just to manage 1,000 contacts, the platform now operates on a sliding, feature-tiered scale that makes full-funnel marketing automation accessible to microscopic budgets.

The modern ecosystem is split into three core tracks: Lite, Standard, and Premium. The foundational Lite plan starts at just $12/month for up to 500 contacts, scaling up to $33/month at the 1,000-contact threshold. While highly economical, the Lite plan severely restricts collaborative teams, limiting access to a single user seat and locking out all advanced behavioral workflows in favor of simple, single-step welcome emails.

The Standard plan represents the optimal middle ground for mid-sized teams, starting at $35/month and adjusting to $55/month for 1,000 contacts. Upgrading to Standard unlocks up to 3 user seats, robust multi-step marketing automation trees, behavioral contact segmentation, and subject line A/B testing tools.

For corporate teams requiring deep telemetry, the Premium tier begins at $80/month ($110/month at 1,000 contacts), removing user seat caps entirely while unlocking custom visual automation paths, revenue attribution dashboards, and integrated SEO tools.

Buyers must keep an eye on their contact ceilings, however: crossing into a higher contact bracket mid-cycle triggers an automatic account upgrade, and exceeding your monthly tiered email delivery volume limits results in an overage fee of $0.002 per email. For massive databases scaling past 50,000 records or specialized white-label marketing setups, customized Agency and Enterprise quotes remain available upon request.

How we tested Lead Gen & CRM

At TechRadar Pro, our CRM testing methodology goes beyond vendor's advertised functionality. To properly evaluate Constant Contact Lead Gen & CRM and its core promise of delivering a unified sales-and-marketing environment, our testing analysts deployed the software in a live production environment configured for mid-market business demands.

We conducted a visual automation stress test, carried out visitor de-anonymization tracking, and assessed the dynamic content performance. Support was also a key feature for the review, and because Constant Contact locks real-time help desks behind extended regional business hours rather than offering global 24/7 coverage, we systematically verified their customer support turnaround. That way you can trust our review wherever you're based.

Lead Gen & CRM review: Summary

Lead Gen & CRM is a solid, intuitive, and easy-to-use CRM solution that provides good value for small to mid-sized businesses and marketing agencies. The platform offers a robust set of features, including lead management, email marketing, social media management, and a built-in CRM at an affordable price point compared to some competitors.

However, Lead Gen & CRM is not without some shortcomings. While the core feature set is solid, it may fall short for companies with very advanced sales automation needs. Some users have also reported occasional performance issues and bugs.

• Valve's Steam Machine has seemingly sold out straight away in Japan
• Reservations are going for up to $3,000 in the US on eBay
• If you're tempted to look at cheap alternatives from Asia given all this, be very cautious around that idea

Given the price of the Steam Machine (and some other wrinkles with the device) it's not surprising that many gamers are looking for alternatives, but you need to be careful in that regard – although you may find it difficult to believe that some people are willing to pay a lot more than the official MSRP for Valve's gaming PC.

Before we come onto the tale of how much scalpers are reselling Steam Machine reservations for, the cautionary development is the likes of what appear to be super-affordable Steam Machine clones being offered over in China.

A prime example posted on Reddit is a white Steam Machine copy which claims to be built around a Ryzen 5 5500 processor with 16GB of DDR5 RAM, alongside an AMD RX 6750 GRE graphics card with a 2TB SSD. This is selling for the equivalent of $688 in China, so compare that to what Valve's charging for the Steam Machine with 2TB of storage: $1,349 in the US.

So, on the face of it, you're looking at not far off half the price for the Chinese clone PC, but there are a fair few weighty caveats attached which I'll come back to in a moment.

Meanwhile, while there are those searching for a bargain alternative to the official Steam Machine, at the other end of the spectrum there are those willing to pay something like double the asking price to secure one of the initial Steam Machine models to roll off the production lines.

As TweakTown noticed, there are people trying to resell their reservations for a Steam Machine on eBay. In case you didn't realize, Valve offered the chance to reserve a spot to purchase its gaming PC (using a randomized lottery system, rather than first-come-first-served), and some successful folks are effectively selling their place in the line.

Some of these auction listings are up for sale at approaching $3,500 over in the US (for the 2TB model), and TweakTown notes there appears to be a confirmed sale at $2,800. It's difficult to believe someone would pay that much, but it's seemingly true (unless the seller is engaging in shenanigans somehow).

