Daily Tech Digest by Kannan Subbiah: context engineering

Showing posts with label context engineering. Show all posts

Daily Tech Digest - April 17, 2026

Quote for the day:

"We don't grow when things are easy. We grow when we face challenges." -- @PilotSpeaker

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Duration: 22 mins • Perfect for listening on the go.

The agent tier: Rethinking runtime architecture for context-driven enterprise workflows

The article "The : Rethinking Runtime Architecture for Context-Driven Enterprise Workflows" explores the evolution of enterprise software from rigid, deterministic workflows to more flexible, agentic systems. Traditionally, business logic relies on explicit branching and hard-coded rules, which often fail to handle the nuanced, context-dependent variations found in complex processes like customer onboarding or fraud detection. To address this limitation, the author introduces the "Agent Tier"—a distinct architectural layer that separates deterministic execution from contextual reasoning. While the deterministic lane maintains authoritative control over state transitions and regulatory compliance, the Agent Tier interprets diverse signals to recommend the most appropriate next actions. This system utilizes the "Reason and Act" (ReAct) pattern, allowing AI agents to interact with governed enterprise tools within a structured reasoning cycle. By decoupling adaptive reasoning from execution, organizations can manage ambiguity more effectively without sacrificing the reliability, safety, or explainability of their core operations. This two-lane approach enables incremental adoption, allowing enterprises to modernize their workflows by integrating adaptive logic into specific points of uncertainty. Ultimately, the Agent Tier provides a scalable, robust framework for building responsive, intelligent enterprise systems that maintain strict governance while navigating the complexities of modern, context-driven business environments.

Crypto Faces Increased Threat From Quantum Attacks

The article "From RSA to Lattices: The Shift" explores the intensifying race to secure digital infrastructure against the looming threat of quantum computing. Central to this discussion is a landmark whitepaper from Google Quantum AI, which reveals that the quantum resources required to break contemporary encryption are approximately twenty times smaller than previously estimated. While current quantum processors possess around 1,000 qubits, the finding that only 500,000 qubits—rather than tens of millions—could compromise RSA and elliptic curve cryptography significantly accelerates the timeline for migration. Expert Chris Peikert highlights that this "lose-lose" situation for classical security stems from compounding advancements in both quantum algorithms and hardware efficiency. The urgency is particularly acute for blockchain and cryptocurrency networks, which face the "harvest now, decrypt later" risk where encrypted data is stolen today to be cracked once capable hardware emerges. Transitioning to lattice-based post-quantum cryptography remains a complex hurdle due to the larger key sizes and signature requirements that stress existing system architectures. Although a successful attack remains unlikely within the next three years, the growing probability over the next decade necessitates immediate industry-wide re-evaluation and the adoption of more resilient, crypto-agile standards to safeguard global data integrity.

The endless CISO reporting line debate — and what it says about cybersecurity leadership

In his article, JC Gaillard explores why the debate over the Chief Information Security Officer (CISO) reporting line persists into 2026, suggesting that the focus on organizational charts masks a deeper struggle with defining the CISO’s actual role. While reporting lines define authority and visibility, Gaillard argues that the core issue is whether a CISO possesses the organizational standing to influence cross-functional silos like legal, HR, and operations. Historically viewed as a technical IT function, cybersecurity has evolved into a strategic business priority, yet governance structures often lag behind. The author asserts there is no universal reporting model; success depends less on whether a CISO reports to the CEO, CIO, or COO, and more on the quality of the relationship and mutual trust with their superior. Furthermore, the supposed conflict between CIOs and CISOs is labeled as an outdated notion, as modern security must be embedded within technology architecture rather than acting as external oversight. Ultimately, the endless debate signals that many organizations still fail to internalize cyber risk as a strategic leadership challenge. Until companies bridge this governance gap by empowering CISOs with genuine influence, structural changes alone will remain insufficient for achieving true digital resilience and organizational alignment.

Building a Leadership Bench Inside IT

Developing a robust within Information Technology (IT) departments has become a strategic imperative for modern enterprises facing rapid digital transformation. The article emphasizes that cultivating internal talent is not merely a human resources function but a critical operational necessity to ensure business continuity and organizational agility. Organizations are increasingly moving away from reactive hiring, instead focusing on identifying high-potential employees early in their careers. These individuals are nurtured through deliberate strategies, including formal mentorship programs, cross-functional rotations, and targeted soft-skills training to bridge the gap between technical expertise and executive management. A successful leadership bench allows for seamless succession planning, reducing the risks associated with sudden executive departures and the high costs of external recruitment. Furthermore, the article highlights that fostering a culture of continuous learning and empowerment encourages retention, as employees see clear pathways for advancement. By investing in diverse talent and providing opportunities for real-world decision-making, IT leaders can build a resilient pipeline that aligns technical innovation with broader corporate objectives. This proactive approach ensures that when the time comes for a leadership transition, the organization is already equipped with visionaries who understand both the underlying infrastructure and the strategic vision of the company.

Data Center Protests Are Growing. How Should the Industry Respond?

Community opposition to data center construction has evolved into an organized movement, significantly impacting the industry by halting roughly $18 billion in projects and delaying an additional $46 billion over the last two years. While some resistance is characterized as "not in my backyard" sentiment, many protesters raise legitimate concerns regarding environmental impact, resource depletion, and public health. Specifically, residents worry about overstressed power grids, excessive water consumption in drought-prone areas, and noise or air pollution from backup generators. Furthermore, the limited number of permanent operational roles compared to the massive initial construction workforce often leaves locals feeling that the economic benefits are fleeting. To navigate this increasingly hostile landscape, industry leaders emphasize that developers must move beyond mere compliance and focus on genuine community partnership. Recommended strategies include engaging with residents early in the planning process, providing transparent data on resource usage, and adopting sustainable technologies like closed-loop cooling systems or waste heat recycling. By investing in local infrastructure and creating stable career pipelines, developers can transform from perceived "takers" of energy into valued community assets. Addressing these social and environmental anxieties is now essential for securing the future of large-scale infrastructure projects in an era of rapid AI expansion.

Empower Your Developers: How Open Source Dependencies Risk Management Can Unlock Innovation

In this InfoQ presentation, Celine Pypaert addresses the pervasive nature of and outlines a comprehensive strategy for managing the inherent risks associated with third-party dependencies. She emphasizes a critical shift from reactive "firefighting" to a proactive risk management framework designed to secure modern application architectures. Central to her blueprint is the use of Software Composition Analysis (SCA) tools and the implementation of Software Bills of Materials (SBOM) to achieve deep visibility into the software supply chain. Pypaert highlights the necessity of prioritizing high-risk vulnerabilities through the lens of exploitability data, ensuring that engineering teams focus their limited resources on the most impactful threats. A significant portion of the session focuses on bridging the historical divide between DevOps and security teams by establishing clear lines of ownership and automated governance. By defining accountability and integrating security checks directly into the development lifecycle, organizations can eliminate bottlenecks and reduce friction. Ultimately, Pypaert argues that robust dependency management does not just mitigate danger; it empowers developers and unlocks innovation by providing a stable, secure foundation for rapid software delivery. This systematic approach transforms security from a perceived hindrance into a strategic enabler of technical agility and enterprise growth.

