Daily Tech Digest by Kannan Subbiah: product management

Showing posts with label product management. Show all posts

Daily Tech Digest - May 17, 2026

Quote for the day:

“In tech, leadership isn’t about predicting the future — it’s about creating the conditions where your teams can build it.” -- Unknown

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Scale ‘autonomous intelligence’ for real growth

In an interview with Ryan Daws, Prakul Sharma, the AI and Insights Practice Leader at Deloitte Consulting LLP, explains that modern enterprises must look beyond the localized productivity gains of generative AI to scale "autonomous intelligence" for real business growth. Sharma describes an intelligence maturity curve transitioning from assisted and artificial intelligence into autonomous intelligence, where systems independently execute actions within predefined boundaries. To unlock true economic value, organizations must integrate these autonomous agents directly into critical, costly workflows like enterprise procurement. However, scaling successfully faces significant technical and structural hurdles. First, enterprises frequently lack decision-grade data, which means real-time, traceable information required for binding transactions, relying instead on outdated reporting-grade data. Second, the production gap and governance debt often stall live deployments, because shortcuts taken during small pilots become major barriers for corporate legal and compliance teams. Sharma advises leaders to conduct thorough decision audits of existing workflows to uncover operational bottlenecks and data gaps. By building pilots from the very outset as reusable platforms equipped with proper identity verification, continuous model evaluations, and robust risk frameworks, enterprises can securely transition from experimental testing to successful, widespread live deployment.

6 Technical Red Flags Product Managers Should Never Ignore

In the article "6 Technical Red Flags Product Managers Should Never Ignore," Seyifunmi Olafioye emphasizes that product managers must recognize signs of underlying technical instability, as it directly impacts delivery, scalability, and customer trust. The author identifies six major red flags that product managers should never overlook: a lack of clear understanding among the team regarding how the system works, new feature development consistently taking much longer than estimated, and resolved bugs repeatedly resurfacing in production. Additionally, product managers should be concerned if operational teams must rely heavily on manual workarounds to keep the platform functioning, if the entire project suffers from an over-reliance on a single engineer's institutional knowledge, or if internal errors are only discovered after users report them due to a lack of proper monitoring. While no system is entirely flawless, ignoring these persistent warning signs can lead to severe operational issues. The article concludes that product managers should not dictate technical fixes; instead, they must proactively initiate honest conversations with engineering leadership, ask challenging questions during planning, and prioritize long-term technical health alongside new features to ensure sustainable growth and protect the user experience.

Is Q-Day Worse Than Y2K? Why Vaulted Encryption Matters In The Quantum Era

In this article, Ed Leavens argues that Quantum Day, known as Q-Day, is the precise moment when quantum computers become advanced enough to break existing asymmetric encryption standards like RSA and ECC, presenting a far greater threat than Y2K. While Y2K had a definitive deadline and a known remedy, Q-Day has no set timeline and introduces the insidious risk of "harvest now, decrypt later" (HNDL) tactics. Under HNDL, adversaries secretly exfiltrate and stockpile encrypted data today, waiting to decrypt it once sufficiently powerful quantum technology becomes available. Furthermore, this threat compounds daily due to modern data sprawl across multiple environments. To counter this impending crisis, organizations must look beyond traditional encryption upgrades and adopt data-layer protection strategies like vaulted tokenization. This quantum-resilient approach mathematically separates original sensitive data from its representation by replacing it with non-sensitive, format-preserving tokens. Because tokens share no reversible mathematical connection with the underlying information, quantum algorithms cannot decipher them, effectively neutralizing the value of stolen payloads. Implementing vaulted tokenization requires comprehensive data discovery, strict access governance, and cross-functional organizational alignment. Ultimately, Leavens emphasizes that enterprises must act immediately to secure their data directly, rendering harvested information useless before quantum-powered breaches materialize.

The AI infrastructure bottleneck is becoming a CIO problem

The article by Madeleine Streets explores how the expanding ambitions of artificial intelligence are colliding with physical infrastructure limitations, shifting the AI bottleneck from a general tech industry challenge into a critical problem for Chief Information Officers (CIOs). While billions of dollars continue pouring into AI development, physical realities like power grid limitations, data center construction delays, permitting hurdles, and cooling requirements are struggling to match software demand. This mismatch threatens to create a more constrained operating environment where AI access becomes expensive, delayed, or regionally uneven. Consequently, this pressure exposes "AI sprawl" within organizations where uncoordinated and disconnected AI initiatives compete for the same resources without centralized governance. To mitigate these risks, experts suggest that CIOs treat AI capacity as a core operational resilience and business continuity issue. IT leaders must introduce disciplined governance by tiering AI workloads into critical, important, and experimental categories, or utilizing smaller, local models to reduce compute reliance. Furthermore, CIOs must demand greater transparency from vendors regarding capacity guarantees, regional availability, and workload prioritization during peak demand. Ultimately, enterprise AI strategies can no longer assume infinite compute availability and must instead realign their deployment ambitions with physical operational constraints.

How AI Is Repeating Familiar Shadow IT Security Risks

The rapid adoption of artificial intelligence across the corporate enterprise is triggering new governance and security risks that closely mirror past technological shifts, such as the initial emergence of shadow IT and unauthorized software as a service platform usage. Modern organizations currently face three primary vectors of vulnerability, starting with employees inadvertently leaking proprietary intellectual property, corporate source code, and confidential financial records by pasting this data into public generative AI platforms. Furthermore, software developers frequently introduce hidden backdoors or compromised dependencies into production systems by integrating unverified open source models and components that circumvent traditional software supply chain scrutiny. Compounding these operational issues is the sudden rise of autonomous AI agents that operate with dynamic decision making authority but completely lack explicitly defined ownership or documented permission boundaries within internal corporate networks. To successfully mitigate these vulnerabilities, blanket restrictive policies are typically ineffective; instead, companies must establish robust frameworks that ensure absolute visibility, accountability, and adaptive identity controls. As detailed in the SANS Institute’s new AI Security Maturity Model, managing these continuous threats requires treating artificial intelligence not as an isolated software application, but as a critical operational layer demanding proactive lifecycle validation and verification.

Six priorities reshaping the MENA boardroom in 2026

The EY report details how the 2026 macroeconomic landscape in the Middle East and North Africa (MENA) region requires corporate boardrooms to transition from traditional, periodic oversight toward integrated, forward-looking strategic leadership. Driven by overlapping pressures across geopolitics, rapid technological innovation, sustainability demands, and complex governance regulations, MENA boards face a highly volatile operating environment. To navigate this uncertainty and secure long-term value, directors must actively address six central boardroom priorities. First, boards need to develop geopolitical foresight, embedding regional shifts directly into strategic scenario planning. Second, they must manage the expanding technology and cyber assurance landscape, ensuring ethical artificial intelligence governance and robust defenses against escalating digital threats. Third, strengthening corporate integrity, fraud prevention, and independent investigation oversight remains essential for maintaining stakeholder trust. Fourth, elevating climate resilience and sustainability governance helps mitigate critical environmental risks while driving resource efficiency. Fifth, achieving financial excellence requires rigorous cost optimization and aligning internal controls across financial and sustainability reporting frameworks. Finally, adopting mature, behavioral-based board evaluations over mere procedural assessments fosters deep accountability. Ultimately, orchestrating these interconnected priorities empowers MENA leaders to fortify institutional trust and transform market disruptions into sustainable growth.