On top of that, Notebookcheck.net highlighted another apparent indication of the popularity of the Steam Machine as Valve readies to open pre-orders (for those with a reservation). In actual fact, the device is already on sale in the Asian market, and the PC has already sold out in Japan. Seemingly retailer Komodo Station put the Steam Machine straight onto its shelves (rather than using a reservation system), and the PCs didn't hang about for long before they vanished.

Analysis: reasons to be fearful

(Image credit: Valve)

There's certainly a level of demand for the Steam Machine, then, although this could, and indeed I'd argue it's likely to be, a reflection of stock levels as much as it is demand. Nonetheless, there are disgruntled gamers over in Japan complaining on social media that they can't get a device.

This is also reflected in the apparent eBay prices for reservations in the US, although there's an important point to note here: most of these haven't sold (yet). In case you were mulling this route, bear in mind that you are placing a lot of trust in the seller to fulfil your order in the end. It's not an approach I'd recommend, and neither is buying a Steam Machine clone from Asia because it seems like a bargain and a half.

What are the dangers of the latter? Well, mainly that you don't really know what you'll be getting. If we take the highlighted example of the Chinese PC on Reddit above, there are some notable red flags with the listing, including that the Ryzen CPU is paired with DDR5 RAM that the platform it runs on (AM4) doesn't support.

On top of that, the RX 6750 GRE is a relatively chunky GPU, as several Redditors point out, and it seems highly unlikely that it'll fit in the chassis which is pictured for the device. What about the thermals, cooling solution, and fan noise, too? I'd be especially worried on those fronts.

Who knows: maybe you'll get a much larger box than the illustrated case, or components that are different to those advertised. I'm not saying this will necessarily be the case with the example product shown, but this is the concern with all of these kinds of offers from Asia, and it's why I'd take a hard pass on any such buying opportunity when it's being shipped outside of China.

Remember, there's the added cost of importing the PC to be considered as well, not to mention that if the device goes wrong or runs overly hot and unstable, then good luck with the returns process. There's also the potential security risks of a PC from an unknown vendor over in China that might be loaded with a dodgy version of SteamOS to trap the unwary.

In short, there are potential pitfalls aplenty, and if you want a more affordable alternative to the Steam Machine – or a living room PC with more performance and bang-for-buck like the so-called 'Stim Machine' – then buy something locally, and from a trusted (national) retailer.

Or just take the DIY path and build your own Steam Machine, which is the other option available to those who are unimpressed with Valve's pricing. Of course, you have to bear in mind that the RAM crisis – which forced up the price of the Steam Machine in the first place – will make this a much trickier endeavor than it would have been a year ago. There are also elements of Valve's PC that a DIY build won't be able to replicate, such as HDMI CEC support.

The U.S. Supreme Court has upheld a Mississippi law that allows election officials to count mail-in ballots that are postmarked by Election Day but received up to five days after it.

(Image credit: Rebecca Droke)

• Samsung wants NAND layer counts to reach four digits this decade
• Future M.2 SSDs could expand from 8TB to 32TB capacities
• Cell Multi-Bonding may replace traditional approaches to NAND density growth

Samsung has mapped out a NAND strategy stretching toward 1000-layer memory designs as demand for denser storage continues accelerating across industries.

The roadmap, disclosed during the IEEE/JSAP VLSI Symposium 2026, extends current vertical scaling plans far beyond existing commercial products.

At the centre of those ambitions sits a future generation of storage capable of pushing familiar SSD capacities into unfamiliar territory.

The route from today's drives to tomorrow's 32TB M.2 SSDs

Samsung expects its NAND technology to reach roughly 420 layers by 2029 before advancing beyond 560 layers during 2030.

Beyond that point, the company intends to explore architectures carrying between 900 and 1000 layers within future generations of flash memory.

Rather than constructing one towering NAND structure, Samsung plans to combine multiple stacks through its Cell Multi-Bonding technology approach.

The method joins separate NAND structures together inside one package to achieve densities that resemble a single 1000-layer device.

Samsung specifically discussed pairing two approximately 450-layer structures to approach the effective density associated with future four-digit layer counts.

According to company projections, this arrangement could increase storage density by as much as four times current generation solutions.

One example outlined during the presentation involved an 8TB QLC M.2 drive eventually scaling upward to reach 32TB capacities.

That scenario would allow substantially larger SSDs without increasing physical dimensions, preserving the compact M.2 format many users remember well.

The same scaling approach could eventually contribute toward enterprise drives exceeding 100TB while bringing Petabyte SSD discussions closer to reality.

The engineering problems standing between Samsung and a petabyte SSD

Samsung acknowledged that increasing layer counts introduces manufacturing complications that become progressively harder as structures grow vertically taller.

