Daily Tech Digest by Kannan Subbiah: ERP

Showing posts with label ERP. Show all posts

Daily Tech Digest - June 17, 2026

Quote for the day:

"The most difficult thing is the decision to act, the rest is merely tenacity." -- Amelia Earhart

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Duration: 25 mins • Perfect for listening on the go.

The Rise of Agentic Internet

The internet has reached a significant milestone where automated web traffic now exceeds human activity. According to recent data, bots currently account for over fifty percent of all internet traffic, crossing this threshold much earlier than industry experts had predicted. This shift is primarily driven by the rapid emergence of autonomous artificial intelligence agents. Unlike older, simple programs or connected devices that only follow rigid instructions, these new agents possess true autonomy. They interpret user intent, adapt to context, and make independent decisions without needing constant human guidance. As a result, autonomous software traffic has experienced exponential growth over the past year. A major area affected by this change is how we search for information. Traditional search engines that return simple lists of links are being replaced by conversational interfaces. When a person asks a complex question, the software dispatches numerous agents to visit hundreds of pages, synthesize the data, and return a complete answer. Because a single human request can generate thousands of automated web actions, we are entering a new era where machines discover information, evaluate options, and execute tasks on our behalf.

Building data centers in space is an intriguing idea on paper, but major engineering challenges must be solved

The proposal to establish data centers in space presents a captivating concept that aims to address the growing energy and cooling demands of our digital infrastructure. By positioning servers outside of Earth's atmosphere, we could theoretically harness constant solar energy and utilize the natural vacuum of space to simplify heat management. While this idea appears promising on paper, it faces significant engineering and logistical hurdles that currently make it impractical. A primary obstacle is the immense difficulty and cost associated with launching and maintaining complex hardware in orbit. Unlike terrestrial facilities, space-based data centers would require specialized, radiation-hardened equipment to withstand the harsh orbital environment, including extreme temperature fluctuations and debris impacts. Furthermore, servicing or upgrading these systems would be exceptionally difficult, requiring sophisticated robotic interventions or costly human missions. There is also the critical issue of signal latency; transmitting data between Earth and space-based servers introduces delays that could disrupt many time-sensitive applications. While the idea reflects creative thinking regarding future infrastructure needs, these formidable technological and economic constraints must be thoroughly addressed before such a project could realistically transition from an interesting theoretical model to a functional reality.

Firms pursue continuous identity in push to meet agentic paradigm shift

The cybersecurity industry is rapidly evolving to address the growing presence of artificial intelligence programs operating autonomously within corporate networks. As organizations increasingly rely on these automated tools, traditional security systems built exclusively for human users are no longer sufficient. To resolve this, major technology firms are developing continuous identity verification systems that monitor and secure both human and machine activities simultaneously. Recently, a new company called NewCore secured significant funding to launch a platform that maps and protects all active network identities from the ground up. Similarly, established companies are expanding their capabilities through acquisitions and updates. SailPoint plans to acquire Entro to improve its tracking of machine credentials, while CrowdStrike has introduced a system that constantly verifies automated actions rather than granting permanent access. Additionally, Akamai has established a structured framework to safely manage automated commerce and interactions, and Silverfort has integrated instant identity checks specifically for Microsoft Copilot Studio to prevent unauthorized actions before they occur. Together, these industry developments highlight a crucial transition from one time authentication to ongoing and instant security models that ensure automated tools operate safely and responsibly within modern enterprise environments.

Beyond the ERP system: The autonomous value chain

Traditional enterprise resource planning systems have reached a performance ceiling because they rely on people to manually move and approve data. This manual approach creates expensive delays and inefficiencies that minor adjustments can no longer fix. To move forward, organizations must abandon these outdated structures in favor of an autonomous value chain. In this modernized setup, intelligent algorithms handle routine daily procurement, production, and delivery coordination in real time. Instead of functioning as manual data processors, employees are freed to focus on high level strategic design and system oversight. Transitioning to this level of autonomy requires more than just installing new software; it demands a deep organizational shift. Companies need to establish centralized, reliable data sources and build automated processes governed by clear rules and boundaries. Equally important is fostering a supportive culture built on trust and psychological safety. Teams must feel secure collaborating with automated systems, knowing they have the authority to intervene without facing blame for machine errors. Ultimately, the goal is to stop managing slow, manual workflows and instead design a fully independent system that coordinates seamlessly. This shift delivers greater operational efficiency and frees human talent for more valuable work.

Four Ways To Develop Emotional Intelligence In The Workplace

While technical skills are often highlighted on resumes, emotional intelligence is the defining trait of an effective leader. It involves recognizing and managing your own emotions while understanding those of your team. Without it, organizations face turnover and burnout; with it, they build resilience and trust. Fortunately, you can develop emotional intelligence through four practical methods. First, practice self-awareness by taking time to reflect on your emotional state before entering important conversations or meetings. This prevents unexamined stress from guiding your behavior. Second, master the strategic pause. Instead of reacting immediately to frustration, give yourself time to process the situation, such as waiting a day before replying to a difficult email. Third, use active empathy to understand the motivations and pressures your team members face. Ask how you can support them rather than demanding explanations for setbacks. Finally, create an environment of psychological safety where employees feel comfortable taking risks and making mistakes without fear of punishment. When leaders openly admit their own errors, it encourages the rest of the team to work authentically. By investing in these areas, you can build a stronger, more resilient organization.