The software supply chain is the new ground zero for enterprise cyber risk. Don’t get caught short

In this article, Matias Madou highlights the rising vulnerabilities within the software supply chain as the new ground zero for enterprise cyber risks, heavily exacerbated by the rapid adoption of artificial intelligence tools. Recent highly sophisticated breaches, such as the TeamPCP supply chain attacks, have aggressively weaponized critical security and developer platforms like Checkmarx and the open-source library LiteLLM. By embedding highly obfuscated, multistage credential stealers into these trusted systems, attackers successfully moved laterally through development pipelines and Kubernetes clusters to exfiltrate highly sensitive enterprise data. Madou warns that traditional, reactive security measures are entirely insufficient against fast-moving, AI-driven threats. To mitigate these expanding dangers, organizations must redefine AI middleware as critical infrastructure, implementing rigorous monitoring of application programming interface keys and environment variables that constantly flow through these abstraction layers. Furthermore, security leaders must modernize risk management strategies by locking down dependency pipelines, enforcing strict least-privilege access, and gaining visibility into autonomous Model Context Protocol agents. Ultimately, the author urges modern enterprises to establish comprehensive internal AI governance frameworks and continuously upskill developers in secure coding standards rather than waiting for formal government legislation, thereby proactively shielding their operational workflows from devastating, cascading supply-chain compromises.

World Bank, African DPAs outline formula for trusted digital identity, DPI

During the ID4Africa 2026 Annual General Meeting, a key World Bank presentation emphasized that establishing public trust is vital for the success of digital public infrastructure and national identity systems across Africa. Experts noted that even mature digital identity networks remain vulnerable to operational failures and public mistrust due to weak data collection safeguards, frequent data breaches, and expanding cyberattack surfaces. To address these vulnerabilities, data protection authorities from nations like Liberia, Benin, and Mauritius highlighted that digital forensics, cybersecurity, and rigorous data governance must operate collectively. Although these under-resourced regulatory bodies often struggle to fund large population-scale awareness campaigns, they are pioneering localized solutions. For example, Mauritius leverages chief data officers and amicable dispute resolution mechanisms to efficiently settle compliance breaches without lengthy prosecution, while Benin relies on specialized government liaisons to ensure proper database compliance across different agencies. Furthermore, regional frameworks like the East African Community body facilitate international knowledge-sharing and joint investigative capabilities. Ultimately, achieving an ecosystem worthy of citizen and business trust requires a comprehensive formula blending careful system architecture, strictly enforced data protection, robust cybersecurity defenses, and transparent communication that effectively helps citizens understand their rights within the broader data lifecycle.

When configuration becomes a vulnerability: Exploitable misconfigurations in AI apps

The rapid deployment of artificial intelligence and agentic applications on cloud-native platforms, particularly Kubernetes clusters, often compromises cybersecurity in favor of operational speed. According to the Microsoft Defender Security Research Team, this trend has led to an increase in exploitable misconfigurations, which are scenarios where public internet access is paired with absent or weak authentication mechanisms. Rather than relying on sophisticated zero-day vulnerabilities, threat actors can leverage these low-effort attack paths to achieve high-impact compromises, including remote code execution, credential exfiltration, and unauthorized access to sensitive internal data. Microsoft identified these specific dangers across several popular AI platforms: Model Context Protocol servers frequently permitted unauthenticated interaction with corporate tools, Mage AI default setups enabled internet-accessible administrative shells, and frameworks like kagent and AutoGen Studio leaked plaintext API keys or allowed unauthorized workload deployments. To mitigate these pervasive security gaps, organizations must treat AI systems as high-impact workloads. Security teams should enforce strong authentication across all endpoints, apply strict least-privilege principles, and continuously audit infrastructure configurations. Furthermore, cloud protection tools like Microsoft Defender for Cloud can actively detect exposed services, helping defenders remediate dangerous oversights before malicious adversaries can exploit them.

Tokenized assets face trust infrastructure test, Cardano chief says

The article, titled "Tokenized assets face trust infrastructure test, Cardano chief says," by Jeff Pao, outlines a pivotal shift in the digital assets sector as financial institutions transition from tentative pilot projects to scaled, production-level tokenization. According to Cardano’s leadership, the primary challenges facing this widespread adoption are no longer the core blockchain mechanisms themselves, but rather the underlying hurdles of verification, identity, and robust auditability. These elements form a critical "trust infrastructure" that remains essential for creating compliant, institutional-grade financial networks. As real-world asset tokenization expands rapidly across global markets, traditional financial institutions require secure mechanisms like decentralized identifiers and privacy-preserving verifiable credentials to interact safely with public ledgers. By embedding accountability directly into the network architecture, digital trust frameworks turn complex compliance into seamless operational coordination, enabling institutions to efficiently manage counterparty exposure and automated settlement risks without exposing sensitive transactional data. Ultimately, the piece underscores that the long-term survival of decentralized finance relies heavily on resolving these identity and legal infrastructure gaps. Establishing a standardized trust layer will determine whether tokenized finance achieves mature stability or succumbs to institutional fragility and unresolved regulatory friction, marking a major turning point for future global capital flows.

Daily Tech Digest - August 16, 2025

Quote for the day:

"Develop success from failures. Discouragement and failure are two of the surest stepping stones to success." -- Dale Carnegie

Digital Debt Is the New Technical Debt (And It’s Worse)

Digital debt doesn’t just slow down technology. It slows down business decision-making and strategic execution. Decision-Making Friction: Simple business questions require data from multiple systems. “What’s our customer lifetime value?” becomes a three-week research project because customer data lives in six different platforms with inconsistent definitions. Campaign Launch Complexity: Marketing campaigns that should take two weeks to launch require six weeks of coordination across platforms. Not because the campaign is complex, but because the digital infrastructure is fragmented. Customer Experience Inconsistency: Customers encounter different branding, messaging, and functionality depending on which digital touchpoint they use. Support teams can’t access complete customer histories because data is distributed across systems. Innovation Paralysis: New initiatives get delayed because teams spend time coordinating existing systems rather than building new capabilities. Digital debt creates a gravitational pull that keeps organizations focused on maintenance rather than innovation. ... Digital debt is more dangerous than technical debt because it’s harder to see and affects more stakeholders. Technical debt slows down development teams. Digital debt slows down entire organizations.