Designing Systems That Don’t Break When It Matters Most

The article "Designing Systems That Don't Break When It Matters Most" explores the critical challenges of maintaining during extreme traffic spikes. Author William Bain argues that the most damaging failures often arise not from technical bugs but from scalability limits in state management. While stateless web services are easily scaled, they frequently overwhelm centralized databases, creating significant bottlenecks. Traditional distributed caching offers some relief by hosting "hot data" in memory; however, it remains vulnerable to issues like synchronized cache misses and "hot keys" that dominate access patterns. To overcome these hurdles, Bain advocates for "active caching," a strategy where application logic is moved directly into the cache. This approach treats cached objects as data structures, allowing developers to invoke operations locally and minimizing the need to move large volumes of data across the network. To ensure robustness, teams must load test for contention rather than just volume, tracking data motion and shared state round trips. Ultimately, designing for peak performance requires prioritizing state management as the primary scaling hurdle, keeping the database off the critical path while leveraging active caching to maintain a seamless user experience even under extreme pressure.

Cyber rules shift as geopolitics & AI reshape policy

The NCC Group’s latest Global Cyber Policy Radar highlights a transformative shift in the cybersecurity landscape, where regulation is increasingly dictated by geopolitical tensions, state-sponsored activities, and the rapid adoption of . No longer confined to mere technical compliance, cyber policy has evolved into a strategic extension of national security and economic interests. This shift is characterized by a rise in digital sovereignty, with governments asserting stricter control over data, infrastructure, and supply chains, often resulting in a fragmented regulatory environment for multinational organizations. Furthermore, artificial intelligence is being governed through existing cyber frameworks, increasing the scrutiny of how businesses secure these emerging tools. A significant trend involves moving cyber governance into the boardroom, placing direct accountability on senior leadership as major legislative acts like NIS2 and the come into force. Perhaps most notably, there is a growing emphasis on offensive cyber capabilities as a core component of national deterrence strategies, moving beyond traditional defensive measures. For global enterprises, navigating this complex patchwork of national priorities requires moving beyond basic technical standards toward integrated resilience and proactive engagement with public authorities. Boards must now understand their strategic position within a world where cyber operations and international power dynamics are inextricably linked.

Is ‘nearly right’ AI generated code becoming an enterprise business risk?

The article examines the escalating enterprise risks associated with "nearly right" AI-generated code—software that appears functional but contains subtle errors or misses critical edge cases. As organizations increasingly adopt AI coding agents, which some analysts estimate produce up to 60% of modern code, the sheer volume of output is creating a massive quality assurance bottleneck. While AI excels at basic syntax, it often struggles with complex behavioral integration in legacy enterprise ecosystems, particularly in high-stakes sectors like finance and telecommunications. Experts warn that even minor AI-driven changes can trigger cascading system failures or outages, citing recent high-profile incidents reported at companies like Amazon. Beyond operational reliability, the shift introduces significant security vulnerabilities, such as prompt injection attacks and bloated codebases containing hidden dependencies. The core challenge lies in the fact that many large enterprises still rely on manual testing processes that cannot scale to match AI’s relentless speed. Ultimately, the article argues that the solution is not just better AI, but more robust governance and automated testing. Without clear human-in-the-loop oversight and rigorous verification protocols, the productivity gains promised by AI could be undermined by unpredictable business disruptions and an expanded cyberattack surface.

Why Traditional SOCs Aren’t Enough

The article argues that traditional Security Operations Centers (SOCs) are no longer sufficient to manage the complexities of modern digital environments characterized by AI-driven threats and rapid cloud adoption. While SOCs remain foundational for threat detection, they are inherently reactive, often operating in data silos that lack critical business context. This limitation results in analyst burnout and a failure to prioritize risks based on financial or regulatory impact. To address these systemic gaps, the author proposes a transition to a Risk Operations Center (ROC) framework, specifically highlighting DigitalXForce’s AI-powered X-ROC. Unlike traditional models, a ROC is proactive and risk-centric, integrating cybersecurity with governance and operational risk management. X-ROC utilizes artificial intelligence to provide continuous assurance and real-time risk quantification, effectively translating technical vulnerabilities into strategic business metrics such as the "." By automating manual workflows and control testing, this next-generation approach significantly reduces operational costs and audit fatigue while providing boards with actionable visibility. Ultimately, the shift from a reactive SOC to a business-aligned ROC allows organizations to transform risk management from a passive reporting requirement into a strategic advantage, ensuring resilience in an increasingly dynamic and dangerous global cyber landscape.

Daily Tech Digest - March 04, 2026

Quote for the day:

“The secret to success is good leadership, and good leadership is all about making the lives of your team members or workers better." -- Tony Dungy

Composable infrastructure and build-to-fit IT: From standard stacks to policy-defined intent

Fixed stacks turn into friction. They are either too heavy for small workloads or too rigid for fast-changing ones. Teams start to fork the standard build “just this once,” and suddenly the exception becomes the default. That is how sprawl begins. Composable infrastructure is the most practical way I have found to break that cycle, but only if we stop defining “composable” as modular hardware. The differentiator is not the pool of compute, storage or fabric. The differentiator is the control plane: The policy, automation and governance that make composition safe, repeatable and reversible. ... The moment you move from “stacks” to “building blocks,” the control plane becomes the product you operate. At a minimum, I expect the control plane to do the following: Translate intent into infrastructure using declarative definitions (infrastructure as code) and reusable compositions; Enforce policy as code consistently across pipelines and runtime; Prevent drift and continuously reconcile desired state; ... The “sprawl prevention” mechanisms that matter: Every composed environment has a time-to-live by default. If it is not renewed by policy, it is retired automatically; Policies require standard tags (application, owner, cost center, data classification). If tags are missing, provisioning fails early; Network exposure is deny-by-default. Public endpoints require explicit approval paths and documented intent;

Why workforce identity is still a vulnerability, and what to do about it

Workforce identity is strongest at the moment of proofing. The risk isn’t usually malicious insiders slipping through onboarding. It’s what happens when verified identity is decoupled from account creation, daily access, and recovery. Manual handoffs are a common culprit. Identity is verified in one system, then an account is provisioned in another, often with human intervention in between. Temporary passwords are issued. Activation links are sent by email. Credentials are reset by help desk staff relying on judgment instead of evidence. ... If there is a single place where workforce identity collapses most consistently, it’s account recovery. Password resets, MFA re-enrollment, and help desk changes are designed to restore access quickly. In practice, they often bypass the very controls organizations rely on elsewhere. Knowledge-based questions, email verification, and voice-only confirmation remain common, even as attackers automate social engineering at scale. Help desk staff are placed in an impossible position. They are expected to verify identity without reliable evidence, under pressure to resolve issues quickly, using channels that are increasingly easy to spoof. ... Workforce identity assurance should begin with strong proofing, but it can’t stop there. Organizations need to deliberately preserve and periodically revalidate trust at key moments in the identity lifecycle, such as account creation, privilege changes, device enrollment, and recovery.