One major concern involves wafer warpage, where taller structures can deform during production and reduce manufacturing consistency or yields.

Another challenge comes from maintaining alignment accuracy across hundreds of stacked layers, requiring extremely precise overlay control throughout fabrication processes.

Even relatively minor deviations between layers can affect long-term reliability, performance, and manufacturing efficiency across finished storage products.

To limit deformation effects, Samsung plans to introduce an Upper Chuck Design intended to stabilise increasingly complex wafer structures.

The company also discussed Overlay Correction technologies intended to improve alignment precision as future NAND structures continue growing upward.

These developments arrive as conventional process shrinking becomes increasingly difficult, forcing memory manufacturers toward more elaborate vertical architectures.

Samsung has separately discussed a record-breaking 400-layer NAND generation that could help push AI hyperscaler SSD capacities beyond the 200TB barrier.

The company has also linked 430-layer NAND technology with a future where 100TB SSDs become increasingly mainstream across enterprise deployments.

Samsung will work with hafnia ferroelectrics in order to extend the practical layer counts beyond 1000 layers.

However, whether these designs eventually deliver mainstream 32TB M.2 drives or petabyte SSDs remains dependent upon manufacturing realities rather than roadmaps.

Samsung's latest roadmap nevertheless suggests the race toward NAND supremacy depends upon stacking ingenuity rather than shrinking dimensions.

Via The Guru of 3D

• Oracle admitted it needed a new approach back in February
• Now, the company has a new community-focused approach to MySQL
• Community roles and steering committee will ensure maximum quality

Oracle's VP of External Standards & Community Engagement, Heather VanCura, has revealed in a blog post the company's "next phase" of MySQL community engagement as it seeks to the open-source database project more transparent and collaborative.

The update comes after community criticism over Oracle's leadership of the project, and the company has finally responded with new governance frameworks.

In February 2026, Community Manager Frederic Descamps admitted the project was letting down community members. Descamps promised a "decisive" and "reinvigorated" approach.

Oracle announces "next phase" of MySQL

VanCura clearly acknowledged the role that community members have played in MySQL over the past three decades, referencing the need for visibility and deeper participation.

Under the new plans, Contributors can participate through code submissions, bug testing, code reviews, technical discussions and more. Experiences Contributors can become Committers, taking on responsibilities like code quality maintenance, and they're set to be guided by Mentors and Project Leads.

"Trust is built through transparent processes, clear decision-making, and meaningful opportunities for participation," VanCura added.

Oracle also launched a new Vulnerability Group and Technical Steering Committee. AWS, Google Cloud and Oracle will have representatives on the committee, but the company also noted the need for "additional perspectives from users of MySQL."

Percona co-founder Peter Zaitsev praised Oracle for its clear willingness to want to make changes (via The Register): "This is a step and in the right direction... Oracle has shown a desire to show more openness to the community in terms of sharing and including the wider community in the decision-making process."

Looking ahead, VanCura promises to share metrics with the community, engage in more discussions and uphold a high quality of contributions.

At SAP Sapphire in Orlando, Christian Klein put it plainly: “For the mission-critical processes of our customers, almost right just isn’t good enough.”

It was the line that crystallized the Autonomous Enterprise vision, and it is also the line that should reframe how every operations leader thinks about AI for the next eighteen months.

Sapphire made one thing unambiguous. AI is becoming visible at the top of the stack.

Joule (or your chosen equivalent) is being positioned as the new front door to enterprise software, with more than two hundred agents and over fifty assistants spanning finance, supply chain, procurement, HCM, and customer experience. Users will increasingly describe an outcome and let agents orchestrate the work across SAP and non-SAP systems.

That is the visible layer. There is also an invisible one, and it is the one that determines whether any of this actually delivers.

Agents only behave as well as the operational substrate they run on. They need systems that are healthy, observable, and consistent enough to act on safely. They need clean process telemetry, automated remediation when things break, and governance that extends across the hybrid landscape most large enterprises actually run. Without that foundation, agentic AI does not reduce operational risk. It multiplies it.

This is what future-proofing now means. Less about adopting the latest model, more about building the operational layer underneath it so that agents become a source of measurable outcomes rather than a source of new incidents.

The opportunity is significant for organizations that get this right. Two groups are forming. Those who have built the operational readiness to let agents execute, and those who will spend the next two years discovering they have not.

Pragmatism in ERP transformation

Enterprises are navigating significant transitions in their core systems, and the 2027 SAP ECC end-of-mainstream-maintenance deadline is the most visible forcing function. But the SAPinsider 2026 research surfaces a more interesting signal underneath it. AI readiness is now cited by 43% of organizations as the primary driver of their transformation investment, ranking above the deadline itself. The deadline creates urgency. AI readiness creates direction.

