Daily Tech Digest by Kannan Subbiah: Critical Infrastructure

Showing posts with label Critical Infrastructure. Show all posts

Daily Tech Digest - March 09, 2026

Quote for the day:

"A positive attitude will not solve all your problems. But it will annoy enough people to make it worth the effort" -- Herm Albright

Is AI Killing Sustainability?

This article examines the paradoxical relationship between the rapid growth of artificial intelligence and environmental goals. On one hand, AI's massive computational needs are driving a surge in energy consumption, with global spending projected to reach $2.52 trillion this year. This expansion is fueling an exponential rise in data center power requirements, potentially consuming as much electricity as 22% of U.S. households by 2028. However, the author argues that AI also serves as a critical tool for boosting sustainability. By analyzing vast datasets, AI can optimize supply chains, automate waste management, and enhance energy efficiency in buildings by up to 30%. The piece provides six strategic tips for organizations to utilize AI for greenhouse gas reduction, including predictive environmental risk monitoring, accurate emission reporting, and improved renewable energy integration. Despite these benefits, a tension exists between corporate "green" ambitions and financial constraints, often leading to a "lite green" approach where cost-cutting takes priority over true environmental innovation. Ultimately, while AI's infrastructure poses a significant threat to climate targets, its potential to identify high-ROI decarbonization opportunities offers a path toward reconciling technological advancement with ecological preservation, provided that organizations move beyond superficial commitments toward mature, outcome-driven strategies.

PQC roadmap remains hazy as vendors race for early advantage

The transition to post-quantum cryptography (PQC) is evolving from a theoretical concern into an urgent operational risk, prompting major security vendors to race for early market advantages. As mainstream players like Palo Alto Networks, Cisco, and IBM join specialized firms, the focus has shifted toward structured readiness offerings centered on discovery, inventory, and migration planning. A significant hurdle for organizations remains the lack of visibility into cryptographic sprawl across infrastructure, making it difficult to identify vulnerabilities in legacy algorithms like RSA. The urgency is further fueled by the “harvest now, decrypt later” threat model, where adversaries collect encrypted data today for future decryption by capable quantum computers. While NIST has finalized several PQC standards, experts suggest that the expected moment of cryptographic compromise could arrive as early as 2029, making immediate preparation essential. Despite the marketing push, some observers question whether these PQC offerings represent a new category of security tools or simply a necessary enforcement of long-overdue security hygiene, such as comprehensive asset mapping and certificate tracking. Ultimately, the migration to quantum-safe environments requires a phased approach and a commitment to crypto-agility, ensuring that enterprises can adapt to evolving cryptographic standards before legacy systems become insurmountable liabilities in a post-quantum world.

Tech Debt “For Later” Crashed Production 5 Years Later

This Devrim Ozcay’s article critiques the pervasive hype surrounding AI in DevOps, specifically addressing the gap between marketing promises and production realities. The author argues that while "autonomous remediation" and "predictive incident detection" are often touted as revolutionary, they frequently fail in complex, high-stakes environments. These tools often rely on simple logic or pattern matching, and general-purpose models like ChatGPT can be dangerous during active incidents by providing confident but entirely incorrect root cause hypotheses. Instead of relying on AI for critical judgment, the article suggests leveraging it for "assembly" tasks that alleviate the mechanical burden on engineers. This includes filtering log noise, reconstructing incident timelines from disparate sources, and drafting initial postmortem reports. By automating these time-consuming, repetitive processes, teams can reduce the duration of post-incident documentation from hours to minutes. Ultimately, the article advocates for a balanced approach where AI handles the data organization while human engineers retain sole responsibility for interpretation and decision-making. This shift allows practitioners to focus on high-leverage problem-solving rather than tedious transcription, ensuring that incident response remains both efficient and reliable without succumbing to the unrealistic expectations often presented at tech conferences.

What Is Sampling in LLMs and How Does It Relate to Ethics?