Microsoft: Hackers abuse OAuth error flows to spread malware

In the campaigns observed by Microsoft, the attackers create malicious OAuth applications in a tenant they control and configure them with a redirect URI pointing to their infrastructure. ... The researchers say that even if the URLs for Entra ID look like legitimate authorization requests, the endpoint is invoked with parameters for silent authentication without an interactive login and an invalid scope that triggers authentication errors. This forces the identity provider to redirect users to the redirect URI configured by the attacker. In some cases, the victims are redirected to phishing pages powered by attacker-in-the-middle frameworks such as EvilProxy, which can intercept valid session cookies to bypass multi-factor authentication (MFA) protections. Microsoft found that the ‘state’ parameter was misused to auto-fill the victim’s email address in the credentials box on the phishing page, increasing the perceived sense of legitimacy. ... Microsoft suggests that organizations should tighten permissions for OAuth applications, enforce strong identity protections and Conditional Access policies, and use cross-domain detection across email, identity, and endpoints. The company highlights that the observed attacks are identity-based threats that abuse an intended behavior in the OAuth framework that behaves as specified by the standard defining how authorization errors are managed through redirects.

Designing infrastructure for AI that actually works

Running AI at scale has real consequences for the systems underneath. The hardware is different, the density is higher, the heat output is significant, and power consumption is a more critical consideration than ever before. This affects everything from rack layouts to grid demand. ... Many AI workloads perform better when they are run locally. Inference applications, like real-time fraud detection, conversational interfaces, and live monitoring, benefit from lower latency and greater data control. This is driving demand for edge computing data centres that can operate independently, handle dense processing loads, and integrate into wider enterprise systems without excessive complexity. ... no template can replace a clear understanding of the use case. The type of model, the data sources, and the required response time, all shape what the critical digital infrastructure needs to deliver. Infrastructure leaders should be involved early in AI planning conversations. Their input can reduce rework, manage costs, and help the organisation avoid disruption from systems that fail under load. Sustainability is no longer optional As AI drives up energy use, scrutiny will follow. Efficiency targets are constantly being tightened across Europe, with new benchmarks being introduced for both new and existing data centre facilities. Regulators want to see measurable improvement, not just strategy slides. ... The organisations that succeed with AI at scale are often the ones that treat infrastructure as a first-order concern.

Context Engineering is the Key to Unlocking AI Agents in DevOps

Context engineering represents an architectural shift from viewing prompts as static strings to treating context as a dynamic, managed resource. This discipline encompasses three core competencies that separate production-grade agents from experimental toys. ... Structured Memory Architectures implement the 12-Factor Agent principles: semantic memory for infrastructure facts, episodic memory for past incident patterns, and procedural memory for runbook execution. Rather than maintaining monolithic conversation histories, production agents externalize state to vector stores and structured databases, injecting only necessary context at each decision point. ... Organizations transitioning to context-engineered agents should begin with observability. Instrument existing agents to track context growth patterns, identifying which tool calls generate bloated outputs and which historical contexts prove irrelevant. This data drives selective context strategies. Next, implement external memory architectures. Vector databases like Pinecone or Weaviate store semantic infrastructure knowledge; graph databases maintain dependency relationships; time-series databases track operational history. Agents query these systems contextually rather than maintaining monolithic state. Finally, adopt MCP incrementally. Start with non-critical internal tools, exposing them through MCP servers to establish patterns for authentication, context isolation, and monitoring.

LLMs can unmask pseudonymous users at scale with surprising accuracy

The findings have the potential to upend pseudonymity, an imperfect but often sufficient privacy measure used by many people to post queries and participate in sometimes sensitive public discussions while making it hard for others to positively identify the speakers. The ability to cheaply and quickly identify the people behind such obscured accounts opens them up to doxxing, stalking, and the assembly of detailed marketing profiles that track where speakers live, what they do for a living, and other personal information. This pseudonymity measure no longer holds. ... Unlike those older pseudonymity-stripping methods, Lermen said, AI agents can browse the web and interact with it in many of the same ways humans do. They can use simulated reasoning to match potential individuals. In one experiment, the researchers looked at responses given in a questionnaire Anthropic took about how various people use AI in their daily lives. Using the information taken from answers, the researchers were able to positively identify 7 percent of 125 participants. ... If LLMs’ success in deanonymizing people improves, the researchers warn, governments could use the techniques to unmask online critics, corporations could assemble customer profiles for “hyper-targeted advertising,” and attackers could build profiles of targets at scale to launch highly personalized social engineering scams.

What is digital employee experience — and why is it more important than ever?

Digital employee experience is a measure of how workers perceive and interact with the many digital tools and services they use in the workplace. It examines how employees feel about these technologies, including systems, software, and devices. Enterprises can deploy a DEX strategy that focuses on tracking, assessing, and improving employees’ technology experience, with the aim of increasing productivity and worker satisfaction. ... “DEX matters because the workplace is primarily digital for most employees, and friction creates compounding impact,” says Dan Wilson, vice president and research analyst, digital workplace, at research firm Gartner. Digital friction, not technology outages, has become the primary employee problem to manage, Wilson says. Brought on by fragmented technology deployments, inconsistent workflows, and other factors, “friction accumulates when employees can’t find information, miss updates, or work without context,” he says. ... “Most digital friction is invisible to IT because employees adapt instead of escalating,” Wilson says. “Friction accumulates across devices, apps, identity, workflows, and support, not in silos. These are not necessarily new issues, but the impact on the workforce increases as employees are increasingly dependent on technology to perform their work tasks.” ... While DEX tools can safely be used by non-IT teams, and some leading organizations do this, it’s not yet a common practice due to “limited IT maturity and collaboration” with the technology, Wilson says.

From 20 Lives an Hour to Zero: Can AI Power India’s Road Safety Reset?

India has made a clear and ambitious commitment. Under the Stockholm Declaration, the country aims to reduce road accident fatalities by 50% by 2030. But the numbers remind us how urgent this mission is. ... From a tech lens, the missing piece on the ground is continuous risk detection with immediate correction, at scale. Think of it like this, if the only time a driver feels the consequence of risk is at a checkpoint, behaviour changes briefly. When the “nudge” happens during the risky moment, exactly when speed crosses a certain threshold, or when the driver gets distracted, or when the following distance collapses, the behaviour of the driver changes more consistently because the driver can self-correct in the exact moment. Hence, the conversation has been shifting from “recordings & post analysis” to “faster, real-time and in-cab alerts” and a coaching loop that is actually sustainable. ... Most serious incidents don’t come out of nowhere. They come from a few ordinary seconds where risk stacks up, like a closing gap, a brief glance away, or fatigue building near the end of a shift. If you only sample driving periodically, you miss those sequences. If you only rely on post-trip analytics, you learn what happened after the fact, when the driver no longer has a chance to correct that moment. That is why analysing 100% of driving time matters. It captures what led up to risk, how often it repeats, and under what conditions it shows up.

Europe’s data center market booms: is it ready to take on the US?

If Europe wants technology to be a success for European companies, the capital must also come from Europe. The fact is that investors in America are generally able and willing to take significantly more risk than investors in Europe. Winterson is well aware of this, of course. He does believe that there are currently more “Europeans who want technology that helps Europeans become better at what they do.” ... Technological services are highly fragmented within Europe, and there is also a lack of a capital market of any substance. Finally, according to the report, there is no competitive energy market. These were and are issues that had to be resolved before more investment could come in. According to Winterson, the European Commission is now working quickly to resolve these issues. In his opinion, this is never fast enough, but the discussion surrounding sovereignty and dependence on technology from other parts of the world is certainly accelerating this process. ... It seems certain to us that data center capacity will increase significantly in the coming years. However, the question remains whether we in Europe can keep up with other parts of the world, particularly America. Winterson readily admits that investments from that corner in Europe will not decline very quickly. Based on the current distribution, we estimate that this would not be desirable either. It would leave a considerable gap.