Rising OT threats put critical infrastructure at risk

Attackers are exploiting a critical remote code execution (RCE) vulnerability in the Erlang programming language's Open Telecom Platform, widely used in OT networks and critical infrastructure. The flaw enables unauthenticated users to execute commands through SSH connection protocol messages that should be processed only after authentication. Researchers from Palo Alto Networks' Unit 42 said they have observed more than 3,300 exploitation attempts since May 1, with about 70% targeting OT networks across healthcare, agriculture, media and high-tech sectors. Experts urged affected organizations to patch immediately, calling it a top priority for any security team defending an OT network. The flaw, which has a CVSS score of 10, could enable an attacker to gain full control over a system and disrupt connected systems -- particularly worrisome in critical infrastructure. ... Despite its complex cryptography, the protocol contains design flaws that could enable attackers to bypass authentication and exploit outdated encryption standards. Researcher Tom Tervoort, a security specialist at Netherlands-based security company Secura, identified issues affecting at least seven different products, resulting in the issuing of three CVEs.

Why Tech Debt is Eating Your ROI (and How To Fix It)

Regardless of industry or specific AI efforts, these frustrations seem to boil down to the same culprit. Their AI initiatives continue to stumble over decades of accumulated tech debt. Part of the reason is despite the hype, most organizations use AI — let’s say, timidly. Fewer than half employ it for predictive maintenance or detecting network anomalies. Fewer than a third use it for root-cause analysis or intelligent ticket routing. Why such hesitation? Because implementing AI effectively means confronting all the messiness that came before. It means admitting our tech environments need a serious cleanup before adding another layer of complexity. Tech complexity has become a monster. This mess came from years of bolting on new systems without retiring old ones. Some IT professionals point to redundant applications as a major source of wasted budget and others blame overprovisioning in the cloud — the digital equivalent of paying rent on empty apartments. ... IT teams admit something that, to me, is alarming: Their infrastructure has grown so tangled they can no longer maintain basic security practices. Let that sink in. Companies with eight-figure tech budgets can’t reliably patch vulnerable systems or implement fundamental security controls. No one builds silos deliberately. Silos emerge from organizational boundaries, competing priorities and the way we fund and manage projects.

Ready on paper, not in practice: The incident response gap in Australian organisations

The truth is, security teams often build their plans around assumptions rather than real-world threats and trends. That gap becomes painfully obvious during an actual incident, when organisations realise they aren't adequately prepared to respond. Recent findings of a Semperis study titled The State of Enterprise Cyber Crisis Readiness revealed a strong disconnect between organisations' perceived readiness to respond to a cyber crisis and their actual performance. The study also showed that cyber incident response plans are being implemented and regularly tested, but not broadly. In a real-world crisis, too many teams are still operating in silos. ... A robust, integrated, and well-practiced cyber crisis response plan is paramount for cyber and business resilience. After all, the faster you can respond and recover, the less severe the financial impact of a cyberattack will be. Organisations can increase their agility by conducting tabletop exercises that simulate attacks. By practicing incident response regularly and introducing a range of new scenarios of varying complexity, organisations can train for the real thing, which can often be unpredictable. Security teams can continually adapt their response plans based on the lessons learned during these exercises, and any new emerging cyber threats.

Quantum Threat Is Real: Act Now with Post Quantum Cryptography

Some of the common types of encryption we use today include RSA (Rivest-Shamir-Adleman), ECC (Elliptic Curve Cryptography), and DH (Diffie-Hellman Key Exchange). The first two are asymmetric types of encryption. The third is a useful fillip to the first to establish secure communication, with secure key exchange. RSA relies on very large integers, and ECC, on very hard-to-solve math problems. As can be imagined, these cannot be solved with traditional computing. ... Cybercriminals think long-term. They are well aware that quantum computing is still some time away. But that doesn’t stop them from stealing encrypted information. Why? They will store it securely until quantum computing becomes readily available; then they will decrypt it. The impending arrival of quantum computers has set the cat amongst the pigeons. ... Blockchain is not unhackable, but it is difficult to hack. A bunch of cryptographic algorithms keep it secure. These include SHA-256 (Secure Hash Algorithm 256-bit) and ECDSA (Elliptic Curve Digital Signature Algorithm). Today, cybercriminals might not attempt to target blockchains and steal crypto. But tomorrow, with the availability of a quantum computer, the crypto vault can be broken into, without trouble. ... We keep saying that quantum computing and quantum computing-enabled threats are still some time away. And, this is true. But when the technology is here, it will evolve and gain traction.

Cultivating product thinking in your engineering team

The most common trap you’ll encounter is what’s called the “feature factory.” This is a development model where engineers are simply handed a list of features to build, without context. They’re measured on velocity and output, not on the value their work creates. This can be comfortable for some – it’s a clear path with measurable metrics – but it’s also a surefire way to kill innovation and engagement. ... First and foremost, you need to provide context, and you need to do so early and often. Don’t just hand a Jira ticket to an engineer. Before a sprint starts, take the time to walk through the “what,” the “why,” and the “who.” Explain the market research that led to this feature request, share customer feedback that highlights the problem, and introduce them to the personas you’re building for. A quick 15-minute session at the start of a sprint can make a world of difference. You should also give engineers a seat at the table. Invite them to meetings where product managers are discussing strategy and customer feedback. They don’t just need to hear the final decision; they need to be a part of the conversation that leads to it. When an engineer hears a customer’s frustration firsthand, they gain a level of empathy that a written user story can never provide. They’ll also bring a unique perspective to the table, challenging assumptions and offering technical solutions you may not have considered.

Adapting to New Cloud Security Challenges

While the essence of Non-Human Identities and their secret management is acknowledged, many organizations still grapple with the efficient implementation of these practices. Some stumble upon the over-reliance on traditional security measures, thereby failing to adopt newer, more effective strategies that incorporate NHI management. Others struggle with time and resource constraints, devoid of efficient automation mechanisms – a crucial aspect for proficient NHI management. The disconnect between security and R&D teams often results in fractured efforts, leading to potential security gaps, breaches, and data leaks. ... With more organizations migrate to the cloud and with the rise of machine identities and secret management, the future of cloud security has been redefined. It is no longer solely about the protection from known threats but now involves proactive strategies to anticipate and mitigate potential future risks. This shift necessitates organizations to rethink their approach to cybersecurity, with a keen focus on NHIs and Secrets Security Management. It requires an integrated endeavor, involving CISOs, cybersecurity professionals, and R&D teams, along with the use of scalable and innovative platforms. Thought leaders in the data field continue to emphasize the importance of robust NHI management as vital to the future of cybersecurity, driving the message home for businesses of all sizes and across all industries.