This article explores the technical mechanisms behind how AI models choose their words and the subsequent moral responsibilities of developers. Sampling is the process by which an LLM selects the next token from a probability distribution. Techniques such as temperature, Top-K, and Top-P (nucleus sampling) are used to balance creativity with accuracy. Higher temperature settings introduce more randomness, which can foster innovation but also increases the likelihood of "hallucinations" or the generation of biased and harmful content. Conversely, lower settings make the model more deterministic and reliable for factual tasks but can lead to repetitive and uninspired responses. From an ethical standpoint, the choice of sampling strategy is never neutral. It requires a delicate balance between providing a diverse range of perspectives and ensuring the safety and truthfulness of the output. The author emphasizes that organizations must transparently define their sampling parameters to mitigate risks like misinformation. Ultimately, ethical AI development hinges on understanding these technical levers, as they directly influence how a model perceives and interacts with human values, necessitating a cautious approach to model tuning that prioritizes user safety and informational integrity.

AI Won't Fix Cybersecurity, But It Could Rebalance It

The article explores the nuanced role of artificial intelligence in cybersecurity, debunking the myth that it serves as a total panacea while highlighting its potential to rebalance the long-standing asymmetric advantage held by attackers. Traditionally, cybercriminals have enjoyed a lower barrier to entry and a higher success rate because defenders must be perfect across every surface, whereas attackers only need to succeed once. With the advent of generative AI, malicious actors are leveraging the technology to craft sophisticated phishing campaigns, automate vulnerability discovery, and democratize complex malware creation. Conversely, AI empowers defenders by automating routine monitoring, identifying anomalous patterns at machine speed, and bridging the significant talent gap within the industry. This technological shift creates a perpetual arms race where AI functions as a force multiplier for both sides. Rather than eliminating threats, AI recalibrates the battlefield, allowing security teams to process vast datasets and respond to incidents with unprecedented agility. However, the human element remains indispensable; strategic oversight and critical thinking are essential to guide AI tools. Ultimately, while AI will not "fix" the inherent vulnerabilities of digital infrastructure, it offers a vital mechanism to shift the strategic advantage back toward those safeguarding the digital frontier.

AI Is Not Here to Replace People, It’s Here to Replace Waiting

In this insightful interview, Aliaksei Tulia, the Chief Technical Officer at CoinsPaid, argues that the true purpose of artificial intelligence in the financial sector is not to displace human judgment but to eliminate the friction of waiting. Tulia emphasizes that AI acts as a powerful catalyst for efficiency and speed within the digital payment ecosystem by automating repetitive, high-volume tasks that traditionally create operational bottlenecks. By handling routine duties such as document summarization, log scanning, and boilerplate coding, AI allows for a significant compression of cycle times while maintaining necessary human oversight. The article highlights how CoinsPaid integrates these intelligent tools to enhance consistency and visibility, ensuring that the platform remains robust without sacrificing control. Furthermore, the discussion explores the essential division of labor where technology manages data-heavy routine processes, freeing professionals to focus on high-level strategic decisions, complex problem-solving, and improving the overall customer experience. This pragmatic approach represents a shift where AI handles the disciplined "first pass," allowing people to dedicate their expertise to tasks requiring creativity and accountability. Ultimately, Tulia envisions a future where AI-driven automation defines industry standards, proving that the technology’s primary value lies in its ability to streamline operations for a global audience.

Dynamic UI for dynamic AI: Inside the emerging A2UI model

The article "Dynamic UI for Dynamic AI: Inside the Emerging A2UI Model" explores the transformative shift from traditional graphical user interfaces to Agent-to-User Interfaces. As AI agents become increasingly autonomous, the standard chat-based "command line" is no longer sufficient for managing complex workflows. A2UI represents a fundamental paradigm shift where the interface is dynamically generated by the AI to match the specific context and requirements of a task. Unlike static SaaS platforms with fixed menus, A2UI allows agents to create ephemeral, highly functional components—such as interactive charts, data tables, or specialized dashboards—on demand. This movement is powered by advancements like Vercel’s AI SDK and features like Anthropic’s Artifacts, which allow for real-time rendering of code and UI. The goal is to bridge the gap between human intent and machine execution by providing a rich, interactive medium that transcends simple text responses. By embracing generative UI, developers are enabling a more fluid collaboration where the software adapts to the user, rather than the user being forced to navigate rigid software structures. This evolution signals the end of "one-size-fits-all" application design, ushering in a future where every interaction produces a bespoke, temporary interface tailored specifically to the immediate problem.