Epic Fury introduces new layer of enterprise risk

Enterprise emergency action groups should already be validating assumptions and aligning organizational plans as conditions evolve. Today, however, that work becomes mandatory. This is a posture adjustment moment for all organizations that could be impacted by Operation Epic Fury and Iran’s response, not a wait and see moment. ... In post‑incident reviews, the pattern is consistent: Once tensions rise or conflict begins, civil aviation and maritime logistics become targeted, high‑impact levers for creating economic and political pressure. They are symbolic, visible, and deeply tied to global business operations. Any itinerary that transits the Gulf or relies on regional airspace or shipping lanes carries elevated risk. ... Iran’s cyber capability is not speculative; it is documented across years of joint advisories from CISA, FBI, NSA, and their international partners. Iranian state‑aligned actors routinely target poorly secured networks, internet‑connected devices, and critical infrastructure, often exploiting edge appliances, outdated software, and weak credentials. They have conducted disruptive operations against operational technology (OT) devices and have collaborated with ransomware affiliates to turn initial access into revenue or leverage. ... The practical point is simple: Iran’s cyber activity accelerates during periods of geopolitical tension, and enterprises with exposed services, unpatched infrastructure, or unmanaged edge devices become part of the accessible attack surface.

Daily Tech Digest - February 07, 2026

Quote for the day:

"Success in almost any field depends more on energy and drive than it does on intelligence. This explains why we have so many stupid leaders." -- Sloan Wilson

Tiny AI: The new oxymoron in town? Not really!

Could SLMs and minituarised models be the drink that would make today’s AI small enough to walk through these future doors without AI bumping into carbon-footprint issues? Would model compression tools like pruning, quantisation, and knowledge distillation help to lift some weight off the shoulders of heavy AI backyards? Lightweight models, edge devices that save compute resources, smaller algorithms that do not put huge stress on AI infrastructures, and AI that is thin on computational complexity- Tiny AI- as an AI creation and adoption approach- sounds unusual and promising at the onset. ... hardware innovations and new approaches to modelling that enable Tiny AI can significantly ease the compute and environmental burdens of large-scale AI infrastructures, avers Biswajeet Mahapatra, principal analyst at Forrester. “Specialised hardware like AI accelerators, neuromorphic chips, and edge-optimised processors reduces energy consumption by performing inference locally rather than relying on massive cloud-based models. At the same time, techniques such as model pruning, quantisation, knowledge distillation, and efficient architectures like transformers-lite allow smaller models to deliver high accuracy with far fewer parameters.” ... Tiny AI models run directly on edge devices, enabling fast, local decision-making by operating on narrowly optimised datasets and sending only relevant, aggregated insights upstream, Acharya spells out.

Kali Linux vs. Parrot OS: Which security-forward distro is right for you?

The first thing you should know is that Kali Linux is based on Debian, which means it has access to the standard Debian repositories, which include a wealth of installable applications. ... There are also the 600+ preinstalled applications, most of which are geared toward information gathering, vulnerability analysis, wireless attacks, web application testing, and more. Many of those applications include industry-specific modifications, such as those for computer forensics, reverse engineering, and vulnerability detection. And then there are the two modes: Forensics Mode for investigation and "Kali Undercover," which blends the OS with Windows. ... Parrot OS (aka Parrot Security or just Parrot) is another popular pentesting Linux distribution that operates in a similar fashion. Parrot OS is also based on Debian and is designed for security experts, developers, and users who prioritize privacy. It's that last bit you should pay attention to. Yes, Parrot OS includes a similar collection of tools as does Kali Linux, but it also offers apps to protect your online privacy. To that end, Parrot is available in two editions: Security and Home. ... What I like about Parrot OS is that you have options. If you want to run tests on your network and/or systems, you can do that. If you want to learn more about cybersecurity, you can do that. If you want to use a general-purpose operating system that has added privacy features, you can do that.

Bridging the AI Readiness Gap: Practical Steps to Move from Exploration to Production

To bridge the gap between AI readiness and implementation, organizations can adopt the following practical framework, which draws from both enterprise experience and my ongoing doctoral research. The framework centers on four critical pillars: leadership alignment, data maturity, innovation culture, and change management. When addressed together, these pillars provide a strong foundation for sustainable and scalable AI adoption. ... This begins with a comprehensive, cross-functional assessment across the four pillars of readiness: leadership alignment, data maturity, innovation culture, and change management. The goal of this assessment is to identify internal gaps that may hinder scale and long-term impact. From there, companies should prioritize a small set of use cases that align with clearly defined business objectives and deliver measurable value. These early efforts should serve as structured pilots to test viability, refine processes, and build stakeholder confidence before scaling. Once priorities are established, organizations must develop an implementation road map that achieves the right balance of people, processes, and technology. This road map should define ownership, timelines, and integration strategies that embed AI into business workflows rather than treating it as a separate initiative. Technology alone will not deliver results; success depends on aligning AI with decision-making processes and ensuring that employees understand its value.

Proxmox's best feature isn't virtualization; it's the backup system

Because backups are integrated into Proxmox instead of being bolted on as some third-party add-on, setting up and using backups is entirely seamless. Agents don't need to be configured per instance. No extra management is required, and no scripts need to be created to handle the running of snapshots and recovery. The best part about this approach is that it ensures everything will continue working with each OS update. Backups can be spotted per instance, too, so it's easy to check how far you can go back and how many copies are available. The entire backup strategy within Proxmox is snapshot-based, leveraging localised storage when available. This allows Proxmox to create snapshots of not only running Linux containers, but also complex virtual machines. They're reliable, fast, and don't cause unnecessary downtime. But while they're powerful additions to a hypervised configuration, the backups aren't difficult to use. This is key since it would render the backups less functional if it proved troublesome to use them when it mattered most. These backups don't have to use local storage either. NFS, CIFS, and iSCSI can all be targeted as backup locations. ... It can also be a mixture of local storage and cloud services, something we recommend and push for with a 3-2-1 backup strategy. But there's one thing of using Proxmox's snapshots and built-in tools and a whole different ball game with Proxmox Backup Server. With PBS, we've got duplication, incremental backups, compression, encryption, and verification.

The Fintech Infrastructure Enabling AI-Powered Financial Services

AI is reshaping financial services faster than most realize. Machine learning models power credit decisions. Natural language processing handles customer service. Computer vision processes documents. But there’s a critical infrastructure layer that determines whether AI-powered financial platforms actually work for end users: payment infrastructure. The disconnect is striking. Fintech companies invest millions in AI capabilities, recommendation engines, fraud detection, personalization algorithms. ... From a technical standpoint, the integration happens via API. The platform exposes user balances and transaction authorization through standard REST endpoints. The card provider handles everything downstream: card issuance logistics, real-time currency conversion, payment network settlement, fraud detection at the transaction level, dispute resolution workflows. This architectural pattern enables fintech platforms to add payment functionality in 8-12 weeks rather than the 18-24 months required to build from scratch. ... The compliance layer operates transparently to end users while protecting platforms from liability. KYC verification happens at multiple checkpoints. AML monitoring runs continuously across transaction patterns. Reporting systems generate required documentation automatically. The platform gets payment functionality without becoming responsible for navigating payment regulations across dozens of jurisdictions.