The AI Accountability Gap CIOs Can't Ignore

According to a recent IBM survey of 2,000 technology executives, chief information and technology officers are facing a significant accountability gap as artificial intelligence moves into everyday production. While eighty percent of these leaders are under direct pressure from chief executives to adopt AI quickly, two-thirds find themselves responsible for AI outcomes they do not fully control. By the year 2027, organizations expect to manage over sixteen hundred AI models, yet only eleven percent of technology leaders feel ready for this rapid growth. A primary challenge is the steady rise of untracked AI use. Seventy percent of executives report that internal business departments deploy AI tools much faster than their technical teams can monitor. This lack of oversight has clear consequences. Over the past year, organizations experienced an average of fifty-four AI-related incidents. These events led to notable problems, including data breaches for thirty-seven percent of respondents and widespread system failures for thirty-three percent. Consequently, AI adoption is currently moving faster than organizations can secure it. Seventy-seven percent of leaders admit their deployment speeds outpace internal governance, forcing many to pause expansion until they can establish proper visibility and control.

Do Software and Programmers Still Have a Future?

In their 2026 update, the team behind the software tool NocoBase reflects on how rapid advancements in artificial intelligence initially caused intense anxiety about the future of traditional programming. Despite these fears, their revenue doubled in the first half of the year. The small team realized that while artificial intelligence can generate code quickly, large businesses still require stable, secure, and standardized foundations to run their daily operations. Companies cannot rely on raw code generation alone; they need reliable systems with proper access rules, clear steps, and visual screens that humans can easily read and adjust. Rather than fighting these rapid market changes, NocoBase adapted its main focus. They shifted from basic visual programming to providing the essential structure that allows artificial intelligence to safely interact with complex business records. By integrating advanced models internally, the team also doubled their own productivity without hiring more staff. Their direct experience with major corporate clients in life sciences and renewable energy proves that actual businesses adapt much slower than internet technology trends. By acting as a practical bridge between new tools and older manual operations, programmers and thoughtful software projects still have a secure and valuable future.

Develop smarter AI agents with data fabrics

As organizations manage data scattered across numerous platforms, data fabrics offer a practical way to centralize access and enforce consistent policies. This centralized approach is especially relevant for teams developing artificial intelligence agents. AI agents require extensive, reliable information to function effectively, relying on both structured data and unstructured formats like documents or emails. Without a shared business context, these agents struggle to make accurate decisions and can even operate counter to one another in complex systems. A data fabric acts as a central system that connects AI models to diverse information sources. It provides agents with the current data and historical memory they need to act appropriately. Furthermore, this structure allows teams to resolve data quality issues before the information reaches the AI, ensuring the agents operate on accurate, compliant, and secure inputs. By consolidating data access, organizations can also establish stricter security controls and monitor exactly what information agents use. Moving forward, data fabrics are expected to improve how they handle multimedia files and complex documents. Ultimately, a carefully planned data fabric helps organizations deploy AI agents with a clear understanding of the rules, leading to more reliable outcomes.

AI and Cybersecurity – Everything You Wanted to Know, But Were Afraid to Ask

Artificial intelligence is changing cybersecurity, presenting both new defensive capabilities and complex security challenges. Based on insights from dozens of industry professionals, the current landscape of AI in security can be understood through five primary categories: generative AI, agentic AI, shadow AI, machine learning, and artificial general intelligence. Currently, generative AI serves as the foundation. While it offers practical benefits for security teams, such as summarizing incident logs, drafting response plans, and assisting with coding, it is not inherently trustworthy. Because these models predict statistically probable answers rather than relying on absolute facts, they can produce confident but incorrect responses. Therefore, AI should act as a supportive tool rather than a replacement for human judgment. Without proper governance, organizations risk unintentional misuse, where employees rely too heavily on unverified outputs or use external, unsecured AI tools. At the same time, malicious actors are actively exploiting these technologies. They move quickly to adopt AI for creating highly convincing phishing campaigns, writing evasive malware, and executing advanced social engineering attacks. Ultimately, understanding both the practical applications and the inherent risks of AI is essential for navigating the modern security environment.

The checklist problem behind critical infrastructure cyber safety

Recent research from George Mason University highlights a significant gap in how the United States approaches the safety of critical infrastructure. Currently, operators of industrial controls, medical devices, and transportation systems often rely on standard IT security compliance to prove their systems are safe. However, this approach is fundamentally flawed because data protection rules do not easily translate to the physical world. In fact, standard IT practices can sometimes introduce physical hazards. For instance, locking down a system to protect data might trap people during an emergency or disrupt safety controls that require real-time responses. The researchers note that current regulations rely too much on administrative checklists and generic technical standards, ignoring the specific engineering needs of physical machinery. When failures occur, regulations typically only require companies to report the incident rather than prove the equipment can naturally revert to a safe state. To fix this, the study suggests shifting the legal standard of care away from basic compliance. Instead, operators should be expected to provide concrete engineering evidence showing their systems are physically resilient. This includes implementing mechanical backups and hazard-specific safety measures, ensuring that if digital defenses fail, the physical equipment remains secure.

Daily Tech Digest - June 03, 2026

Quote for the day:

"Leadership is practiced not so much in words as in attitude and actions." -- Harold S. Geneen

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Duration: 19 mins • Perfect for listening on the go.

What will AI-first UX look like?

The transition to user experiences guided by artificial intelligence marks a steady move away from rigid, traditional interfaces like static forms and manual dashboards. Rather than requiring users to navigate multiple disconnected software tools to complete tasks, future interfaces will rely on conversational systems that connect seamlessly across various applications. In this evolving landscape, standard data entry forms are being replaced by adaptive interactions where users simply describe what they want to accomplish, and the system gathers the necessary details. Similarly, data reporting is shifting from complex, manually built dashboards to narrative summaries generated on demand, providing clear explanations of business metrics and actionable next steps. This shift transforms standard workflows into coordinated teamwork between humans and software agents. The software handles processes involving multiple steps behind the scenes and only escalates to human workers when careful judgment is required. To make this work effectively, organizations must build strong underlying foundations, including clear data structures, connected programming interfaces, and solid oversight rules. Ultimately, these systems are designed not to replace human workers, but to reduce friction and manage tasks across platforms more naturally. As this technology matures, the focus remains on building reliable environments where software acts as a helpful teammate, smoothly coordinating background tasks while keeping human users firmly in control of the final outcomes.