Why IT Modernization Occurs at the Intersection of People and Data

A mandate for IT modernization doesn’t always mean the team has the complete expertise necessary to complete that mandate. It may take some time to arm the team with the correct knowledge to support modernization. Let’s take data analytics, for example. Many modern data analytics solutions, armed with AI, now allow teams to deliver natural language prompts that can retrieve the data necessary to inform strategic modernization initiatives without having to write expert-level SQL. While this lessens the need for writing scripts, IT leaders must still ensure their teams have the right expertise to construct the correct prompts. This could mean training on correct terms for presenting data and/or manipulating data, along with knowing in what circumstances to access that data. Having a well-informed and educated team will be especially important after modernization efforts are underway. ... One of the most important steps to IT modernization is arming your IT teams with a complete picture of the current IT infrastructure. It’s equivalent to giving them a full map before embarking on their modernization journey. In many situations, an ideal starting point is to ensure that any documentation, ER diagrams, and architectural diagrams are collected into a single repository and reviewed. Then, the IT teams use an observability solution that integrates with every part of the enterprise infrastructure to show each team how every part of it works together.

Cyber Resilience Must Become The Third Pillar Of Security Strategy

For years, enterprise security has been built around two main pillars: prevention and detection. Firewalls, endpoint protection, and intrusion detection systems all aim to stop attackers before they do damage. But as threats grow more sophisticated, it’s clear that this isn’t enough. ... The shift to cloud computing has created dangerous assumptions. Many organizations believe that moving workloads to AWS, Azure, or Google Cloud means the provider “takes care of security.” ... Effective resilience starts with rethinking backup as more than a compliance checkbox. Immutable, air-gapped copies prevent attackers from tampering with recovery points. Built-in threat detection can spot ransomware or other malicious activity before it spreads. But technology alone isn’t enough. Mariappan urges leaders to identify the “minimum viable business” — the essential applications, accounts, and configurations required to function after an incident. Recovery strategies should be built around restoring these first to reduce downtime and financial impact. She also stresses the importance of limiting the blast radius. In a cloud context, that might mean segmenting workloads, isolating credentials, or designing architectures that prevent a single compromised account from jeopardizing an entire environment.

Breaking Systems to Build Better Ones: How AI is Reshaping Chaos Engineering

While AI dominates technical discussions across industries, Andrus maintains a pragmatic perspective on its role in system reliability. “If Skynet comes about tomorrow, it’s going to fail in three days. So I’m not worried about the AI apocalypse, because AI isn’t going to be able to build and maintain and run reliable systems.” The fundamental challenge lies in the nature of distributed systems versus AI capabilities. “A lot of the LLMs and a lot of what we talk about in the AI world is really non deterministic, and when we’re talking about distributed systems, we care about it working correctly every time, not just most of the time.” However, Andrus sees valuable applications for AI in specific areas. AI excels at providing suggestions and guidance rather than making deterministic decisions. ... Despite its name, chaos engineering represents the opposite of chaotic approaches to system reliability. “Chaos engineering is a bit of a misnomer. You know, a lot of people think, Oh, we’re going to go cause chaos and see what happens, and it’s the opposite. We want to engineer the chaos out of our systems.” This systematic approach to understanding system behavior under stress provides the foundation for building more resilient infrastructure. As AI-generated code increases system complexity, the need for comprehensive reliability testing becomes even more critical.

Daily Tech Digest - July 27, 2025

Quote for the day:

"The only way to do great work is to love what you do." -- Steve Jobs

Amazon AI coding agent hacked to inject data wiping commands

The hacker gained access to Amazon’s repository after submitting a pull request from a random account, likely due to workflow misconfiguration or inadequate permission management by the project maintainers. ... On July 23, Amazon received reports from security researchers that something was wrong with the extension and the company started to investigate. Next day, AWS released a clean version, Q 1.85.0, which removed the unapproved code. “AWS is aware of and has addressed an issue in the Amazon Q Developer Extension for Visual Studio Code (VSC). Security researchers reported a potential for unapproved code modification,” reads the security bulletin. “AWS Security subsequently identified a code commit through a deeper forensic analysis in the open-source VSC extension that targeted Q Developer CLI command execution.” “After which, we immediately revoked and replaced the credentials, removed the unapproved code from the codebase, and subsequently released Amazon Q Developer Extension version 1.85.0 to the marketplace.” AWS assured users that there was no risk from the previous release because the malicious code was incorrectly formatted and wouldn’t run on their environments.

How to migrate enterprise databases and data to the cloud

Migrating data is only part of the challenge; database structures, stored procedures, triggers and other code must also be moved. In this part of the process, IT leaders must identify and select migration tools that address the specific needs of the enterprise, especially if they’re moving between different database technologies (heterogeneous migration). Some things they’ll need to consider are: compatibility, transformation requirements and the ability to automate repetitive tasks. ... During migration, especially for large or critical systems, IT leaders should keep their on-premises and cloud databases synchronized to avoid downtime and data loss. To help facilitate this, select synchronization tools that can handle the data change rates and business requirements. And be sure to test these tools in advance: High rates of change or complex data relationships can overwhelm some solutions, making parallel runs or phased cutovers unfeasible. ... Testing is a safety net. IT leaders should develop comprehensive test plans that cover not just technical functionality, but also performance, data integrity and user acceptance. Leaders should also plan for parallel runs, operating both on-premises and cloud systems in tandem, to validate that everything works as expected before the final cutover. They should engage end users early in the process in order to ensure the migrated environment meets business needs.

Researchers build first chip combining electronics, photonics, and quantum light

The new chip integrates quantum light sources and electronic controllers using a standard 45-nanometer semiconductor process. This approach paves the way for scaling up quantum systems in computing, communication, and sensing, fields that have traditionally relied on hand-built devices confined to laboratory settings. "Quantum computing, communication, and sensing are on a decades-long path from concept to reality," said Miloš Popović, associate professor of electrical and computer engineering at Boston University and a senior author of the study. "This is a small step on that path – but an important one, because it shows we can build repeatable, controllable quantum systems in commercial semiconductor foundries." ... "What excites me most is that we embedded the control directly on-chip – stabilizing a quantum process in real time," says Anirudh Ramesh, a PhD student at Northwestern who led the quantum measurements. "That's a critical step toward scalable quantum systems." This focus on stabilization is essential to ensure that each light source performs reliably under varying conditions. Imbert Wang, a doctoral student at Boston University specializing in photonic device design, highlighted the technical complexity.

Product Manager vs. Product Owner: Why Teams Get These Roles Wrong

While PMs work on the strategic plane, Product Owners anchor delivery. The PO is the guardian of the backlog. They translate the product strategy into epics and user stories, groom the backlog, and support the development team during sprints. They don’t just manage the “what” — they deeply understand the “how.” They answer developer questions, clarify scope, and constantly re-evaluate priorities based on real-time feedback. In Agile teams, they play a central role in turning strategic vision into working software. Where PMs answer to the business, POs are embedded with the dev team. They make trade-offs, adjust scope, and ensure the product is built right. ... Some products need to grow fast. That’s where Growth PMs come in. They focus on the entire user lifecycle, often structured using the PIRAT funnel: Problem, Insight, Reach, Activation, and Trust (a modern take on traditional Pirate Metrics, such as Acquisition, Activation, Retention, Referral, and Revenue). This model guides Growth PMs in identifying where user friction occurs and what levers to pull for meaningful impact. They conduct experiments, optimize funnels, and collaborate closely with marketing and data science teams to drive user growth.