AI Use at Work Is Causing “Brain Fry,” Researchers Find, Especially Among High Performers

The Futurism article "AI Use at Work Is Causing 'Brain Fry'" highlights a concerning trend where artificial intelligence, despite its promises of productivity, is significantly damaging employee mental health. A study of 1,500 workers conducted by Boston Consulting Group and the University of California, Riverside, introduced the term "AI brain fry" to describe the cognitive exhaustion resulting from excessive interaction with AI tools. Approximately 14 percent of employees—predominantly high performers in fields like software development and finance—reported symptoms such as mental "static," brain fog, and headaches. This fatigue is largely driven by information overload, rapid task-switching, and the constant, draining necessity of overseeing multiple AI agents. Rather than lightening the load, these tools often force users to work harder to manage the technology than to solve actual problems. The consequences are severe for both individuals and organizations; the research found a 33 percent increase in decision fatigue and a higher likelihood of employees quitting their jobs. Ultimately, the piece argues that while AI is marketed as a way to supercharge efficiency, it often acts as a "burnout machine" that compromises cognitive capacity and leads to costly errors or paralysis in professional environments.

Submarine cables move to the center of critical infrastructure security debate

The article examines the escalating strategic significance of submarine cables, which facilitate the vast majority of international data traffic but are increasingly vulnerable to geopolitical tensions and physical threats. A new sector report highlights how high-profile incidents, such as the 2024 Baltic Sea cable severing, have transitioned these underwater assets from ignored infrastructure into critical security priorities. Beyond intentional sabotage or "grey-zone" activities, the industry faces significant resilience challenges, including an annual average of two hundred cable faults primarily caused by commercial fishing and anchoring. This vulnerability is exacerbated by a critical shortage of specialized repair vessels and experienced personnel, complicating rapid incident response. Furthermore, the shift in ownership dynamics, where cloud hyperscalers are now primary investors, creates commercial friction with traditional operators while reshaping infrastructure architecture. Technological advancements, particularly AI-driven distributed acoustic sensing, are transforming cables into active monitoring tools, yet technical solutions alone remain insufficient. The report concludes that long-term security depends on improved international coordination and unified governance frameworks between governments and private entities. Ultimately, protecting these vital conduits requires a holistic approach that integrates technical controls, organizational readiness, and cross-border cooperation to match the scale of modern digital dependency and evolving global risks.

How DevOps Broke Accessibility

In this article on DevOps Digest, the author explores the unintended consequences that the rapid adoption of DevOps practices has had on web accessibility. While DevOps has revolutionized software development by emphasizing speed, continuous integration, and frequent deployments, these very priorities have often sidelined the inclusive design and rigorous accessibility testing required for users with disabilities. The shift-left mentality, which aims to catch bugs early, frequently fails to incorporate accessibility checks into the automated pipeline, leading to a "move fast and break things" culture that disproportionately affects those relying on assistive technologies. Furthermore, the reliance on automated testing tools—which can only detect about 30% of accessibility issues—creates a false sense of security among development teams. This technical debt accumulates quickly in fast-paced environments, making retroactive fixes costly and complex. The article argues that for DevOps to truly succeed, accessibility must be integrated as a core pillar of the development lifecycle, rather than being treated as an afterthought. Ultimately, the piece calls for a cultural shift where developers and stakeholders prioritize human-centric design alongside technical efficiency to ensure the digital world remains open and equitable for every user regardless of their physical or cognitive abilities.