Minimally Acceptable Systems: Tolerable at the Lowest Cost Possible

The article discusses a growing trend in software engineering and business where companies intentionally design systems to be merely adequate rather than striving for excellence. This concept, described as creating minimally acceptable systems, focuses on finding the exact point where a product is just tolerable for users while being as cheap as possible to build and maintain. Instead of prioritizing high quality, reliability, or a great user experience, organizations aim to minimize their costs and speed up delivery. They provide the bare minimum functionality required to keep people from abandoning the software. While this approach makes clear financial sense in the short term and helps companies stay competitive, it comes with serious long-term consequences. By constantly pushing standards to the lowest acceptable limit, the industry conditions people to expect and accept frustrating, unreliable software in their daily lives. The author warns that treating quality simply as an expense to be cut ultimately damages user trust and builds up massive technical problems for the future. To fix this, the software field needs to rethink its current financial motives. Engineers and business leaders should work together to find a better balance, creating products that are both affordable to produce and genuinely reliable for the people who use them.

Software sprawl is becoming a margin problem for SaaS CFOs

For software companies, the practice of adopting isolated tools to solve individual problems, such as payments, billing, and tax compliance, often leads to a fragmented operations setup known as software sprawl. While the subscription-based business model has historically enjoyed strong profit margins, this growing web of disconnected systems threatens to undermine those financial advantages. Finance leaders are finding that a patched-together technology system severely limits their clear view of business performance, putting unneeded pressure on profit margins through manual work, costly billing errors, and duplicate expenses. Furthermore, relying on fragmented tools restricts a company's ability to smoothly expand into new regions or test different pricing methods. Rather than looking at this as just an IT issue, financial executives must recognize it as a fundamental challenge to scalable growth. The path forward does not necessarily require adopting one massive platform, but rather ensuring that all revenue processes operate smoothly together. By replacing disconnected tools with an integrated infrastructure, companies can drastically reduce manual interventions and internal friction. Ultimately, the next era of the software industry will reward organizations that match their desire for growth with strict operational discipline. By fixing these underlying structural flaws now, finance teams can build a resilient foundation capable of handling future expansion without constantly multiplying internal complexities or operational costs.

The Zero-Knowledge Threat Actor and the End of Responsible Disclosure

Artificial intelligence is drastically lowering the barrier to entry for cybercriminals, enabling a new wave of "zero-knowledge threat actors." These attackers lack deep technical expertise but use advanced AI tools to generate malicious code, find vulnerabilities, and execute complex attack chains with surprising ease. This democratization of offensive capabilities means that hackers can now discover and exploit software flaws at unprecedented speeds, effectively closing the traditional responsible disclosure window that software vendors rely on to create patches. Smaller organizations are particularly at risk, often serving as stepping stones into larger enterprise supply chains due to their limited security resources and slower patching cycles. To defend against these rapidly evolving threats, security teams must abandon fragmented approaches and adopt unified monitoring systems that provide clear, comprehensive visibility across their entire digital environment. Proactive defense requires prioritizing faster patch management, conducting regular incident response drills, and rigorously testing in-house AI systems against deliberate manipulation by external actors. Furthermore, training employees to recognize highly realistic, AI-generated phishing attempts is absolutely essential for maintaining a strong security posture. By relying on established security frameworks and maintaining an organized, practiced defense strategy, organizations can calmly and effectively counter the increased capabilities of low-skill attackers without resorting to panic or operational disruption.

ERP Modernization: Most Expensive, Risky Item on CIO Agenda

Enterprise resource planning systems have grown over the last forty years from basic financial and manufacturing tools into the central framework of most organizations. Today, they handle everything from supply chains to human resources. However, updating these core systems is now one of the most difficult and costly challenges facing technology leaders. Modernizing these structures is not just a software update; it is a major overhaul of how a business operates on a daily basis. Transitioning to modern setups, like cloud-based platforms, involves heavy restructuring of daily work processes and often triggers natural resistance from staff. To succeed, these projects need more than just technical expertise. They require a clear process for managing transitions, direct communication to address employee fears, and strong backing from senior leadership to keep the effort on track during inevitable setbacks. As software vendors increasingly move customers toward cloud and artificial intelligence platforms, technology leaders are forced to weigh the long-term benefits against the immediate financial costs, operational risks, and widespread disruptions. Navigating this shift takes a dedicated, highly skilled team and steady executives who will not abandon the project when minor problems arise. With careful planning, patience, and stable leadership, organizations can successfully migrate their central systems to meet current operational demands without jeopardizing their everyday stability.

The AI ‘Revolution' is Not a People's Revolution

Politicians and technology executives increasingly frame artificial intelligence as an inevitable revolution, a term historically reserved for popular movements driving social progress. In truth, this modern narrative serves primarily to bypass democratic scrutiny and consolidate power among a select few. Rather than arising from the people to challenge the existing order, the current technological push is being imposed from the top down. Leaders like former UK Prime Minister Tony Blair promote a vision where society must passively accept widespread automation, mass data harvesting, and unchecked corporate influence, treating any hesitation as backwardness. By labeling this shift a revolution, proponents cleverly silence debate and frame regulatory efforts as sabotage. Furthermore, while previous digital tools aided grassroots organizing, artificial intelligence is frequently deployed to monitor, police, and discipline the public. This rhetoric essentially functions as a manipulative marketing tool, designed to mask the reality of wealth generation for elites at the expense of ordinary citizens facing job insecurity and climate disruption. Ultimately, society must reject this predetermined technological path and demand accountability. Citizens have the right to question who truly benefits from these systems and to actively decide how new technologies should integrate into their lives, ensuring that any real change remains firmly rooted in public consent and democratic choice.