Ransomware payments to be banned – the unanswered questions

With thresholds in place, businesses/organisations may choose to operate differently so that they aren’t covered by the ban, such as lowering turnover or number of employees. All of this said, rules like this could help to get a better picture of what’s going on with ransomware threats in the UK. Arda Büyükkaya, senior cyber threat intelligence analyst at EclecticIQ, explains more: “As attackers evolve their tactics and exploit vulnerabilities across sectors, timely intelligence-sharing becomes critical to mounting an effective defence. Encouraging businesses to report incidents more consistently will help build a stronger national threat intelligence picture something that’s important as these attacks grow more frequent and become sophisticated. To spare any confusion, sector-specific guidance should be provided by government on how resources should be implemented, making resources clear and accessible. “Many victims still hesitate to come forward due to concerns around reputational damage, legal exposure, or regulatory fallout,” said Büyükkaya. “Without mechanisms that protect and support victims, underreporting will remain a barrier to national cyber resilience.” Especially in the earlier days of the legislation, organisations may still feel pressured to pay in order to keep operations running, even if they’re banned from doing so.

AI Unleashed: Shaping the Future of Cyber Threats

AI optimizes reconnaissance and targeting, giving hackers the tools to scour public sources, leaked and publicly available breach data, and social media to build detailed profiles of potential targets in minutes. This enhanced data gathering lets attackers identify high-value victims and network vulnerabilities with unprecedented speed and accuracy. AI has also supercharged phishing campaigns by automatically crafting phishing emails and messages that mimic an organization’s formatting and reference real projects or colleagues, making them nearly indistinguishable from genuine human-originated communications. ... AI is also being weaponized to write and adapt malicious code. AI-powered malware can autonomously modify itself to slip past signature-based antivirus defenses, probe for weaknesses, select optimal exploits, and manage its own command-and-control decisions. Security experts note that AI accelerates the malware development cycle, reducing the time from concept to deployment. ... AI presents more than external threats. It has exposed a new category of targets and vulnerabilities, as many organizations now rely on AI models for critical functions, such as authentication systems and network monitoring. These AI systems themselves can be manipulated or sabotaged by adversaries if proper safeguards have not been implemented.

Agile and Quality Engineering: Building a Culture of Excellence Through a Holistic Approach

Agile development relies on rapid iteration and frequent delivery, and this rhythm demands fast, accurate feedback on code quality, functionality, and performance. With continuous testing integrated into automated pipelines, teams receive near real-time feedback on every code commit. This immediacy empowers developers to make informed decisions quickly, reducing delays caused by waiting for manual test cycles or late-stage QA validations. Quality engineering also enhances collaboration between developers and testers. In a traditional setup, QA and development operate in silos, often leading to communication gaps, delays, and conflicting priorities. In contrast, QE promotes a culture of shared ownership, where developers write unit tests, testers contribute to automation frameworks, and both parties work together during planning, development, and retrospectives. This collaboration strengthens mutual accountability and leads to better alignment on requirements, acceptance criteria, and customer expectations. Early and continuous risk mitigation is another cornerstone benefit. By incorporating practices like shift-left testing, test-driven development (TDD), and continuous integration (CI), potential issues are identified and resolved long before they escalate.

Could Metasurfaces be The Next Quantum Information Processors?

Broadly speaking, the work embodies metasurface-based quantum optics which, beyond carving a path toward room-temperature quantum computers and networks, could also benefit quantum sensing or offer “lab-on-a-chip” capabilities for fundamental science Designing a single metasurface that can finely control properties like brightness, phase, and polarization presented unique challenges because of the mathematical complexity that arises once the number of photons and therefore the number of qubits begins to increase. Every additional photon introduces many new interference pathways, which in a conventional setup would require a rapidly growing number of beam splitters and output ports. To bring order to the complexity, the researchers leaned on a branch of mathematics called graph theory, which uses points and lines to represent connections and relationships. By representing entangled photon states as many connected lines and points, they were able to visually determine how photons interfere with each other, and to predict their effects in experiments. Graph theory is also used in certain types of quantum computing and quantum error correction but is not typically considered in the context of metasurfaces, including their design and operation. The resulting paper was a collaboration with the lab of Marko Loncar, whose team specializes in quantum optics and integrated photonics and provided needed expertise and equipment.

New AI architecture delivers 100x faster reasoning than LLMs with just 1,000 training examples

When faced with a complex problem, current LLMs largely rely on chain-of-thought (CoT) prompting, breaking down problems into intermediate text-based steps, essentially forcing the model to “think out loud” as it works toward a solution. While CoT has improved the reasoning abilities of LLMs, it has fundamental limitations. In their paper, researchers at Sapient Intelligence argue that “CoT for reasoning is a crutch, not a satisfactory solution. It relies on brittle, human-defined decompositions where a single misstep or a misorder of the steps can derail the reasoning process entirely.” ... To move beyond CoT, the researchers explored “latent reasoning,” where instead of generating “thinking tokens,” the model reasons in its internal, abstract representation of the problem. This is more aligned with how humans think; as the paper states, “the brain sustains lengthy, coherent chains of reasoning with remarkable efficiency in a latent space, without constant translation back to language.” However, achieving this level of deep, internal reasoning in AI is challenging. Simply stacking more layers in a deep learning model often leads to a “vanishing gradient” problem, where learning signals weaken across layers, making training ineffective.

For the love of all things holy, please stop treating RAID storage as a backup

Although RAID is a backup by definition, practically, a backup doesn't look anything like a RAID array. That's because an ideal backup is offsite. It's not on your computer, and ideally, it's not even in the same physical location. Remember, RAID is a warranty, and a backup is insurance. RAID protects you from inevitable failure, while a backup protects you from unforeseen failure. Eventually, your drives will fail, and you'll need to replace disks in your RAID array. This is part of routine maintenance, and if you're operating an array for long enough, you should probably have drive swaps on a schedule of several years to keep everything operating smoothly. A backup will protect you from everything else. Maybe you have multiple drives fail at once. A backup will protect you. Lord forbid you fall victim to a fire, flood, or other natural disaster and your RAID array is lost or damaged in the process. A backup still protects you. It doesn't need to be a fire or flood for you to get use out of a backup. There are small issues that could put your data at risk, such as your PC being infected with malware, or trying to write (and replicate) corrupted data. You can dream up just about any situation where data loss is a risk, and a backup will be able to get your data back in situations where RAID can't.