Daily Tech Digest - February 18, 2026

Quote for the day:

"Engagement is a leadership responsibility—never the employee’s, and not HR’s." -- Gordon Tredgold

Why cloud outages are becoming normal

As the headlines become more frequent and the incidents themselves start to blur together, we have to ask: Why are these outages becoming a monthly, sometimes even weekly, story? What’s changed in the world of cloud computing to usher in this new era of instability? In my view, several trends are converging to make these outages not only more common but also more disruptive and more challenging to prevent. ... The predictable outcome is that when experienced engineers and architects leave, they are often replaced by less-skilled staff who lack deep institutional knowledge. They lack adequate experience in platform operations, troubleshooting, and crisis response. While capable, these “B Team” employees may not have the skills or knowledge to anticipate how minor changes affect massive, interconnected systems like . ... Another trend amplifying the impact of these outages is the relative complacency about resilience. For years, organizations have been content to “” workloads to the cloud, reaping the benefits of agility and scalability without necessarily investing in the levels of redundancy and disaster recovery that such migrations require. There is growing cultural acceptance among enterprises that cloud outages are unavoidable and that mitigating their effects should be left to providers. This is both an unrealistic expectation and a dangerous abdication of responsibility.

AI agents are changing entire roles, not just task augmentation

Task augmentation was about improving individual tasks within an existing process. Think of a source-to-pay process in which specific steps are automated. That is relatively easy to visualize and implement in a classic process landscape. Role transformation, however, requires a completely different approach. You have to turn your entire end-to-end business process architecture into a role-based architecture, explains Mueller. ... Think of an agent that links past incidents to existing problems. Or an agent that automatically checks licenses and certifications for all running systems. “I wonder why everyone isn’t already doing this,” says Mueller. In the event of an incident with a known problem, the agent can intervene immediately without human intervention. That’s an autonomous circle. For more complex tasks, you can start in supervised mode and later transition to autonomous mode. ... The real challenge is that companies are so far behind in their capabilities to handle the latest technology. Many cannot even visualize what AI means. The executive has a simple recommendation: “If you had to build it from scratch on greenfield, would you do it the same way you do now?” That question gets to the heart of the matter. “Everyone looks at the auto industry and sees that it is being disrupted by Chinese companies. This is because Chinese companies can do things much faster than old economies,” Mueller notes.

Why are AI leaders fleeing?

Normally, when big-name talent leaves Silicon Valley giants, the PR language is vanilla: they’re headed for a “new chapter” or “grateful for the journey” — or maybe there’s some vague hints about a stealth startup. In the world of AI, though, recent exits read more like a whistleblower warnings. ... Each individual story is different, but I see a thread here. The AI people who were concerned about “what should we build and how to do it safely?” are leaving. They’ll be replaced by people whose first, if not only, priority is “how fast can we turn this into a profitable business?” Oh, and not just profitable; not even a unicorn with a valuation of $1 billion is enough for these people. If the business isn’t a “,” a privately held startup company valued at more than $10 billion, they don’t want to hear about it. I think it’s very telling that Peter Steinberger, the creator of the insanely — in every sense of the word — hot , has already been hired by OpenAI. Altman calls him a “genius” and says his ideas “will quickly become core to our product offerings.” Actually, OpenClaw is a security disaster waiting to happen. Someday soon, some foolhardy people or companies will lose their shirts because they trusted valuable information with it. And, its inventor is who Altman wants at the heart of OpenAI!? Gartner needs to redo its hype cycle. With AI, we’re past the “Peak of Inflated Expectations” and charging toward the “Pinnacle of Hysterical Financial Fantasies.”