For many large enterprises, the preferred approach is not wholesale reinvention but incremental change. Brownfield migration has become a common starting point. It allows organizations to move existing systems to modern platforms while preserving established processes and minimizing disruption. In complex landscapes with extensive integrations and dependencies, that level of continuity is non-negotiable.

A brownfield approach also provides a structured path forward. It enables organizations to stabilize their core systems before introducing further innovation, including agentic AI. The transition to cloud ERP software plays a central role here. Managed, scalable environments establish the platform that supports both current operations and future capabilities, with continuous updates and easier integration of new services.

This foundation matters particularly for AI. As intelligent features become embedded within enterprise applications, cloud platforms provide the IT infrastructure needed to support them at scale. From advanced analytics to autonomous execution, AI capabilities are increasingly delivered as part of the platform rather than as separate tools.

During these transitions, most organizations operate in hybrid environments that combine on-premises and cloud systems. This state can persist for years, introducing complexity in governance, monitoring, and integration. Managing hybrid operations effectively requires clear definitions of roles and responsibilities, and an operational substrate that is observable, automatable, and consistent across the entire landscape.

As legacy solutions reach the end of life, organizations are reassessing how they support operations in this mixed environment, and the bar is rising.

AI as invisible infrastructure, AI as visible interaction

The Sapphire announcements make clear that AI is now operating at two layers, and both have to work.

At the interaction layer, AI is becoming the front door. Joule Work, the Autonomous Suite, and the broader agentic stack are designed to let users interact with enterprise systems through conversation and outcomes rather than screens and clicks. This is the visible AI, and it is what most of the industry will spend the next year talking about.

At the execution layer, AI is also becoming part of the underlying infrastructure. It will show up in observability, in automated remediation, in capacity and performance management, in the operational disciplines that have always determined whether mission-critical systems actually behave. This is the invisible AI, and it is what determines whether the visible layer delivers.

Lacking context is the number one reason enterprise AI projects fail to deliver value. Operational data, process telemetry, and the live state of the landscape are a critical part of that context. Agents that act on stale, incomplete, or unobservable systems will produce confident answers that quietly create new failure modes. Agents that act on a well-instrumented, well-automated estate will deliver the outcomes Sapphire promised.

This is why operational readiness is emerging as the real differentiator. Two groups are forming. Those who have built the foundation that lets agents execute reliably, and those who have never closed the gap between AI ambition and operational reality. The divide is not driven by access to technology. AI capabilities are increasingly available across major platforms. The divide is driven by whether the operational layer is ready to absorb them.

Positioning for long-term resilience

For enterprise and technology leaders, the convergence of cloud transformation and agentic AI presents a clearer opportunity than at any previous point in the SAP cycle. The path forward is not defined by rapid disruption but by deliberate, sustained evolution.

Future-proofing now means building the foundation that lets continuous improvement happen safely. It involves modernising core systems, embracing incremental change, and ensuring that emerging capabilities, especially agentic ones, can be integrated into operations without expanding the risk surface.

As AI becomes embedded across both the interaction layer and the execution layer, success will depend on how well organisations have prepared for both. The goal is intelligent operations that deliver tangible business outcomes, with AI serving as the enabler at every level of the stack. Resilience, adaptability, and operational discipline are the disciplines that will define long-term competitiveness in the autonomous enterprise era.

We list the best business cloud storage services.

This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.

The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit

• Windows 11's File Explorer is receiving major improvements via the latest preview update
• File Explorer should perform much faster, including mounting disk images
• The update is currently in the rollout process

Microsoft is still hard at work fixing pain points within Windows 11 for its users. While this case isn't focused on gaming improvements, it addresses an issue that should improve one of the operating system's fundamental aspects.

As reported by Windows Latest, Microsoft is rolling out File Explorer improvements with its latest preview update, KB5095093. The update includes much better speed and performance of the File Explorer and increased responsiveness when mounting disk images.

This is a long-awaited update for Windows 11 users, as File Explorer hasn't always been the most responsive or fastest, especially compared to macOS or SteamOS, both of which feature fairly responsive file managers.

It's also worth noting that PC hardware, specifically SSD speeds and storage space, can have an impact on loading times. Still, the onus has been on Microsoft to fix its Windows 11 File Explorer, which has been noticeably slow even with a high-speed SSD — so this update is very much necessary.