Daily Tech Digest - March 20, 2025

Quote for the day:

"We get our power from the people we lead, not from our stars and our bars." -- J. Stanford

Agentic AI — What CFOs need to know

Agentic AI takes efficiency to the next level as it builds on existing AI platforms with human-like decision-making, relieving employees of monotonous routine tasks, allowing them to focus on more important work. CFOs will be happy to know that like other forms of AI, agentic is scalable and flexible. For example, organizations can build it into customer-facing applications for a highly customized experience or sophisticated help desk. Or they could embed agentic AI behind the scenes in operations. ... Not surprisingly, like other emerging technologies, agentic AI requires thoughtful and strategic implementation. This means starting with process identification and determining which specific process or functions are suitable for agentic AI. Business leaders also need to determine organizational value and impact and find ways to evaluate and measure to ensure the technology is delivering clear benefits. Companies should also be mindful of team composition, and, if necessary, secure external experts to ensure successful implementation. Beyond the technical feasibility, there are other considerations such as data security. For now, CFOs and other business leaders need to wrap their heads around the concept of “agents” and keep their minds open to how this powerful technology can best serve the needs of their organization.

5 pitfalls that can delay cyber incident response and recovery

For tabletop exercises to be truly effective they must have internal ownership and be customized to the organization. CISOs need to ensure that tabletops are tailored to the company’s specific risks, security use cases and compliance requirements. Exercises should be run regularly (quarterly, at a minimum) and evaluated with a critical eye to ensure that outcomes are reflected in the company’s broader incident response plan. ... One of the most common failures in incident response is a lack of timely information sharing. Key stakeholders, including HR, PR, Legal, executives and board members must be kept informed about the situation in real time. Without proper communication channels and predefined reporting structures, misinformation or delays can lead to confusion, prolonged downtime and even regulatory penalties for failure to report incidents within required timeframes. CISOs are responsible for proactively establishing clear communication protocols and ensuring that all responders and stakeholders understand their role in incident management. ... Out-of-band communication capabilities are critical for safeguarding response efforts and shielding them from an attacker’s view. Organizations should establish secure, independent channels for coordinating incident response that aren’t tied to corporate networks.

Bringing Security to Digital Product Design

We are aware that prioritizing security is a common challenge. Even though it is a critical issue, most leaders behind the development of new products are not interested in prioritizing this type of matter. Whenever possible, they try to focus the team's efforts on features. For this reason, there is often no room for this type of discussion. So what should we do? Fortunately, there are multiple possible solutions. One way to approach the topic is to take advantage of the opportunity of a collaborative and immersive session such as product discovery. ... Usually, in a product discovery session, there is a proposed activity to map personas. To map this kind of behavior, I recommend using the same persona model that is suggested. From there, go deeper into hostility characteristics in sections such as bio, objectives, interests, and frustrations, as in the figure above. After the personas have been described, it is important to deepen the discussion by mapping journeys. The goal here is to identify actions and behaviors that provide ideas on how to correctly deal with threats. Remember that when using an assailant actor, the materials should be written from its perspective. ... Complementing the user journey with likely attacker actions is another technique that helps software development teams map, plan, and address security as early as possible.

From Cloud Native to AI Native: Lessons for the Modern CISO to Win the Cybersecurity Arms Race

Today, CISOs stand at another critical crossroads in security operations: the move from a “Traditional SOC” to an “AI Native SOC.” In this new reality, generative AI, machine learning and large-scale data analytics power the majority of the detection, triage and response tasks once handled by human analysts. Like Cloud Native technology before it, AI Native security methods promise profound efficiency gains but also necessitate a fundamental shift in processes, skillsets and organizational culture.  ... For CISOs, transitioning to an AI Native SOC represents a massive opportunity—akin to how CIOs leveraged DevOps and cloud-native to gain a competitive edge:  Strategic Perspective: CISOs must look beyond tool selection to organizational and cultural shifts. By championing AI-driven security, they demonstrate a future-ready mindset—one that’s essential for keeping up with advanced adversaries and board-level expectations around cyber resilience.  Risk Versus Value Equation: Cloud-native adoption taught CIOs that while there are upfront investments and skill gaps, the long-term benefits—speed, agility, scalability—are transformative. In AI Native security, the same holds true: automation reduces response times, advanced analytics detect sophisticated threats and analysts focus on high-value tasks. 

Europe slams the brakes on Apple innovation in the EU

With its latest Digital Markets Act (DMA) action against Apple, the European Commission (EC) proves it is bad for competition, bad for consumers, and bad for business. It also threatens Europeans with a hitherto unseen degree of data insecurity and weaponized exploitation. The information Apple is being forced to make available to competitors with cynical interest in data exfiltration will threaten regional democracy, opening doors to new Cambridge Analytica scandals. This may sound histrionic. And certainly, if you read the EC’s statement detailing its guidance to “facilitate development of innovative products on Apple’s platforms” you’d almost believe it was a positive thing. ... Apple isn’t at all happy. In a statement, it said: “Today’s decisions wrap us in red tape, slowing down Apple’s ability to innovate for users in Europe and forcing us to give away our new features for free to companies who don’t have to play by the same rules. It’s bad for our products and for our European users. We will continue to work with the European Commission to help them understand our concerns on behalf of our users.” There are several other iniquitous measures contained in Europe’s flawed judgement. For example, Apple will be forced to hand over access to innovations to competitors for free from day one, slowing innovation.

The Impact of Emotional Intelligence on Young Entrepreneurs

The first element of emotional intelligence is self-awareness which means being able to identify your emotions as they happen to understand how they affect your behavior. During the COVID-19 pandemic, I often felt frustrated when my sales went down during the international bookfair. But by practicing self-awareness, I was able to acknowledge the frustration and think about its sources instead of letting it lead to impulsive reactions. Being self-aware helps me to stay in control of  actions and make decisions that align with my values. So the solution back then was to keep pushing sales through my online platform instead of showing up in person as I realized that people were still in lockdown due to the pandemic.   Self-recognition is another important aspect of emotional intelligence. While self-awareness is about recognizing emotions, self-regulation focuses on managing how you respond to them. Self-regulation doesn't mean ignoring your emotions but learning to express them in a constructive way. Imagine a situation where you feel angry after receiving negative feedback. Instead of reacting defensively or shouting, self-recognition allows you to take a step back, consider the feedback calmly, and respond appropriately.

Bridging the Gap: Integrating All Enterprise Data for a Smarter Future

To bridge the gap between mainframe and hybrid cloud environments, businesses need a modern, flexible, technology-driven strategy — one that ensures they can access, analyze, and act on their data without disruption. Rather than relying on costly, high-risk "rip-and-replace" modernization efforts, organizations can integrate their core transactional data with modern cloud platforms using automated, secure, and scalable solutions capable of understanding and modernizing mainframe data. One of the most effective methods is real-time data replication and synchronization, which enables mainframe data to be continuously updated in hybrid cloud environments in real time. Low-impact change data capture technology recognizes and replicates only the modified portions of datasets, reducing processing overhead and ensuring real-time consistency across both mainframe and hybrid cloud systems. Another approach is API-based integration, which allows organizations to provide mainframe data as modern, cloud-compatible services. This eliminates the need for batch processing and enables cloud-native applications, AI models, and analytics platforms to access real-time mainframe data on demand. API gateways further enhance security and governance, ensuring only authorized systems can interact with sensitive transactional business data.