Context Engineering for Coding Agents

Context engineering is relevant for all types of agents and LLM usage of course. My colleague Bharani Subramaniam’s simple definition is: “Context engineering is curating what the model sees so that you get a better result.” For coding agents, there is an emerging set of context engineering approaches and terms. The foundation of it are the configuration features offered by the tools, and then the nitty gritty of part is how we conceptually use those features. ... One of the goals of context engineering is to balance the amount of context given - not too little, not too much. Even though context windows have technically gotten really big, that doesn’t mean that it’s a good idea to indiscriminately dump information in there. An agent’s effectiveness goes down when it gets too much context, and too much context is a cost factor as well of course. Some of this size management is up to the developer: How much context configuration we create, and how much text we put in there. My recommendation would be to build context like rules files up gradually, and not pump too much stuff in there right from the start. ... As I said in the beginning, these features are just the foundation for humans to do the actual work and filling these with reasonable context. It takes quite a bit of time to build up a good setup, because you have to use a configuration for a while to be able to say if it’s working well or not - there are no unit tests for context engineering. Therefore, people are keen to share good setups with each other.

Reimagining The Way Organizations Hire Cyber Talent

The way we hire cybersecurity professionals is fundamentally flawed. Employers post unicorn job descriptions that combine three roles’ worth of responsibilities into one. Qualified candidates are filtered out by automated scans or rejected because their resumes don’t match unrealistic expectations. Interviews are rushed, mismatched, or even faked—literally, in some cases. On the other side, skilled professionals—many of whom are eager to work—find themselves lost in a sea of noise, unable to connect with the opportunities that align with their capabilities and career goals. Add in economic uncertainty, AI disruption and changing work preferences, and it’s clear the traditional hiring playbook simply isn’t working anymore. ... Part of fixing this broken system means rethinking what we expect from roles in the first place. Jones believes that instead of packing every security function into a single job description and hoping for a miracle, organizations should modularize their needs. Need a penetration tester for one month? A compliance SME for two weeks? A security architect to review your Zero Trust strategy? You shouldn’t have to hire full-time just to get those tasks done. ... Solving the cybersecurity workforce challenge won’t come from doubling down on job boards or resume filters. But organizations may be able to shift things in the right direction by reimagining the way they connect people to the work that matters—with clarity, flexibility and mutual trust.

News sites are locking out the Internet Archive to stop AI crawling. Is the ‘open web’ closing?

Publishers claim technology companies have accessed a lot of this content for free and without the consent of copyright owners. Some began taking tech companies to court, claiming they had stolen their intellectual property. High-profile examples include The New York Times’ case against ChatGPT’s parent company OpenAI and News Corp’s lawsuit against Perplexity AI. ... Publishers are also using technology to stop unwanted AI bots accessing their content, including the crawlers used by the Internet Archive to record internet history. News publishers have referred to the Internet Archive as a “back door” to their catalogues, allowing unscrupulous tech companies to continue scraping their content. ... The opposite approach – placing all commercial news behind paywalls – has its own problems. As news publishers move to subscription-only models, people have to juggle multiple expensive subscriptions or limit their news appetite. Otherwise, they’re left with whatever news remains online for free or is served up by social media algorithms. The result is a more closed, commercial internet. This isn’t the first time that the Internet Archive has been in the crosshairs of publishers, as the organisation was previously sued and found to be in breach of copyright through its Open Library project. ... Today’s websites become tomorrow’s historical records. Without the preservation efforts of not-for-profit organisations like The Internet Archive, we risk losing vital records.

Who will be the first CIO fired for AI agent havoc?

As CIOs deploy teams of agents that work together across the enterprise, there’s a risk that one agent’s error compounds itself as other agents act on the bad result, he says. “You have an endless loop they can get out of,” he adds. Many organizations have rushed to deploy AI agents because of the fear of missing out, or FOMO, Nadkarni says. But good governance of agents takes a thoughtful approach, he adds, and CIOs must consider all the risks as they assign agents to automate tasks previously done by human employees. ... Lawsuits and fines seem likely, and plaintiffs will not need new AI laws to file claims, says Robert Feldman, chief legal officer at database services provider EnterpriseDB. “If an AI agent causes financial loss or consumer harm, existing legal theories already apply,” he says. “Regulators are also in a similar position. They can act as soon as AI drives decisions past the line of any form of compliance and safety threshold.” ... CIOs will play a big role in figuring out the guardrails, he adds. “Once the legal action reaches the public domain, boards want answers to what happened and why,” Feldman says. ... CIOs should be proactive about agent governance, Osler recommends. They should require proof for sensitive actions and make every action traceable. They can also put humans in the loop for sensitive agent tasks, design agents to hand off action when the situation is ambiguous or risky, and they can add friction to high-stakes agent actions and make it more difficult to trigger irreversible steps, he says.

Measuring What Matters: Balancing Data, Trust and Alignment for Developer Productivity

Organizations need to take steps over and above these frameworks. It's important to integrate those insights with qualitative feedback. With the right balance of quantitative and qualitative data insights, companies can improve DevEx, increase employee engagement, and drive overall growth. Productivity metrics can only be a game-changer if used carefully and in conjunction with a consultative human-based approach to improvement. They should be used to inform management decisions, not replace them. Metrics can paint a clear picture of efficiency, but only become truly useful once you combine them with a nuanced view of the subjective developer experience. ... People who feel safe at work are more productive and creative, so taking DevEx into account when optimizing processes and designing productivity frameworks includes establishing an environment where developers can flag unrealistic deadlines and identify and solve problems together, faster. Tools, including integrated development environments (IDEs), source code repositories and collaboration platforms, all help to identify the systemic bottlenecks that are disrupting teams' workflows and enable proactive action to reduce friction. Ultimately, this will help you build a better picture of how your team is performing against your KPIs, without resorting to micromanagement. Additionally, when company priorities are misaligned, confusion and complexity follow, which is exhausting for developers, who are forced to waste their energy on bridging the gaps, rather than delivering value.

Daily Tech Digest - February 04, 2026

Quote for the day:

"The struggle you're in today is developing the strength you need for tomorrow." -- Elizabeth McCormick

A deep technical dive into going fully passwordless in hybrid enterprise environments

Before we can talk about passwordless authentication, we need to address what I call the “prerequisite triangle”: cloud Kerberos trust, device registration and Conditional Access policies. Skip any one of these, and your migration will stall before it gains momentum. ... Once your prerequisites are in place, you face critical architectural decisions that will shape your deployment for years to come. The primary decision point is whether to use Windows Hello for Business, FIDO2 security keys or phone sign-in as your primary authentication mechanism. ... The architectural decision also includes determining how you handle legacy applications that still require passwords. Your options are limited: implement a passwordless-compatible application gateway, deprecate the application entirely or use Entra ID’s smart lockout and password protection features to reduce risk while you transition. ... Start with a pilot group — I recommend between 50 and 200 users who are willing to accept some friction in exchange for security improvements. This group should include IT staff and security-conscious users who can provide meaningful feedback without becoming frustrated with early-stage issues. ... Recovery mechanisms deserve special attention. What happens when a user’s device is stolen? What if the TPM fails? What if they forget their PIN and can’t reach your self-service portal? Document these scenarios and test them with your help desk before full rollout.