(Image credit: Surface/Unsplash)

Perhaps the most important improvement being rolled out is better performance for mounting disk images, which was arguably the worst aspect of Windows 11's File Explorer. This would often result in a five-minute wait for the disk image to fully open, and that's frustrating, especially for users with high-speed hardware.

Windows Latest also highlights that the 'Properties' tab on a file will be seeing a visual overhaul, with a more modern look using WinUI 3, as opposed to the Windows 95-era UI.

It's great to see Microsoft address these issues, seemingly as a wider attempt to improve Windows 11's functionality and appearance due to consistent user complaints. For sure, there's still more to be desired in the game performance aspect, but Microsoft should get praise where it's due.

My only concern is a potential update that could undo all of the hard work, since Windows 11 updates are notorious for breaking functionality, whether that's via File Explorer or as far as GPU stability — which have previously impacted Nvidia GPU users.

Have I Been Pwned added 124M stolen passwords. Discover how this infostealer data impacts New Zealand users and the essential steps to protect your online accounts.

The post New Infostealer Data Raises Fresh Risks for New Zealand Password Users appeared first on TechRepublic.

Google’s Chrome 149 security update fixes 18 bugs, including four critical flaws affecting WebGL, Autofill, and Blink components.

The post Update Chrome Now: Google Fixes 18 Security Flaws, Including Critical Bugs appeared first on TechRepublic.

Sugar season 2 returned to Apple TV after a break, and we've been introduced to an intriguing new case against that moreish LA noir-style backdrop.

One of the best Apple TV shows gave us quite the twist in season 1, and we've seen Colin Farrell's detective John Sugar deciding to stay on Earth after many of his fellow aliens decided to leave. He's been searching for his sister while staying hidden as a human detective, but how long will he be able to stay undetected?

Here's what you need to know about Sugar season 2, episode 3.

What time can I watch Sugar season 2 on Apple TV?

Sugar's newest case involves an up and coming boxer whose brother has gone missing. (Image credit: Apple TV)

The US can expect the third episode of Sugar season 2 to be available on Apple TV on July 3 at 12am PT / 3am ET. Episodes will then drop weekly until the finale on August 7.

Internationally, look out for the below times:

• US – 12am PT / 3am ET
• Canada – 12am PT / 3am ET
• UK – 8am BST
• India – 12:30pm IST
• Singapore – 3pm SGT
• Australia – 6pm AEST
• New Zealand – 8pm NZDT

When do new episodes of Sugar season 2 come out on Apple TV?

Episode 1: Out now

Episode 2: Out now

Episode 3: July 3

Episode 4: July 10

Episode 5: July 17

Episode 6: July 24

Episode 7: July 31

Episode 8: August 7

As AI increasingly underpins competitive advantage, UK organizations face mounting pressure to build a workforce capable of using these technologies effectively and confidently.

Universities are central to this talent pipeline. However, many employers see a growing disconnect between what students learn academically and the skills required in today’s workplace.

UK job postings mentioning AI skills are now 127% above pre‑pandemic levels, highlighting how quickly employer expectations are evolving.

To close this gap, particularly amid the ongoing AI skills shortage, higher education institutions need to place greater emphasis on practical, applied training.

That means ensuring students are not only familiar with AI tools, but capable of using them confidently, critically, and responsibly in real-world settings.

Core competencies such as prompt engineering, AI-enabled data analysis, and translating AI insights into business outcomes are essential.

Without these skills, graduates risk entering the workforce underprepared.

Employer expectations are rising faster than graduate readiness

The standard for what constitutes an ‘AI-ready' employee is increasing. As AI shifts from experimental to embedded in everyday workflows, organizations expect new hires to use these tools effectively and with minimal onboarding.

At the same time, many employers lack the internal capacity to build these capabilities themselves. A significant proportion report limited hands-on AI use across their workforce, and relatively few have invested in structured training programs. As a result, businesses are increasingly looking to early-career talent to help close this gap.

However, many graduates still enter the workplace without meaningful exposure to AI in a professional context or an understanding of how it informs decision-making. Without stronger integration of practical AI experience into higher education, the gap between employer expectations and graduate readiness is likely to widen.

Equipping educators is critical to building AI-ready talent

Universities are on the front line when it comes to preparing students for the responsible use of AI, both during their studies and beyond. But this depends on educators themselves feeling confident in how these tools work in practice.

This includes understanding which tools are appropriate for different use cases, how to incorporate them into learning in a way that builds critical thinking rather than shortcuts, and how to demonstrate responsible, real-world usage. Yet many educators still lack confidence in this area, particularly when it comes to applying AI in daily teaching or administrative tasks.