How CISOs are approaching staffing diversity with DEI initiatives under pressure

“In the end, a diverse, engaged cybersecurity team isn’t just the right thing to build — it’s critical to staying ahead in a rapidly evolving threat landscape,” he says. “To fellow CISOs, I’d say: Stay the course. The adversary landscape is global, and so our perspective should be as well. A commitment to DEI enhances resilience, fosters innovation, and ultimately strengthens our defenses against threats that know no boundaries.” Nate Lee, founder and CISO at Cloudsec.ai, says that even if DEI isn’t a specific competitive advantage — although he thinks diversity in many shapes is — it’s the right thing to do, and “weaponizing it the way the administration has is shameful.” “People want to work where they’re valued as individuals, not where diversity is reduced to checking boxes, but where leadership genuinely cares about fostering an inclusive environment,” he says. “The current narrative tries to paint efforts to boost people up as misguided and harmful, which to me is a very disingenuous argument.” ... “Diverse workforces make you stronger and you are a fool if you [don’t] establish a diverse workforce in cybersecurity. You are at a distinct disadvantage to your adversaries who do benefit from diverse thinking, creativity, and motivations.”

AI-Powered Cyber Attacks and Data Privacy in The Age of Big Data

Artificial intelligence significantly increased the capabilities of attackers to efficiently conduct cyber-attacks. This also increased their intelligence and the scale of the attacks. Compared to the traditional process of cyber-attacks, the attacks driven by AI have the capability to automatically learn, adapt, and develop strategies with a minimum number of human interventions. These attacks proactively utilize the algorithms of machine learning, natural language processing, and deep learning models. They leverage these algorithms in the process of determining and analyzing issues or vulnerabilities, avoiding security and detection systems, and developing phishing campaigns that are believable. ... AI has also significantly increased the intelligence of systems related to malware and autonomous hacking. These systems gained the capabilities to infiltrate networks, leverage the vulnerabilities of the system, and avoid detection systems. Malware driven by AI has the capability to make real-time modifications to its codes, unlike conventional malware. This significantly increases the difficulties in the detection and eradication process for the security software. These difficulties involve infiltration in systems powered by AI, such as polymorphic malware. It can convert its appearance based on the data collected from every attempt of cyber-attack.

Platform Engineers Must Have Strong Opinions

Many platform engineering teams build internal developer platforms, which allow development teams to deploy their infrastructure with just a few clicks and reduce the number of issues that slow deployments. Because they are designing the underlying application infrastructure across the organization, the platform engineering team must have a strong understanding of their organization and the application types their developers are creating. This is also an ideal point to inject standards about security, data management, observability and other structures that make it easier to manage and deploy large code bases. ... To build a successful platform engineering strategy, a platform engineering team must have well-defined opinions about platform deployments. Like pizza chefs building curated pizza lists based on expertise and years of pizza experience, the platform engineering team applies its years of industry experience in deploying software to define software deployments inside the organization. The platform engineering team’s experience and opinions guide and shape the underlying infrastructure of internal platforms. They put guardrails into deployment standards to ensure that the provided development capabilities meet the needs of engineering organizations and fulfill the larger organization’s security, observability and maintainability needs.

Daily Tech Digest - December 12, 2024

The future of AI regulation is up in the air: What’s your next move?

The problem is, Jones says, is that lack of regulations boils down to a lack of accountability, when it comes to what your large language models are doing — and that includes hoovering up intellectual property. Without regulations and legal ramifications, resolving issues of IP theft will either boil down to court cases, or more likely, especially in cases where the LLM belongs to a company with deep pockets, the responsibility will slide downhill to the end users. And when profitability outweighs the risk of a financial hit, some companies are going to push the boundaries. “I think it’s fair to say that the courts aren’t enough, and the fact is that people are going to have to poison their public content to avoid losing their IP,” Jones says. “And it’s sad that it’s going to have to get there, but it’s absolutely going to have to get there if the risk is, you put it on the internet, suddenly somebody’s just ripped off your entire catalog and they’re off selling it directly as well.” ... “These massive weapons of mass destruction, from an AI perspective, they’re phenomenally powerful things. There should be accountability for the control of them,” Jones says. “What it will take to put that accountability onto the companies that create the products, I believe firmly that that’s only going to happen if there’s an impetus for it.”

Leading VPN CCO says digital privacy is "a game of chess we need to play"

Sthanu calls VPNs a first step, and puts forward secure browsers as a second. IPVanish recently launched a secure browser, which is an industry first, and something not offered by other top VPN providers. "It keeps your browser private, blocking tracking, encrypting the sessions, but also protecting your device from any malware," Sthanu said. IPVanish's secure browser utilises the cloud. Session tracking, cookies, and targeting are all eliminated, as web browsing operates in a cloud sandbox. ... Encrypting your data is a vital part of what VPNs do. AES 256-bit and ChaCha20 encryption are currently the standards for the most secure VPNs, which do an excellent job at encrypting and protecting your data. These encryption ciphers can protect you against the vast majority of cyber threats out there right now – but as computers and threats develop, security will need to develop too. Quantum computers are the next stage in computing evolution, and there will come a time, predicted to be in the next five years, where these computers can break 256-bit encryption – this is being referred to as "Q-day." Quantum computers are not readily available at this moment in time, with most found in universities or research labs, but they will become more widespread.

Kintsugi Leaders: Conservers of talent who convert the weak into winners

Profligate Leaders are not only gluttonous in their appetite for consuming resources, they are usually also choosy about the kind they will order. Not for them the tedious effort of using their own best-selling, training cookbook for seasoning and stirring the youth coming out from the country’s stretched and creaking educational system. On the contrary, they push their HR to queue up for ready-cooked candidates outside the portals of elite institutes on day zero. ... Kintsugi Leaders can create nobility of a different kind if they follow three precepts. The central one is the willingness to bet big and take risks on untried talent. In one of my Group HR roles, eyebrows were raised when I placed the HR leadership of large businesses in the hands of young, internally groomed talent instead of picking stars from the market. ... There is a third (albeit rare) kind of HR leader: the Trusted Transformer who can convert a Profligate Leader into the Kintsugi kind. Revealable corporate examples are thin on the ground. In keeping with the Kintsugi theme, then, I have to fall back on Japan. Itō Hirobumi had a profound influence on Emperor Meiji and played a pivotal role in shaping the political landscape of Meiji-era Japan.