The AI pricing conundrum — it started as a nightmare, now it’s worse.

Enterprise technology leaders face a growing dilemma in how they pay for artificial intelligence. Buyers want pricing based on the tangible business value the technology delivers, while software providers prefer charging based on resource consumption, such as per-token fees. This creates a deep disconnect. Technology departments often feel consumption pricing is detached from real results, likening it to paying for unproven sales leads. On the other hand, providers cannot realistically accept value-based pricing because they have no control over internal company issues like poor data, broken processes, or office politics. Furthermore, if these systems were compensated strictly based on successful outcomes, it could create dangerous incentives. The software might aggressively pursue specific metrics, potentially sacrificing customer trust, ethical standards, or operational safety just to achieve the defined goal. Since bridging this gap directly is nearly impossible, organizations must take control internally. The article suggests forming dedicated committees to ask difficult questions about the goals, risks, and realistic benefits of any new project. Additionally, senior executives should share the financial accountability, tying their compensation directly to the success or failure of these initiatives. Only by thoroughly understanding a project's true intent, limitations, and risks can technology leaders negotiate sensible, fair pricing agreements with their service providers.

AI Is Shipping Fast, Quality Can't Be Left Behind

The recent transition of artificial intelligence from experimental phases to widespread integration has revealed a significant gap between rapid development and reliable performance. While organizations are swift to embed these systems into their daily operations, a substantial number of these initiatives stall before full implementation due to quality and integration hurdles. Data indicates an increase in user-reported errors, such as misunderstandings and factual inaccuracies, highlighting that traditional validation methods are inadequate for modern, complex systems. Because these programs produce varying outputs rather than predictable, fixed results, engineering teams are finding that automated checks alone are insufficient. To address this, successful organizations are adopting a balanced approach to quality assurance that combines automated evaluations with essential human oversight. Human reviewers are uniquely equipped to gauge context, usability, and intent, catching subtle errors that automated tools often miss. Furthermore, as features expand to process combinations of text, audio, and visual data, the scope of testing becomes even more difficult. The focus is shifting from merely launching features to ensuring they are dependable and trustworthy. Moving forward, the true measure of success will not be the speed of release, but the ability to maintain rigorous, ongoing evaluation processes that prioritize consistent, high-quality experiences for everyday users.

Why Leadership Development Is A System, Not An Event

Organizations frequently send their managers to training workshops, hoping they return ready to guide their teams more effectively. However, these well-intentioned programs often fail because managers step right back into the exact same workloads, pressures, and routines that shaped their old habits in the first place. Meaningful leadership development requires more than simply teaching new skills to individuals; it demands a daily environment actively designed to support those new behaviors. This involves shifting the focus from individual improvement to strengthening the broader company system. Executives must intentionally build a supportive structure with both visible changes, like collaborative meeting practices and transparent decision-making, and invisible shifts, such as fostering an atmosphere where feedback flows freely and people feel secure taking interpersonal risks. Instead of relying on isolated lectures, learning should become an ongoing process smoothly integrated into daily work. By encouraging peer learning groups, aligning company rewards with the behaviors taught in training, and personally modeling these changes, executives create a setting where true growth can take root over time. Ultimately, developing effective leaders is about expanding the capabilities of the entire organization. When the daily workplace aligns with the principles taught in training, individuals practice what they learn, ensuring development becomes a continuous habit rather than a fleeting event.

Responsible AI in fintech: Balancing innovation with trust, risk, and compliance

The article examines the growing role of artificial intelligence within the financial technology sector, focusing closely on the need to balance new capabilities with trust, risk management, and regulatory compliance. As financial institutions increasingly adopt these systems for routine tasks like fraud detection, customer service, and credit scoring, they face significant practical challenges in ensuring their models operate fairly and transparently. A primary concern is that automated systems can unintentionally reproduce human biases, leading to unfair outcomes in lending or account access. To prevent this, companies must establish clear, sensible guidelines for developing and monitoring their algorithms. The text emphasizes that maintaining customer trust requires being straightforward about how decisions are made and how personal data is actually used. Financial organizations also need strong oversight frameworks to handle risks associated with data privacy and system errors effectively. Furthermore, the evolving regulatory environment means that firms must stay current with new laws designed specifically to protect consumers and maintain market stability. Ultimately, the successful integration of these tools in finance depends entirely on a measured approach. By prioritizing ethical practices and strong governance, financial technology companies can improve their services while protecting their customers and meeting their legal obligations responsibly.

Daily Tech Digest - August 24, 2025

Quote for the day:

"To accomplish great things, we must not only act, but also dream, not only plan, but also believe." -- Anatole France

Creating the ‘AI native’ generation: The role of digital skills in education

Boosting AI skills has the potential to drive economic growth and productivity and create jobs, but ambition must be matched with effective delivery. We must ensure AI is integrated into education in a way that encourages students to maintain critical thinking skills, skeptically assess AI outputs, and use it responsibly and ethically. Education should also inspire future tech talent and prepare them for the workplace. ... AI fluency is only one part of the picture. Amid a global skills gap, we also need to capture the imaginations of young people to work in tech. To achieve this, AI and technology education must be accessible, meaningful, and aspirational. That requires coordinated action from schools, industry, and government to promote the real-world impact of digital skills and create clearer, more inspiring pathways into tech careers and expose students how AI is applied in various professions. Early exposure to AI can do far more than build fluency, it can spark curiosity, confidence and career ambition towards high-value sectors like data science, engineering and cybersecurity—areas where the UK must lead. ... Students who learn how to use AI now will build the competencies that industries want and need for years to come. But this will form the first stage of a broader AI learning arc where learning and upskilling become a lifelong mindset, not a single milestone.