When Cloud Outages Ripple Across the Internet

For consumers, these outages are often experienced as an inconvenience, such as being unable to order food, stream content, or access online services. For businesses, however, the impact is far more severe. When an airline’s booking system goes offline, lost availability translates directly into lost revenue, reputational damage, and operational disruption. These incidents highlight that cloud outages affect far more than compute or networking. One of the most critical and impactful areas is identity. When authentication and authorization are disrupted, the result is not just downtime; it is a core operational and security incident. ... Cloud providers are not identity systems. But modern identity architectures are deeply dependent on cloud-hosted infrastructure and shared services. Even when an authentication service itself remains functional, failures elsewhere in the dependency chain can render identity flows unusable. ... High availability is widely implemented and absolutely necessary, but it is often insufficient for identity systems. Most high-availability designs focus on regional failover: a primary deployment in one region with a secondary in another. If one region fails, traffic shifts to the backup. This approach breaks down when failures affect shared or global services. If identity systems in multiple regions depend on the same cloud control plane, DNS provider, or managed database service, regional failover provides little protection. In these scenarios, the backup system fails for the same reasons as the primary.

The Art of Lean Governance: Elevating Reconciliation to Primary Control for Data Risk

In today's environment comprising of continuous data ecosystems, governance based on periodic inspection is misaligned with how data risk emerges. The central question for boards, regulators, auditors, and risk committees has shifted: Can the institution demonstrate at the moment data is used that it is accurate, complete, and controlled? Lean governance answers this question by elevating data reconciliation from a back-office cleanup activity to the primary control mechanism for data risk reduction. ... Data profiling can tell you that a value looks unusual within one system. It cannot tell you whether that value aligns with upstream sources, downstream consumers, or parallel representations elsewhere in the enterprise. ... Lean governance reframes governance as a continual process-control discipline rather than a documentation exercise. It borrows from established control theory: Quality is achieved by controlling the process, not by inspecting outputs after failures. Three principles define this approach: Data risk emerges continuously, not periodically; Controls must operate at the same cadence as data movement; and Reconciliation is the control that proves process integrity. ... Data profiling is inherently inward-looking. It evaluates distributions, ranges, patterns, and anomalies within a single dataset. This is useful for hygiene, but insufficient for assessing risk. Reconciliation is inherently relational. It validates consistency between systems, across transformations, and through the lifecycle of data.

Working with Code Assistants: The Skeleton Architecture

Critical non-functional requirements- such as security, scalability, performance, and authentication- are system-wide invariants that cannot be fragmented. If every vertical slice is tasked with implementing its own authorization stack or caching strategy, the result is "Governance Drift": inconsistent security postures and massive code redundancy. This necessitates a new unifying concept: The Skeleton and The Tissue. ... The Stable Skeleton represents the rigid, immutable structures (Abstract Base Classes, Interfaces, Security Contexts) defined by the human although possibly built by the AI. The Vertical Tissue consists of the isolated, implementation-heavy features (Concrete Classes, Business Logic) generated by the AI. This architecture draws on two classical approaches: actor models and object-oriented inversion of control. It is no surprise that some of the world’s most reliable software is written in Erlang, which utilizes actor models to maintain system stability. Similarly, in inversion of control structures, the interaction between slices is managed by abstract base classes, ensuring that concrete implementation classes depend on stable abstractions rather than the other way around. ... Prompts are soft; architecture is hard. Consequently, the developer must monitor the agent with extreme vigilance. ... To make the "Director" role scalable, we must establish "Hard Guardrails"- constraints baked into the system that are physically difficult for the AI to bypass. These act as the immutable laws of the application.

8-Minute Access: AI Accelerates Breach of AWS Environment

A threat actor gained initial access to the environment via credentials discovered in public Simple Storage Service (S3) buckets and then quickly escalated privileges during the attack, which moved laterally across 19 unique AWS principals, the Sysdig Threat Research Team (TRT) revealed in a report published Tuesday. ... While the speed and apparent use of AI were among the most notable aspects of the attack, the researchers also called out the way that the attacker accessed exposed credentials as a cautionary tale for organizations with cloud environments. Indeed, stolen credentials are often an attacker's initial access point to attack a cloud environment. "Leaving access keys in public buckets is a huge mistake," the researchers wrote. "Organizations should prefer IAM roles instead, which use temporary credentials. If they really want to leverage IAM users with long-term credentials, they should secure them and implement a periodic rotation." Moreover, the affected S3 buckets were named using common AI tool naming conventions, they noted. The attackers actively searched for these conventions during reconnaissance, enabling them to find the credentials quite easily, they said. ... During this privilege-escalation part of the attack — which took a mere eight minutes — the actor wrote code in Serbian, suggesting their origin. Moreover, the use of comments, comprehensive exception handling, and the speed at which the script was written "strongly suggests LLM generation," the researchers wrote.

Ask the Experts: The cloud cost reckoning

According to the 2025 Azul CIO Cloud Trends Survey & Report, 83% of the 300 CIOs surveyed are spending an average of 30% more than what they had anticipated for cloud infrastructure and applications; 43% said their CEOs or boards of directors had concerns about cloud spend. Moreover, 13% of surveyed CIOs said their infrastructure and application costs increased with their cloud deployments, and 7% said they saw no savings at all. Other surveys show CIOs are rethinking their cloud strategies, with "repatriation" -- moving workloads from the cloud back to on-premises -- emerging as a viable option due to mounting costs. ... "At Laserfiche we still have a hybrid environment. So we still have a colocation facility, where we house a lot of our compute equipment. And of course, because of that, we need a DR site because you never want to put all your eggs in that one colo. We also have a lot of SaaS services. We're in a hyperscaler environment for Laserfiche cloud. "But the reason why we do both is because it actually costs us less money to run our own compute in a data center colo environment than it does to be all in on cloud." ,,, "The primary reason why the [cloud] costs have been increasing is because our use of cloud services has become much more sophisticated and much more integrated. "But another reason cloud consumption has increased is we're not as diligent in managing our cloud resources in provisioning and maintaining."

NIST develops playbook for online use cases of digital credentials in financial services

The objective is to develop what a panel description calls a “playbook of standards and best practices that all parties can use to set a high bar for privacy and security.” “We really wanted to be able to understand, what does it actually take for an organization to implement this stuff? How does it fit into workflows? And then start to think as well about what are the benefits to these organizations and to individuals.” “The question became, what was the best online use case?” Galuzzo says. “At which point our colleagues in Treasury kind of said, hey, our online banking customer identification program, how do we make that both more usable and more secure at the same time? And it seemed like a really nice fit. So that brought us to both the kind of scope of what we’re focused on, those online components, and the specific use case of financial services as well.” ... The model, he says, “should allow you to engage remotely, to not have to worry about showing up in person to your closest branch, should allow for a reduction in human error from our side and should allow for reduction in fraud and concern over forged documents.” It should also serve to fulfil the bank’s KYC and related compliance requirements. Beyond the bank, the major objective with mDLs remains getting people to use them. The AAMVA’s Maru points to his agency’s digital trust service, and to its efforts in outreach and education – which are as important in driving adoption as anything on the technical side.