The challenge is that when educators are not fully comfortable with AI, it becomes harder to equip students with the practical skills they need. To address this, institutions need to move beyond basic awareness and invest in meaningful professional development.

Educators should be supported to understand not just how to use AI, but where it adds value, where it falls short, and how to evaluate its outputs critically. With this foundation, they can then introduce low-risk, practical opportunities for students to engage with AI. For example, using it to break down complex concepts while strengthening independent reasoning.

Embedding AI throughout the student journey

Despite AI becoming increasingly prevalent in the workplace, many students still remain hesitant to use it during their studies. This is often due to uncertainty around what is permitted. Clear and practical guidance from universities is essential to remove this ambiguity, reduce anxiety, and support responsible adoption.

Once expectations are clearly defined, institutions can create learning environments that help students understand not only how to use AI, but when and why. Greater transparency fosters confidence and builds the kind of ethical judgement that employers increasingly value.

In practice, this means modelling responsible use of AI while encouraging reflection and critical thinking. Assessment methods may also need to evolve by shifting focus from the final output to the full process of learning, including research, drafting and iteration.

Regular feedback and check-ins also play an important role. Tools that provide insight into how work develops over time can help educators offer more targeted guidance and create space for open conversations around AI use. Over time, this approach helps students build transferable skills, such as evaluating their own work, applying sound judgement, and clearly articulating the reasoning behind their decisions.

Final thought

The gap between what universities teach and what employers expect, particularly around AI, continues to grow. But with clear frameworks, better-supported educators, and a more deliberate integration of AI across curricula, there is a clear opportunity to realign education with workplace needs.

By investing in AI capability at every level (from faculty development to student experience), universities can ensure graduates leave with more than theoretical knowledge. Instead, they enter the workforce equipped to use AI with confidence. In doing so, institutions play a vital role in strengthening the talent pipeline that organizations increasingly depend on.

We list the best recruitment platforms.

This article was produced as part of TechRadar Pro Perspectives, our channel to feature the best and brightest minds in the technology industry today.

The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/pro/perspectives-how-to-submit

Instead of bouncing between AI tools, this platform puts models, file features, and creative tools together.

The post This $70 AI Assistant Aims to Consolidate Your Daily Work Tools appeared first on TechRepublic.

The return of Marvel's best-rated TV show is almost upon us, and with critical and commercial darling X-Men 97 set to return for its second season later this week, you'll want to know when it'll premiere on Disney+.

To spare you the trouble of searching for the release date and launch times for this season's first three chapters, I've rounded up the necessary information below. So, to paraphrase Cyclops: to me, my fellow Marvel fans!

What time can I watch the first three episodes of X-Men 97 season 2?

X-Men 97 season 2 will make its Disney+ debut on Wednesday, July 1. That's its global launch date, too, so North and South American viewers won't be able to watch this Marvel Cinematic Universe (MCU) project earlier than fans on other continents.

As for the exact time that its first three entries will arrive, they're expected to drop on July 1 at 12am PT / 3am ET. Based on those likely release times, we can work out when viewers in other nations should tune into one of the world's best streaming services to catch them, too:

• US — 12am PT / 3am ET
• Canada — 12am PT / 3am ET
• UK — 8am BST
• India — 12:30pm IST
• Singapore — 3pm SGT
• Australia — 5pm AEST
• New Zealand — 7pm NZST

X-Men 97 season 2 full release schedule

The countdown to mutant mayhem begins. Don’t miss the three-episode premiere of Marvel Animation’s #XMen97 Season 2 in one week, streaming only on Disney+. pic.twitter.com/iPIUkx15KgJune 24, 2026

Following this X-Men animated show's latest premiere, new episodes of the Marvel Phase 6 production will come out every Wednesday. That'll be the case until the season 2 finale airs on August 12, too.

For a quick rundown of the dates you need to know about, read on:

• Season 2 episode 1 — July 1
• Season 2 episode 2 — July 1
• Season 2 episode 3 — July 1
• Season 2 episode 4 — July 8
• Season 2 episode 5 — July 15
• Season 2 episode 6 — July 22
• Season 2 episode 7 — July 29
• Season 2 episode 8 — August 5
• Season 2 episode 9 — August 12

For more on the highly-rated TV series ahead of its return, remind yourself what happened in last season's finale via my X-Men 97 season 1 ending explained piece. Then, find out everything we know so far about X-Men 97 season 2.

Once you're done, read up on how to watch the X-Men movies in order and/or how to stream the Marvel movies in order.