What is the State of SIEM?

In addition to high deployment costs, many organizations grapple with implementing SIEM. A primary challenge is SIEM configuration -- given that the average organization has more than 100 different data sources that must plug into the platform, according to an IDC report. It can be daunting for network staff to do the following when deploying SIEM: Choose which data sources to integrate; Set up SIEM correlation rules that define what will be classified as a security event; and Determine the alert thresholds for specific data and activities. It's equally challenging to manage the information and alerts a SIEM platform issues. If you fine-tune too much, the result might be false positives as the system triggers alarms about events that aren't actually threats. This is a time-stealer for network techs and can lead to staff fatigue and frustration. In contrast, if the calibration is too liberal, organizations run the risk of overlooking something that could be vital. Network staff must also coordinate with other areas of IT and the company. For example, what if data safekeeping and compliance regulations change? Does this change SIEM rule sets? What if the IT applications group rolls out new systems that must be attached to SIEM? Can the legal department or auditors tell you how long to store and retain data for eDiscovery or for disaster backup and recovery? And which data noise can you discard as waste?

AI Data Centers: A Popular Term That’s Hard to Define

The tricky thing about trying to define AI data centers based on characteristics like those described above is that none of those features is unique to AI data centers. For example, hyperscale data centers – meaning very large facilities capable of accommodating more than a hundred thousand servers in some cases – existed before modern AI debuted. AI has made large-scale data centers more important because AI workloads require vast infrastructures, but it’s not as if no one was building large data centers before AI rose to prominence. Likewise, it has long been possible to deploy GPU-equipped servers in data centers. ... Likewise, advanced cooling systems and innovative approaches to data center power management are not unique to the age of generative AI. They, too, predated AI data centers. ... Arguably, an AI data center is ultimately defined by what it does (hosting AI workloads) more than by how it does it. So, before getting hung up on the idea that AI requires investment in a new generation of data centers, it’s perhaps healthier to think about how to leverage the data centers already in existence to support AI workloads. That perspective will help the industry avoid the risk of overinvesting in new data centers designed specifically for AI – and as a bonus, it may save money by allowing businesses to repurpose the data centers they already own to meet their AI needs as well.

Password Managers Vulnerable to Data Theft via Clickjacking

Tóth showed how an attacker can use DOM-based extension clickjacking and the autofill functionality of password managers to exfiltrate sensitive data stored by these applications, including personal data, usernames and passwords, passkeys, and payment card information. The attacks demonstrated by the researcher require 0-5 clicks from the victim, with a majority requiring only one click on a harmless-looking element on the page. The single-click attacks often involved exploitation of XSS or other vulnerabilities. DOM, or Document Object Model, is an object tree created by the browser when it loads an HTML or XML web page. ... Tóth’s attack involves a malicious script that manipulates user interface elements injected by browser extensions into the DOM. “The principle is that a browser extension injects elements into the DOM, which an attacker can then make invisible using JavaScript,” he explained. According to the researcher, some of the vendors have patched the vulnerabilities, but fixes have not been released for Bitwarden, 1Password, iCloud Passwords, Enpass, LastPass, and LogMeOnce. SecurityWeek has reached out to these companies for comment. Bitwarden said a fix for the vulnerability is being rolled out this week with version 2025.8.0. LogMeOnce said it’s aware of the findings and its team is actively working on resolving the issue through a security update.

Iskraemeco India CEO: ERP, AI, and the future of utility leadership

We see a clear convergence ahead, where ERP systems like Infor’s will increasingly integrate with edge AI, embedded IoT, and low-code automation to create intelligent, responsive operations. This is especially relevant in utility scenarios where time-sensitive data must drive immediate action. For instance, our smart kits – equipped with sensor technology – are being designed to detect outages in real time and pinpoint exact failure points, such as which pole needs service during a natural disaster. This type of capability, powered by embedded IoT and edge computing, enables decisions to be made closer to the source, reducing downtime and response lag. ... One of the most important lessons we've learned is that success in complex ERP deployments is less about customisation and more about alignment, across leadership, teams, and technology. In our case, resisting the urge to modify the system and instead adopting Infor’s best-practice frameworks was key. It allowed us to stay focused, move faster, and ensure long-term stability across all modules. In a multi-stakeholder environment – where regulatory bodies, internal departments, and technology partners are all involved – clarity of direction from leadership made all the difference. When the expectation is clear that we align to the system, and not the other way around, it simplifies everything from compliance to team onboarding.

Experts Concerned by Signs of AI Bubble

"There's a huge boom in AI — some people are scrambling to get exposure at any cost, while others are sounding the alarm that this will end in tears," Kai Wu, founder and chief investment officer of Sparkline Capital, told the Wall Street Journal last year. There are even doubters inside the industry. In July, recently ousted CEO of AI company Stability AI Emad Mostaque told banking analysts that "I think this will be the biggest bubble of all time." "I call it the 'dot AI’ bubble, and it hasn’t even started yet," he added at the time. Just last week, Jeffrey Gundlach, billionaire CEO of DoubleLine Capital, also compared the AI craze to the dot com bubble. "This feels a lot like 1999," he said during an X Spaces broadcast last week, as quoted by Business Insider. "My impression is that investors are presently enjoying the double-top of the most extreme speculative bubble in US financial history," Hussman Investment Trust president John Hussman wrote in a research note. In short, with so many people ringing the alarm bells, there could well be cause for concern. And the consequences of an AI bubble bursting could be devastating. ... While Nvidia would survive such a debacle, the "ones that are likely to bear the brunt of the correction are the providers of generative AI services who are raising money on the promise of selling their services for $20/user/month," he argued.