Poland Energy Survives Attack on Wind, Solar Infrastructure

The attack on Poland's energy sector late last year might have failed, but it's also the first large-scale attack against decentralized energy resources (DERs) like wind turbines and solar farms. ... The attacks were destructive by nature and "occurred during a period when Poland was struggling with low temperatures and snowstorms just before the New Year." ... Dragos said that over the past year, Electrum has worked alongside another threat actor, tracked as Kamicite, to conduct destructive attacks against Ukrainian ISPs and persistent scanning of industrial devices in the US. Kamicite gained initial access and persistence against organizations, and Electrum executed follow-on activity. Dragos has tracked Kamicite activities against the European ICS/OT supply chain since late 2024. "Electrum remains one of the most aggressive and capable OT/ICS-adjacent threat actors in the world," Dragos said. "Even when targeting IT infrastructure, Electrum's destructive malware often affects organizations that provide critical operational services, telecommunications, logistics, and infrastructure support, blurring the traditional boundary between IT and OT. Kamacite's continuous reconnaissance and access development directly enable Electrum's destructive operations. These activities are neither theoretical nor preparatory, they are part of active campaigns culminating in real-world outages, data destruction, and coordinated destabilization campaigns."

Why SaaS cost optimization is an operating model problem, not a budget exercise

When CIOs ask why SaaS costs spiral, the answer is rarely “poor discipline.” It’s usually structural. ... In the engagement I described, had accumulated over years for understandable reasons: Business units bought tools to move faster; IT teams enabled experimentation during growth phases; Mergers brought duplicate platforms; and Pandemic-era urgency favored speed over standardization. No one made a single bad decision. Hundreds of reasonable decisions added up to an unreasonable outcome. ... During a review session, I asked a simple question about one of the highest-cost platforms: “Who owns this product?” The room went quiet. IT assumed the business owned it. The business assumed IT managed it. Procurement negotiated the contract. Security reviewed access annually. No one was accountable for adoption, value realization or lifecycle decisions. This lack of accountability wasn’t unique to that tool — it was systemic. Best-practice guidance on SaaS governance consistently emphasizes the importance of assigning a clearly named owner for every application, accountable for cost, security, compliance and ongoing value. Without that ownership, redundancy and unmanaged spend tend to persist across portfolios. ... CIOs focus on licenses and contracts, but the real issue is the absence of a product mindset. SaaS platforms behave like products, but many organizations manage them like utilities.

Finding a common language around risk

The CISO warns about ransomware threats. Operations worries about supply chain breakdowns. The board obsesses over market disruption. They’re all talking about risk, but they might as well be on different planets. When the crisis hits (and it always does), everyone scrambles in their own direction while the place burns down. ... The Organizational Risk Culture Standard (ORCS) offers something most frameworks miss: it treats culture as the foundation, not the afterthought. You can’t bolt culture onto existing processes and call it done. Culture is how people actually think about risk when no one is watching. It’s the shared beliefs that guide decisions under pressure. Think of it as a dynamic system in which people, processes and technology must dance together. People are the operators who judge and act on risks. Processes provide standards, so they don’t have to improvise in a crisis. Technology provides tools to detect patterns, monitor threats and respond faster than human reflexes. But here’s the catch: these three elements have to align across all three risk domains. Your cybersecurity team needs to understand how their decisions affect operations. Your operations team needs to grasp strategic implications. ... The ORCS standard provides a maturity model with five levels. Most organizations start at Level 1, where risk management is reactive and fragmented. People improvise. Policies exist on paper, but nobody follows them. Crises catch everyone off guard.

Harnessing curated threat intelligence to strengthen cybersecurity

Improving one’s cybersecurity posture with up-to-date threat intelligence is a foundational element of any modern security stack. This enables automated blocking of known threats and reduces the workload on security teams while keeping the network protected. Curated threat intelligence also plays a broader role across cybersecurity strategies, like blocking malicious IP addresses from accessing the network to support intrusion prevention and defend against distributed denial-of-service (DDoS) attacks. ... Organizations overwhelmed by massive amounts of cybersecurity data can gain clarity and control with curated threat intelligence. By validating, enriching and verifying the data, curated intelligence dramatically reduces false positives and noise, enabling security teams to focus on the most relevant and credible threats. Improved accuracy and certainty accelerates time-to-knowledge, sharpens prioritization based on threat severity and potential impact, and ensures resources are applied and deployed where they matter most. With higher confidence and certainty, teams can respond to incidents faster and more decisively, while also shifting from reactive to proactive and ultimately preventative – using known adversary indicators and patterns to investigate threats, strengthen controls, and stop attacks before they cause damage. Curated threat Intelligence transforms one’s cybersecurity from reactive to resilient.