4 North Star Metrics for Platform Engineering Teams

“Acknowledging that DORA, SPACE and DevEx provide different slivers or different perspectives into the problem, our goal was to create a framework that encapsulates all the frameworks,” Noda said, “like one framework to rule them all, that is prescriptive and encapsulates all the existing knowledge and research we have.” DORA metrics don’t mean much at the team level, but, he continued, developer satisfaction — a key measurement of platform engineering success — doesn’t matter to a CFO. “There’s a very intentional goal of making especially the key metrics, but really all the metrics, meaningful to all stakeholders, including managers,” Noda said. “That enables the organization to create a single, shared and aligned definition of productivity so everyone can row in the same direction.” The Core 4 key metrics are:An average of diffs per engineer is used to measure speed. The Developer Experience Index, or homegrown developer experience surveys, is used to measure effectiveness. A change failure rate is used to measure quality. The percentage of time spent on new capabilities to measure impact. DX’s own DXI, which uses a standardized set of 14 Likert-scale questions — from strongly agree to strongly disagree — is currently only available to DX users.

The future of data: A 5-pillar approach to modern data management

To succeed in today’s landscape, every company — small, mid-sized or large — must embrace a data-centric mindset. This article proposes a methodology for organizations to implement a modern data management function that can be tailored to meet their unique needs. By “modern”, I refer to an engineering-driven methodology that fully capitalizes on automation and software engineering best practices. This approach is repeatable, minimizes dependence on manual controls, harnesses technology and AI for data management and integrates seamlessly into the digital product development process. ... Unlike the technology-focused Data Platform pillar, Data Engineering concentrates on building distributed parallel data pipelines with embedded business rules. It is crucial to remember that business needs should drive the pipeline configuration, not the other way around. For example, if preserving the order of events is essential for business needs, the appropriate batch, micro-batch or streaming configuration must be implemented to meet these requirements. Another key area involves managing the operational health of data pipelines, with an even greater emphasis on monitoring the quality of the data flowing through the pipeline.

How and Why the Developer-First Approach Is Changing the Observability Landscape

First and foremost, developers aim to avoid issues altogether. They seek modern observability solutions that can prevent problems before they occur. This goes beyond merely monitoring metrics: it encompasses the entire software development lifecycle (SDLC) and every stage of development within the organization. Production issues don't begin with a sudden surge in traffic; they originate much earlier when developers first implement their solutions. Issues begin to surface as these solutions are deployed to production and customers start using them. Observability solutions must shift to monitoring all the aspects of SDLC and all the activities that happen throughout the development pipeline. This includes the production code and how it’s running, but also the CI/CD pipeline, development activities, and every single test executed against the database. Second, developers deal with hundreds of applications each day. They can’t waste their time manually tuning alerting for each application separately. The monitoring solutions must automatically detect anomalies, fix issues before they happen, and tune the alarms based on the real traffic. They shouldn’t raise alarms based on hard limits like 80% of the CPU load.

We must adjust expectations for the CISO role

The sense of vulnerability CISOs feel today is compounded by a shifting accountability model in the boardroom. As cybersecurity incidents make front-page news more frequently, boards and executive teams are paying closer attention. This increased scrutiny is a double-edged sword: on the one hand, it can mean greater support and resources; on the other, it often translates to CISOs being in the proverbial hot seat. What’s more, cybersecurity is still a rapidly evolving field with few long-standing best practices. It’s a space marked by constant adaptation, bringing a certain degree of trial and error. When an error occurs—especially one that leads to a breach—the CISO’s role is scrutinized. While the entire organization might have a role in cybersecurity, CISOs are often expected to bear the brunt of accountability. This dynamic is unsettling for many in the position, and the 99% of CISOs who fear for their job security in the event of a breach clearly illustrates this point. So, what can be done? Both organizations and CISOs are responsible for recalibrating expectations and addressing the root causes of these pervasive job security fears. For organizations, a starting point is to shift cybersecurity from a reactive to a proactive stance. Investing in continuous improvement—whether through advanced security technologies, employee training, or cyber insurance—is crucial.

Bug bounty programs can deliver significant benefits, but only if you’re ready

The most significant benefit of a bug bounty program is finding vulnerabilities an organization might not have otherwise discovered. “A bug bounty program gives you another avenue of identifying vulnerabilities that you’re not finding through other processes,” such as internal vulnerability scans, Stefanie Bartak, associate director of the vulnerability management team at NCC Group, tells CSO. Establishing a bug bounty program signals to the broader security research community that an organization is serious about fixing bugs. “For an enterprise, it’s a really good way for researchers, or anyone, to be able to contact them and report something that may not be right in their security,” Louis Nyffenegger, CEO of PentesterLab, tells CSO. Moreover, a bug bounty program will offer an organization a wider array of talent to bring perspectives that in-house personnel don’t have. “You get access to a large community of diverse thinkers, which help you find vulnerabilities you may otherwise not get good access to,” Synack’s Lance says. “That diversity of thought can’t be underestimated. Diversity of thought and diversity of researchers is a big benefit. You get a more hardened environment because you get better or additional testing in some cases.”

Harnessing SaaS to elevate your digital transformation journey

The impact of AI-driven SaaS solutions can be seen across multiple industries. In retail, AI-powered SaaS platforms enable businesses to analyze consumer behavior in real-time, providing personalized recommendations that drive sales. In manufacturing, AI optimizes supply chain management, reducing waste and increasing productivity. In the finance sector, AI-driven SaaS automates risk assessment, improving decision-making and reducing operational costs. ... As businesses continue to adopt SaaS and AI-driven solutions, the future of digital transformation looks promising. Companies are no longer just thinking about automating processes or improving efficiency, they are investing in technologies that will help them shape the future of their industries. From developing the next generation of products to understanding their customers better, SaaS and AI are at the heart of this evolution. CTOs, like myself, are now not only responsible for technological innovation but are also seen as key contributors to shaping the company’s overall business strategy. This shift in leadership focus will be critical in helping organizations navigate the challenges and opportunities of digital transformation. By leveraging AI and SaaS, we can build scalable, efficient, and innovative systems that will drive growth for years to come.

What makes product teams effective?

More enterprises are adopting a cross-functional team model, yet many still tend to underinvest in product management. While they make sure to fill the product owner role—a person accountable for translating business needs into technology requirements—they do not always choose the right individual for the product manager role. Effective product managers are business leaders with the mindset and technical skills to guide multiple product teams simultaneously. They shape product strategy, define requirements, and uphold the bar on delivery quality, usually partnering with an engineering or technology lead in a two-in-a-box model. ... Unsurprisingly, when organizations recognize individual expertise, provide options for career progression, and base promotions on capabilities, employees are more engaged and satisfied with their teams. Similarly, by standardizing and reducing the overall number of roles, organizations naturally shift to a balanced ratio of orchestrators (minority) to doers (majority), which increases team capacity without hiring more employees. This shift helps ensure teams can meet their delivery commitments and creates a transparent environment where individuals feel empowered and informed.

Quote for the day:

“Things come to those who wait, but only the things left by those who hustle” -- Abraham Lincoln