OpenCUA’s open source computer-use agents rival proprietary models from OpenAI and Anthropic

Computer-use agents are designed to autonomously complete tasks on a computer, from navigating websites to operating complex software. They can also help automate workflows in the enterprise. However, the most capable CUA systems are proprietary, with critical details about their training data, architectures, and development processes kept private. “As the lack of transparency limits technical advancements and raises safety concerns, the research community needs truly open CUA frameworks to study their capabilities, limitations, and risks,” the researchers state in their paper. ... The tool streamlines data collection by running in the background on an annotator’s personal computer, capturing screen videos, mouse and keyboard inputs, and the underlying accessibility tree, which provides structured information about on-screen elements. ... The key insight was to augment these trajectories with chain-of-thought (CoT) reasoning. This process generates a detailed “inner monologue” for each action, which includes planning, memory, and reflection. This structured reasoning is organized into three levels: a high-level observation of the screen, reflective thoughts that analyze the situation and plan the next steps, and finally, the concise, executable action. This approach helps the agent develop a deeper understanding of the tasks.

How to remember everything

MyMind is a clutter-free bookmarking and knowledge-capture app without folders or manual content organization.There are no templates, manual customizations, or collaboration tools. Instead, MyMind recognizes and formats the content type elegantly. For example, songs, movies, books, and recipes are displayed differently based on MyMind’s detection, regardless of the source, as are pictures and videos. MyMind uses AI to auto-tag everything and allows custom tags. Every word, including those in pictures, is indexed. You can take pictures of information, upload them to MyMind, and find them later by searching a word or two found in the picture. Copying a sentence or paragraph from an article will display the quote with a source link. Every data chunk is captured in a “card.” ... Alongside AI-enabled lifelogging tools like MyMind, we’re also entering an era of lifelogging hardware devices. One promising direction comes from a startup called Brilliant Labs. Its new $299 Halo glasses, available for pre-order and shipping in November, are lightweight AI glasses. The glasses have a long list of features — bone conduction sound, a camera, light weight, etc. — but the lifelogging enabler is an “agentic memory” system called Narrative. It captures information automatically from the camera and microphones and places it into a personal knowledge base.

From APIs to Digital Twins: Warehouse Integration Strategies for Smarter Supply Chains

Digital twins create virtual replicas of warehouses and supply chains for monitoring and testing. A digital twin ingests live data from IoT sensors, machines, and transportation feeds to simulate how changes affect outcomes. For instance, GE’s “Digital Wind Farm” project feeds sensor data from each turbine into a cloud model, suggesting performance tweaks that boost energy output by ~20% (worth ~$100M more revenue per turbine). In warehousing, digital twins can model workflows (layout changes, staffing shifts, equipment usage) to identify bottlenecks or test improvements before physical changes. Paired with AI, these twins become predictive and prescriptive: companies can run thousands of what-if scenarios (like a port strike or demand surge) and adjust plans accordingly. ... Today’s warehouses are not just storage sheds; they are smart, interconnected nodes in the supply chain. Leveraging IIoT sensors, cloud APIs, AI analytics, robotics, and digital twins transforms logistics into a competitive advantage. Integrated systems reduce manual handoffs and errors: for example, automated picking and instant carrier booking can shorten fulfillment cycles from days to hours. Industry data bear this out, deploying these technologies can improve on-time delivery by ~20% and significantly lower operating costs.

Enterprise Software Spending Surges Despite AI ROI Shortfalls

AI capabilities increasingly drive software purchasing decisions. However, many organizations struggle with the gap between AI promise and practical ROI delivery. The disconnect stems from fundamental challenges in data accessibility and contextual understanding. Current AI implementations face significant obstacles in accessing the full spectrum of contextual data required for complex decision-making. "In complex use cases, where the exponential benefits of AI reside, AI still feels forced and contrived when it doesn't have the same amount and depth of contextual data required to read a situation," Kirkpatrick explained. Effective AI implementation requires comprehensive data infrastructure investments. Organizations must ensure AI models can access approved data sources while maintaining proper guardrails. Many IT departments are still working to achieve this balance. The challenge intensifies in environments where AI needs to integrate across multiple platforms and data sources. Well-trained humans often outperform AI on complex tasks because their experience allows them to read multiple factors and adjust contextually. "For AI to mimic that experience, it requires a wide range of data that can address factors across a wide range of dimensions," Kirkpatrick said. "That requires significant investment in data to ensure the AI has the information it needs at the right time, with the proper context, to function seamlessly, effectively, and efficiently."

Daily Tech Digest - August 12, 2022

7 best reasons to be a CISO

As they become key players in wider business matters, modern CISOs can develop their credentials and knowledge beyond hands-on security skills and abilities. “Our role is continuously expanding,” Smart says. “Today, I am also responsible for governance, risk and compliance, which opens up more avenues into setting a cohesive plan and strategy for security and risk management that impacts the whole business,” she adds. “The modern CISO can make use of a wide range of skills, beyond technical cybersecurity, and explore more areas of interest within the business,” Stapleton agrees. “As the cybersecurity landscape is constantly changing, there are always new and fascinating topics to dive into, so a CISO is never bored.” “The Disabled CISO,” the Twitter handle of an anonymous CISO of a global company, tells CSO that security now touches every part of the business, driving CISOs to positively engage with and learn from all corners of a company. “I love getting out and joining colleagues at the coalface. To protect the business, I need to understand how we operate and the challenges that presents to colleagues ..."