What, like making a prequel series is hard? I should never have doubted the power of Elle Woods, who at this point feels like the pop culture equivalent of Mother Teresa to millennials.

Since the moment that Elle was announced by Prime Video, I've been it's number one hater. I've written opinion pieces about how its existence is going to destroy the sanctity of Elle's journey at Harvard, and I've spent hours stewing over how anybody could touch the side of Reese Witherspoon's career-defining performance. If we're getting another Legally Blonde project, make it about Elle's Supreme Court Justice years... right?

But oh, how the mighty have fallen. Having now watched all eight episodes of Elle, my hater-self is metaphorically standing in a dumpster fire of her own making. As someone prepared to loathe it, take this next remark with absolute seriousness and sincerity: this series is outrageously good.

In the blink of an eye, I once again felt like my 6-year-old self when the 2001 movie first came out — enraptured, inspired and completely at ease with who I am inside. How? Well, that's just what Elle Woods does, regardless of who is playing her.

But if you'd have told me at Lexi Minetree was actually an AI version of Witherspoon in her twenties, I'd have believed you. Minetree has all of Witherspoon's mannerisms down to a tee, has perfected her voice, and wholeheartedly understands the spirit of the woman we all know and love. It is, frankly, a miracle.

But Minetree isn't the only reason for Elle's success... absolutely everybody, and almost everything, is pulling their weight.

Elle is about to put the Legally Blonde haters to shame — and most of the film's lore holds up

When Elle turns 16, she's forced to leave her Bel-Air luxury lifestyle behind for Seattle, all thanks to a plastic surgery scandal that her father is embroiled it. With her new high school in the grip of the 90s grunge scene, our favorite pink tornado is once again a fish out of water, and she has to fight to fit in.

As I've pointed out, Minetree's freakishly brilliant understanding of Elle — and how unwilling she is to deviate from Witherspoon's blueprint — spearheads the feel-good fun, but let's look at what's happening around her.

Surprisingly, Elle isn't just a nod to Legally Blonde. There are also clear references to big nineties and noughties hitters including Mean Girls, Clueless, Freaky Friday and The Breakfast Club, and the nostalgic yearning is strong. From the corded landlines to the banging soundtrack, our young adult life from this time period is fully and lovingly represented.

As willing as I initially was to write our Seattle newbies off, they're also a treat of an ensemble. Bel-Air bestie Madison (Jessica Belkin) shirks the airhead sidekick stereotype in favor of a grounded spirit and unshakable loyalty, while high school mean girl Kimberly (Chandler Kinney) is hiding a true self that is the last thing you'd expect (no spoilers here).

British boy Dustin (Zac Looker) fuels Elle's curiosity for anarchy and change, while also providing proof that she can truly extract the best out of every walk of life. A more touching shoutout goes to the enigmatic role of Dean Wilson, which marks James Van Der Beek's final acting credit before his death earlier this year.

It's no surprise that my favorite side character is Eva Woods, played by the underrated powerhouse in June Diane Raphael. You only had to briefly see this woman in Parks and Recreation or Grace and Frankie to know how much she truly understands the superficial class, which she poignantly balances with a steady heart and sense of empathy.

Sadly, Perfect Day by Hoku is nowhere to be seen

(Image credit: Prime Video)

Now for the most important bit of feedback: the existing Legally Blonde lore. For the most part, I found that it adds to my love of the IP rather than takes away from it, especially when it answers some pivotal questions.

Without giving too much away, we'll find out how Elle gets Bruiser the Chihuahua (who's wardrobe is absolutely jaw-dropping, by the way), how Elle ends up back in Bel-Air in time for the events of the original movie, and how she begins to gain an interest in defending innocent people.

However, it's this last one that's a bit of a sticking point. For those of us who know the 2001 film better than we know ourselves, it's unspoken knowledge that Elle had zero interest in pursuing anything related to a law degree, but was only compelled to do so to win boyfriend Warner back.

That, in a nutshell, is the reason why Legally Blonde even exists. So the mere fact that Elle's rewritten history suggests that this inspiration came much earlier in her life doesn't completely sit with what we know of her adult life. It's clearly supposed to be a seedling for what's to come, but perhaps is a little overplayed.

Even so, I had such a good time watching Elle that I don't even care. The ebbs and flows of high school drama are deliciously played, the script is genuinely hilarious, and the overarching narrative plot is addictively compelling. I've been that engrossed that I'd even go as far as to say that it needs a second season, stat.

What, like making a prequel series is hard? I should never have doubted the power of Elle Woods, who at this point feels like the pop culture equivalent of Mother Teresa to millennials.