Designing for the unknown: How flexibility is reshaping data center design

Rapid advances in compute architectures – particularly GPUs and AI-oriented systems – are compressing technology cycles faster than many design and delivery processes can respond. In response, flexibility has shifted from a desirable feature to the core principle of successful data center design. This evolution is reshaping how we think about structure, power distribution, equipment procurement, spatial layout, and long-term operability. ... From a design perspective, this means planning for change across several layers: Structural systems that can accommodate higher equipment loads without reinforcement; Spatial layouts that allow reconfiguration of white space and service zones; and Distribution pathways that support future modifications without disrupting live operations. The objective is not to overbuild for every possible scenario, but to provide a framework that can absorb change efficiently and economically. ... Another emerging challenge is equipment lead time. While delivery periods vary by system, generators can now carry lead times approaching 12 months, particularly for higher capacities, while other major infrastructure components – including transformers, UPS modules, and switchgear – typically fall within the 30- to 40-week range. Delays in securing these items can introduce significant risk when procurement decisions are deferred until late in the design cycle.

Onboarding new AI hires calls for context engineering - here's your 3-step action plan

In the AI world, the institutional knowledge is called context. AI agents are the new rockstar employees. You can onboard them in minutes, not months. And the more context that you can provide them with, the better they can perform. Now, when you hear reports that AI agents perform better when they have accurate data, think more broadly than customer data. The data that AI needs to do the job effectively also includes the data that describes the institutional knowledge: context. ... Your employees are good at interpreting it and filling in the gaps using their judgment and applying institutional knowledge. AI agents can now parse unstructured data, but are not as good at applying judgment when there are conflicts, nuances, ambiguity, or omissions. This is why we get hallucinations. ... The process maps provide visibility into manual activities between applications or within applications. The accuracy and completeness of the documented process diagrams vary wildly. Front-office processes are generally very poor. Back-office processes in regulated industries are typically very good. And to exploit the power of AI agents, organizations need to streamline them and optimize their business processes. This has sparked a process reengineering revolution that mirrors the one in the 1990s. This time around, the level of detail required by AI agents is higher than for humans.

Q&A: How Can Trust be Built in Open Source Security?

The security industry has already seen examples in 2025 of bad actors deploying AI in cyberattacks – I’m concerned that 2026 could bring a Heartbleed- or Log4Shell-style incident involving AI. The pace at which these tools operate may outstrip the ability of defenders to keep up in real time. Another focus for the year ahead: how the Cyber Resilience Act (CRA) will begin to reshape global compliance expectations. Starting in September 2026, manufacturers and open source maintainers must report exploited vulnerabilities and breaches to the EU. This is another step closer to CRA enforcement and other countries like Japan, India and Korea are exploring similar legislation. ... The human side of security should really be addressed just as urgently as the technical side. The way forward involves education, tooling and cultural change. Resilient human defences start with education. Courses from the Linux Foundation like Developing Secure Software and Secure AI/ML‑Driven Software Development equip users with the mindset and skills to make better decisions in an AI‑enhanced world. Beyond formal training, reinforcing awareness creating a vigilant community is critical. The goal is to embed security into culture and processes so that it’s not easily overlooked when new technology or tools roll around. ... Maintainers and the community projects they lead are struggling without support from those that use their software.

Daily Tech Digest - November 30, 2025

Quote for the day:

"The real leader has no need to lead - he is content to point the way." -- Henry Miller

Four important lessons about context engineering

Modern LLMs operate with context windows ranging from 8K to 200K+ tokens, with some models claiming even larger windows. However, several technical realities shape how we should think about context. ... Research has consistently shown that LLMs experience attention degradation in the middle portions of long contexts. Models perform best with information placed at the beginning or end of the context window. This isn’t a bug. It’s an artifact of how transformer architectures process sequences. ... Context length impacts latency and cost quadratically in many architectures. A 100K token context doesn’t cost 10x a 10K context, it can cost 100x in compute terms, even if providers don’t pass all costs to users. ... The most important insight: more context isn’t better context. In production systems, we’ve seen dramatic improvements by reducing context size and increasing relevance. ... LLMs respond better to structured context than unstructured dumps. XML tags, markdown headers, and clear delimiters help models parse and attend to the right information. ... Organize context by importance and relevance, not chronologically or alphabetically. Place critical information early and late in the context window. ... Each LLM call is stateless. This isn’t a limitation to overcome, but an architectural choice to embrace. Rather than trying to maintain massive conversation histories, implement smart context management

What Fuels AI Code Risks and How DevSecOps Can Secure Pipelines

AI-generated code refers to code snippets or entire functions produced by Machine Learning models trained on vast datasets. While these models can enhance developer productivity by providing quick solutions, they often lack the nuanced understanding of security implications inherent in manual coding practices. ... Establishing secure pipelines is the backbone of any resilient development strategy. When code flows rapidly from development to production, every step becomes a potential entry point for vulnerabilities. Without careful controls, even well-intentioned automation can allow flawed or insecure code to slip through, creating risks that may only surface once the application is live. A secure pipeline ensures that every commit, every integration, and every deployment undergo consistent security scrutiny, reducing the likelihood of breaches and protecting both organizational assets and user trust. Security in the pipeline begins at the earliest stages of development. By embedding continuous testing, teams can identify vulnerabilities before they propagate, identifying issues that traditional post-development checks often miss. This proactive approach allows security to move in tandem with development rather than trailing behind it, ensuring that speed does not come at the expense of safety.

The New Role of Enterprise Architecture in the AI Era

Traditional architecture assumes predictability in which once the code has shipped, systems behave in a standard way. On the contrary, AI breaks that assumption completely, given that the machine learning models continuously change as data evolves and model performance keeps fluctuating as every new dataset gets added. ... Architecture isn’t just a phase in the AI era; rather it’s a continuous cycle that must operate across various interconnected stages that follow well-defined phases. This process starts with discovery, where the teams assess and identify AI opportunities that are directly linked to the business objectives. Engage early with business leadership to define clear outcomes. Next comes design, where architects create modular blueprints for data pipelines and model deployment by reusing the proven patterns. In the delivery phase, teams execute iteratively with governance built in from the onset. Ethics, compliance and observability should be baked into the workflows, not added later as afterthoughts. Finally, adaptation keeps the system learning. Models are monitored, retrained and optimized continuously, with feedback loops connecting system behavior back to business metrics and KPIs (key performance indicators). When architecture operates this way, it becomes a living ecosystem that learns, adapts and improves with every iteration.

Quenching Data Center Thirst for Power Now Is Solvable Problem

“Slowing data center growth or prohibiting grid connection is a short-sighted approach that embraces a scarcity mentality,” argued Wannie Park, CEO and founder of Pado AI, an energy management and AI orchestration company, in Malibu, Calif. “The explosive growth of AI and digital infrastructure is a massive engine for economic, scientific, and industrial progress,” he told TechNewsWorld. “The focus should not be on stifling this essential innovation, but on making data centers active, supportive participants in the energy ecosystem.” ... Planning for the full lifecycle of a data center’s power needs — from construction through long-term operations — is essential, he continued. This approach includes having solutions in place that can keep facilities operational during periods of limited grid availability, major weather events, or unexpected demand pressures, he said. ... The ITIF report also called for the United States to squeeze more power from the existing grid without negatively impacting customers, while also building new capacity. New technology can increase supply from existing transmission lines and generators, the report explained, which can bridge the transition to an expanded physical grid. On the demand side, it added, there is spare capacity, but not at peak times. It suggested that large users, such as data centers, be encouraged to shift their demand to off-peak periods, without damaging their customers. Grids do some of that already, it noted, but much more is needed.