Should We Build Quantum Computers at All?

Using quantum computers, physicists want to simulate and unearth unusual states of matter; pharmaceutical companies want to discover new types of drugs; auto companies want to paint cars faster. While no one has conclusively demonstrated the utility of quantum computers, their potential seems endless. Emma McKay offers a provocative counterpoint. In the face of climate change, societal inequality, and other global problems, McKay, a PhD student in education at McGill University, thinks that perhaps we don’t need to develop quantum computing at all. “I haven’t seen any reasons compelling enough to me,” McKay, who uses they/them pronouns, told APS News. ... Maybe quantum annealers [a type of quantum computer] will be able to help us manage resources more efficiently. But it appears that people are most interested in using these types of technology to optimize things that suck, like optimizing traffic for single-person vehicles when widely available public transit, via buses and cycling infrastructure, is possible and the best way to reduce congestion and pollution from private vehicles in a city.

Are Application-Specific Chains the Future of Blockchain?

As decentralized application (dApps) developers gain more experience working with blockchains, some are running into limitations created by the parameters of blockchain architecture. Ethereum, for instance, allows for applications to be created via smart contracts, but does not allow for automatic execution of code. It also maintains fairly strict control over the way consensus and networking functions are exposed to those applications. To overcome these limitations, some developers are turning to application-specific blockchains — purpose-built and tuned for their specific application needs, and colloquially called “appchains.” One of the more popular options for building appchains is the Cosmos SDK, due to built-in composability, interconnected blockchains, and the ability for developers to maintain sovereignty over their blockchain. We’ve covered Cosmos in the past, including a developer academy for learning to build in the Cosmos Network and the addition of Interchain Security, which allows multiple Cosmos blockchains to align around common security protocols while maintaining sovereignty.

A Long-Awaited IoT Reverse Engineering Tool Is Finally Here

The tool was specifically designed to elucidate internet-of-things (IoT) device firmware and the compiled “binaries” running on anything from a home printer to an industrial door controller. Dubbed FRAK, the Firmware Reverse Analysis Console aimed to reduce overhead so security researchers could make progress assessing the vast and ever-growing population of buggy and vulnerable embedded devices rather than getting bogged down in tedious reverse engineering prep work. Cui promised that the tool would soon be open source and available for anyone to use. “This is really useful if you want to understand how a mysterious embedded device works, whether there are vulnerabilities inside, and how you can protect these embedded devices against exploitation,” Cui explained in 2012. “FRAK will be open source very soon, so we’re working hard to get that out there. I want to do one more pass, internal code review before you guys see my dirty laundry.” He was nothing if not thorough. A decade later, Cui and his company, Red Balloon Security, are launching Ofrak, or OpenFRAK, at DefCon in Las Vegas this week.

Is cloud computing immune from economic downturns?

First, and most important, many businesses now consider IT spending to be directly reflected in the value built within the enterprise. IT systems are no longer just for tactical uses such as processing transactions. Instead, cloud systems are becoming the business itself. The businesses disrupting their markets are doing so with their own unique innovations. They can only create these innovations by developing core IT systems using digital transformation processes and cloud computing. IT is no longer a cost center but an investment that needs to be nurtured. This new outlook is seen in manufacturing companies invested in supply chain automation using cloud-based artificial intelligence capabilities and cloud-based blockchain to lower costs and increase productivity. It’s seen in businesses that are entirely based on technology offerings, such as ride-sharing or residence-sharing applications. Many investors and company executives now believe software will define the future of business. IT is the engine that can build and use these systems; thus it’s a budgetary line item that boards and executives are reluctant to touch.

Cybersecurity and Technology Industry Leaders Launch Open-Source Project to Help Organizations Detect and Stop Cyberattacks Faster and More Effectively

"Every business deserves a simple, straightforward way to analyze and understand the security landscape – and that starts with their data," said John Graham-Cumming, CTO at Cloudflare. "By participating in the OCSF, we hope to help the entire security industry focus on doing the work that matters instead of wasting countless hours and resources on formatting data." "At CrowdStrike, our mission is to stop breaches and power productivity for organizations," said Michael Sentonas, Chief Technology Officer, CrowdStrike. "We believe strongly in the concept of a shared data schema, which enables organizations to understand and digest all data, streamline their security operations and lower risk. As a member of the OCSF, CrowdStrike is committed to doing the hard work to deliver solutions that organizations need to stay ahead of adversaries." "Modern cybersecurity operations is a team sport, and products must integrate with each other to provide value beyond what a single product can. Sure, it's possible to make that happen with open APIs and mapping data structures, but development and processing resources are not infinite," said Mohan Koo, Co-founder and CTO with DTEX Systems.

What Are Your Decision-Making Strengths and Blind Spots?

What do you do when you face an important but complicated decision? Do you turn to experts? Dig for data? Ask trusted friends and colleagues? Go with your gut? The truth is many of us approach decision making from the same perspective over and over. We use the same tools and habits every time, even if the decisions are vastly different. But following the same strategy for every problem limits your abilities. To make better decisions, you need to break out of these patterns and see things differently, even if it is uncomfortable. First, you need to understand your own decision-making strengths and your blind spots: What is the psychology of your decision making? What is your typical approach? What mental mistakes or cognitive biases tend to get in your way? Looking inward to what you value can illuminate why you make decisions the way you do — and how you might be shortchanging yourself with your approach. From there, you can disrupt your traditional processes.