Password managers’ promise that they can’t see your vaults isn’t always true

All eight of the top password managers have adopted the term “” to describe the complex encryption system they use to protect the data vaults that users store on their servers. The definitions vary slightly from vendor to vendor, but they generally boil down to one bold assurance: that there is no way for malicious insiders or hackers who manage to compromise the cloud infrastructure to steal vaults or data stored in them. ... New research shows that these claims aren’t true in all cases, particularly when account recovery is in place or password managers are set to share vaults or organize users into groups. The researchers reverse-engineered or closely analyzed Bitwarden, Dashlane, and LastPass and identified ways that someone with control over the server—either administrative or the result of a compromise—can, in fact, steal data and, in some cases, entire vaults. The researchers also devised other attacks that can weaken the encryption to the point that ciphertext can be converted to plaintext. ... Three of the attacks—one against Bitwarden and two against LastPass—target what the researchers call “item-level encryption” or “.” Instead of encrypting a vault in a single, monolithic blob, password managers often encrypt individual items, and sometimes individual fields within an item. These items and fields are all encrypted with the same key.

Poor documentation risks an AI nightmare for developers

Poor documentation not only slows down development and makes bug fixing difficult, but its effects can multiply. Misunderstandings can propagate through codebases, creating issues that can take a long time to fix. The use of AI accelerates this problem. AI coding assistants rely on documentation to understand how software should be used. Without AI, there is the option of institutional knowledge, or even simply asking the developer behind the code. AI doesn’t have this choice and will confidently fill in the gaps where no documentation exists. We’re familiar with – and developers will be checking for these kinds of errors – but a lack of documentation will likely cause an AI to simply take a stab in the dark. ... Developers need to write documentation around complete workflows: the full path from local development to production deployment, including failures and edge cases. It can be tricky to spot errors in your own work, so AI can be used to help here, following the documentation end-to-end and observing where confusion and errors appear. AI can also be used to draft documentation and generally does a pretty good job of putting together documentation when presented with code. ... Document development should be an ongoing process – just as software is patched and updated, so should the documentation. Questions that come in from support tickets and community forums – especially repeat problems – can be used to highlight issues in documentation, particularly those caused by assumed knowledge.

Branding Beyond the Breach: How Cybersecurity Companies Can Lead with Trust, Not Fear

The almost constant stream of cyberattack headlines in the news only highlights the importance for cybersecurity companies to ensure their messaging is creating trust and confidence for B2B businesses. ... It is easy to take issues such as AI- powered attacks and and create fear-based messaging in hopes of capturing attention. However, when cybersecurity companies endlessly recycle breach risks as reasons to do business, it can overload prospective clients with the dangers and cause them to disengage. It also minimises cybersecurity services down to being solely reactive, rather than proactive and preventative. By following fear-based messaging, cybersecurity companies are blending in, not standing out. ... To navigate the complexities of cybersecurity, B2B businesses need a partner to guide them, not just sell to them. By including thought-leadership, education initiatives, consultation services, partnerships and customised strategies into a cybersecurity company’s messaging and offering, it highlights their authenticity, credibility and reliability. ... The cybersecurity landscape is wide and complex, and the market will only continue to diversify as threats evolve. Cybersecurity organisations need messaging that shows they can support businesses to expand in new sectors, communicate complex offerings clearly and become the optimal solution for risk-conscious enterprises.