A Waste(d) Opportunity: How can the UK utilize data center waste heat?

Walking into the data hall, you are struck by the heat resonating from the numerous server racks, each capable of handling up to 20kW of compute. However, rather than allowing this heat to dissipate into the atmosphere, the team at QMUL had another plan. Instead, in partnership with Schneider Electric, the university deployed a novel heat reuse system. ... Large water cylinders across campus act like thermal batteries, storing hot water overnight when compute needs are constant, but demand is low, then releasing it in the morning rush. As one project lead put it, there is “no mechanical rejection. All the heat we generate here is used. The gas boilers are off or dialed down - the computing heat takes over completely.” At full capacity, the data center could supply the equivalent of nearly 4 million ten-minute showers per year. ... Walking out, it’s easy to see why Queen Mary’s project is being held up as a model for others. In the UK, however, the project is somewhat of an oddity, but through the lens of QMUL you can see a glimpse of the future, where compute is not only solving the mysteries of our universe but heating our morning showers. The question remains, though, why data center waste heat utilization projects in the UK are few and far between, and how the country can catch up to regions such as the Nordics, which has embedded waste heat utilization into the planning and construction of its data center sector.

Redefining cyber-resilience for a new era

The biggest vulnerability is still the human factor, not the technology. Many companies invest in expensive tools but overlook the behaviour and mindset of their teams. In regions experiencing rapid digital growth, that gap becomes even more visible. Phishing, credential theft and shadow IT remain common ways attackers gain access. What’s needed is a shift in culture. Cybersecurity should be seen as a shared responsibility, embedded in daily routines, not as a one-time technical solution. True resilience begins with awareness, leadership and clarity at all levels of the organisation. ... Leaders play a crucial role in shaping that future. They need to understand that cybersecurity is not about fear, but about clarity and long-term thinking. It is part of strategic leadership. The leaders who make the biggest impact will be the ones who see cybersecurity as cultural, not just technical. They will prioritise transparency, invest in ethical and explainable technology, and build teams that carry these values forward. ... Artificial Intelligence is already transforming how we detect and respond to threats, but the more important shift is about ownership. Who controls the infrastructure, the models and the data? Centralised AI, controlled by a few major companies, creates dependence and limits transparency. It becomes harder to know what drives decisions, how data is used and where vulnerabilities might exist.

Building Your Geopolitical Firewall Before You Need One

In today’s world, where regulators are rolling out data sovereignty and localization initiatives that turn every cross-border workflow into a compliance nightmare, this is no theoretical exercise. Service disruption has shifted from possibility to inevitability, and geopolitical moves can shut down operations overnight. For storage engineers and data infrastructure leaders, the challenge goes beyond mere compliance – it’s about building genuine operational independence before circumstances force your hand. ... The reality is messier than any compliance framework suggests. Data sprawls everywhere, from edge, cloud and core to laptops and mobile devices. Building walls around everything does not offer true operational independence. Instead, it’s really about having the data infrastructure flexibility to move workloads when regulations shift, when geopolitical tensions escalate, or when a foreign government’s legislative reach suddenly extends into your data center. ... When evaluating sovereign solutions, storage engineers typically focus on SLAs and certifications. However, Oostveen argues that the critical question is simpler and more fundamental: who actually owns the solution or the service provider? “If you’re truly sovereign, my view is that you (the solution provider) are a company that is owned and operated exclusively within the borders of that particular jurisdiction,” he explains.

The 5 elements of a good cybersecurity risk assessment

Companies can use a cybersecurity risk assessment to evaluate how effective their security measures are. This provides a foundation for deciding which security measures are important — and which are not. But also for deciding when a product or system is secure enough and additional measures would be excessive. When they’ve done enough cybersecurity. However, not every risk assessment fulfills this promise. ... Too often, cybersecurity risk assessments take place solely in cyberspace — but this doesn’t allow meaningful prioritizing of requirements. “Server down” is annoying, but cyber systems never exist for their own sake. That’s why risk assessments need a connection to real processes that are mission critical for the organization — or perhaps not. ... Without system understanding, there is no basis for attack modeling. Without attack modeling, there is no basis for identifying the most important requirements. It shouldn’t really be cybersecurity’s job to create system understanding. But since there is often a lack of documentation in IT, OT, or for cyber systems in general, cybersecurity is often left to provide it. And if cybersecurity is the first team to finally create an overview of all cyber systems, then it’s a result that is useful far beyond security risk assessment. ... Attack scenarios are a necessary stepping stone to move your thinking from systems and real-world impacts to meaningful security requirements — no more and no less.

Finding Strength in Code, Part 2: Lessons from Loss and the Power of Reflection

Every problem usually has more than one solution. The engineers who grow the fastest are the ones who can look at their own mistakes without ego, list what they’re good at and what they're not, and then actually see multiple ways forward. Same with life. A loss (a pet, a breakup, whatever) is a bug that breaks your personal system. ... Solo debugging has limits. On sprawling systems, we rally the squad—frontend, backend, QA—to converge faster. Similarly, grief isn't meant for isolation. I've leaned on my network: a quick Slack thread with empathetic colleagues or a vulnerability share in my dev community. It distributes the load and uncovers blind spots you might miss on your own. ... Once a problem is solved, it is essential to communicate the solution. The list of lessons from that solution: some companies solve problems, but never put the effort into documenting the process in a way that prevents them from happening again. I know it is impossible to avoid problems, as it is impossible not to make mistakes in our lives. The true inefficiency? Skipping the "why" and "how next time." ... Borrowed from incident response, it's a structured debrief that prevents recurrence without finger-pointing. In engineering, it ensures resilience; in life, it builds emotional antifragility. There are endless flavours of postmortems—simple Markdown outlines to full-blown docs—but the gold standard is "blameless," focusing on systems over scapegoats.

Cyber resilience is a business imperative: skills and strategy must evolve

Cyber upskilling must be built into daily work for both technical and non-technical employees. It’s not a one-off training exercise; it’s part of how people perform their roles confidently and securely. For technical teams, staying current on certifications and practicing hands-on defense is essential. Labs and sandboxes that simulate real-world attacks give them the experience needed to respond effectively when incidents happen. For everyone else, the focus should be on clarity and relevance. Employees need to understand exactly what’s expected of them; how their individual decisions contribute to the organization's resilience. Role-specific training makes this real: finance teams need to recognize invoice fraud attempts; HR should know how to handle sensitive data securely; customer service needs to spot social engineering in live interactions. ... Resilience should now sit alongside financial performance and sustainability as a core board KPI. That means directors receiving regular updates not only on threat trends and audit findings, but also on recovery readiness, incident transparency, and the cultural maturity of the organization's response. Re-engaging boards on this agenda isn’t about assigning blame—it’s about enabling smarter oversight. When leaders understand how resilience protects trust, continuity, and brand, cybersecurity stops being a technical issue and becomes what it truly is: a measure of business strength.