Since the moment that Elle was announced by Prime Video, I've been it's number one hater. I've written opinion pieces about how its existence is going to destroy the sanctity of Elle's journey at Harvard, and I've spent hours stewing over how anybody could touch the side of Reese Witherspoon's career-defining performance. If we're getting another Legally Blonde project, make it about Elle's Supreme Court Justice years... right?

But oh, how the mighty have fallen. Having now watched all eight episodes of Elle, my hater-self is metaphorically standing in a dumpster fire of her own making. As someone prepared to loathe it, take this next remark with absolute seriousness and sincerity: this series is outrageously good.

In the blink of an eye, I once again felt like my 6-year-old self when the 2001 movie first came out — enraptured, inspired and completely at ease with who I am inside. How? Well, that's just what Elle Woods does, regardless of who is playing her.

But if you'd have told me at Lexi Minetree was actually an AI version of Witherspoon in her twenties, I'd have believed you. Minetree has all of Witherspoon's mannerisms down to a tee, has perfected her voice, and wholeheartedly understands the spirit of the woman we all know and love. It is, frankly, a miracle.

But Minetree isn't the only reason for Elle's success... absolutely everybody, and almost everything, is pulling their weight.

Elle is about to put the Legally Blonde haters to shame — and most of the film's lore holds up

When Elle turns 16, she's forced to leave her Bel-Air luxury lifestyle behind for Seattle, all thanks to a plastic surgery scandal that her father is embroiled it. With her new high school in the grip of the 90s grunge scene, our favorite pink tornado is once again a fish out of water, and she has to fight to fit in.

As I've pointed out, Minetree's freakishly brilliant understanding of Elle — and how unwilling she is to deviate from Witherspoon's blueprint — spearheads the feel-good fun, but let's look at what's happening around her.

Surprisingly, Elle isn't just a nod to Legally Blonde. There are also clear references to big nineties and noughties hitters including Mean Girls, Clueless, Freaky Friday and The Breakfast Club, and the nostalgic yearning is strong. From the corded landlines to the banging soundtrack, our young adult life from this time period is fully and lovingly represented.

As willing as I initially was to write our Seattle newbies off, they're also a treat of an ensemble. Bel-Air bestie Madison (Jessica Belkin) shirks the airhead sidekick stereotype in favor of a grounded spirit and unshakable loyalty, while high school mean girl Kimberly (Chandler Kinney) is hiding a true self that is the last thing you'd expect (no spoilers here).

British boy Dustin (Zac Looker) fuels Elle's curiosity for anarchy and change, while also providing proof that she can truly extract the best out of every walk of life. A more touching shoutout goes to the enigmatic role of Dean Wilson, which marks James Van Der Beek's final acting credit before his death earlier this year.

It's no surprise that my favorite side character is Eva Woods, played by the underrated powerhouse in June Diane Raphael. You only had to briefly see this woman in Parks and Recreation or Grace and Frankie to know how much she truly understands the superficial class, which she poignantly balances with a steady heart and sense of empathy.

Sadly, Perfect Day by Hoku is nowhere to be seen

(Image credit: Prime Video)

Now for the most important bit of feedback: the existing Legally Blonde lore. For the most part, I found that it adds to my love of the IP rather than takes away from it, especially when it answers some pivotal questions.

Without giving too much away, we'll find out how Elle gets Bruiser the Chihuahua (who's wardrobe is absolutely jaw-dropping, by the way), how Elle ends up back in Bel-Air in time for the events of the original movie, and how she begins to gain an interest in defending innocent people.

However, it's this last one that's a bit of a sticking point. For those of us who know the 2001 film better than we know ourselves, it's unspoken knowledge that Elle had zero interest in pursuing anything related to a law degree, but was only compelled to do so to win boyfriend Warner back.

That, in a nutshell, is the reason why Legally Blonde even exists. So the mere fact that Elle's rewritten history suggests that this inspiration came much earlier in her life doesn't completely sit with what we know of her adult life. It's clearly supposed to be a seedling for what's to come, but perhaps is a little overplayed.

Even so, I had such a good time watching Elle that I don't even care. The ebbs and flows of high school drama are deliciously played, the script is genuinely hilarious, and the overarching narrative plot is addictively compelling. I've been that engrossed that I'd even go as far as to say that it needs a second season, stat.

Pakistan says it targeted militant hideouts along the Pakistan-Afghanistan border in response to militant attacks across Pakistan. Afghanistan condemned the strikes as acts of aggression.

(Image credit: Saifullah Zahir)