The Rise of the ‘Fractional’ CMO and the Role CIOs Play

Relay Network 's CMO Tal Klein points out the CIO/CDO has a vested interest in the interplay of technology and business. “Depending on what marketing pillar the fractional CMO is being brought onboard to address, the CIO may care a lot if the fractional CMO is being brought in to address operational issues like lead generation or lead-to-opportunity conversion velocity,” he says. That's because that kind of work relies heavily on technology and may impact changes to the company's CRM, website, or even communication infrastructure. “Whereas if the fractional CMO is being brought it to address messaging or market positioning, the CIO may have less of a vested stake in the recruitment efforts,” Klein says. Klein adds other than the obvious infrastructure work associated with supporting marketing operations, the CIO or CDO may own a lot of the outputs from marketing engagements like the compliance issues. These could arise from capturing customer information, security ramifications associated with new tools or processes, and ensuring whatever prospect or customer data marketing needs in order to run effective campaigns is available to them.

Hybrid work: What's changed – and what hasn't

With an overwhelming number of employees saying they want hybrid work to become the new normal, flexible work arrangements are becoming integral to an organization’s hiring and retention strategies. Pre-pandemic, industries that offered work flexibility were often considered somewhat progressive and it was more the exception than the norm. Today, hybrid work is standard in a growing number of fields. Still, there are challenges. ... With employees potentially using personal devices and home wi-fi connections, IT security teams must constantly consider new vulnerabilities and strategies to remain safe. Clear policies and practices, along with training programs that reflect these new procedures are essential for any successful hybrid work model. On the positive side, hybrid work reduces the impact on our environment. Working remotely means less paper consumption and energy used to maintain office buildings and less waste from consumable products in the workplace. It also provides team members an opportunity to practice sustainability when working at home.

Why SAP systems need to be brought into the cybersecurity fold

The problem is exacerbated by the variety of attack vectors that cybercriminals are leveraging to target mission critical SAP systems, with applications often remaining vulnerable for extended periods due to security patches not being applied in a timely manner. In February we saw the Cybersecurity and Infrastructure Security Agency (CISA) urge admins to patch SAP NetWeaver against a critical vulnerability that could facilitate a range of attacks and even lead to operational shutdown. In the very same month, of the 22 security notes or updates issued by SAP, eight were deemed “Hot News”. Four were updates but of the remainder, three had a maximum CVSS score of 10 and the fourth 9.1. SAP is prolific in its patching. However, patches cannot be applied directly to productive systems, requiring downtime which is often not an option for mission-critical systems. Even when a business upgrades to SAP S/4HANA, the pressure to go-live can see security side-lined. ... Indeed, the earlier mentioned report reveals that exploits are attempted within 72 hours of SAP publicly announcing patches, while new SAP environments are being identified and attacked online within as little as three hours.

Quote for the day:

"I have a different vision of leadership. A leadership is someone who brings people together." -- George W. Bush

Daily Tech Digest - June 16, 2022

High-Bandwidth Memory (HBM) delivers impressive performance gains

In addition to widening the bus in order to boost bandwidth, HBM technology shrinks down the size of the memory chips and stacks them in an elegant new design form. HBM chips are tiny when compared to graphics double data rate (GDDR) memory, which it was originally designed to replace. 1GB of GDDR memory chips take up 672 square millimeters versus just 35 square millimeters for 1GB of HBM. Rather than spreading out the transistors, HBM is stacked up to 12 layers high and connected with an interconnect technology called ‘through silicon via’ (TSV). The TSV runs through the layers of HBM chips like an elevator runs through a building, greatly reducing the amount of time data bits need to travel. With the HBM sitting on the substrate right next to the CPU or GPU, less power is required to move data between CPU/GPU and memory. The CPU and HBM talk directly to each other, eliminating the need for DIMM sticks. “The whole idea that [we] had was instead of going very narrow and very fast, go very wide and very slow,” Macri said.

3 forces shaping the evolution of ERP

If there was any hesitation about moving to cloud-based ERP, it was quashed as the COVID crisis erupted, and corporate workplaces became scattered across countless home-based offices. On-premises ERP is seen as “not as scalable as people thought,” says Sharon Bhalaru, partner at accounting and technology consulting firm Armanino LLP. “We’re seeing a move to cloud-based systems,” to support remote employees who need to perform HR, financial and accounting tasks remotely. ... Next-generation ERP platforms “give companies real-time transparency with respect to sales, inventory, production, and financials,” the Boston Consulting Group analysts wrote. “Powerful data-driven analytics enables more agile decisions, such as adjustments to the supply chain to improve resilience. Robust e-commerce capabilities help companies better engage with online customers before and after a sale. And a lean ERP core and cloud-first approach increase deployment speed.” ... Unprecedented and ongoing supply chain disruptions underscore the need for greater visibility, more predictable lead times, alternative supply sources, and faster response to disruptions.

Interpol arrests thousands in global cyber fraud crackdown

The operation’s targets included telephone scammers, long-distance romance scammers, email fraudsters and other connected financial criminals, identified through a prior intelligence operation using Interpol’s secure global comms network, sharing data on suspects, suspicious bank accounts, unlawful transactions, and communications means such as phone numbers, email addresses, fake websites and IP addresses. “Telecom and BEC fraud are sources of serious concern for many countries and have a hugely damaging effect on economies, businesses and communities,” said Rory Corcoran. “The international nature of these crimes can only be addressed successfully by law enforcement working together beyond borders, which is why Interpol is critical to providing police the world over with a coordinated tactical response.” Duan Daqi, added: “The transnational and digital nature of different types of telecom and social engineering fraud continues to present grave challenges for local police authorities, because perpetrators operate from a different country or even continent than their victims and keep updating their fraud schemes.

Is Cyber Essentials Enough to Secure Your Organisation?

If you are to have confidence in your security controls, you must implement defence in depth. This requires a holistic approach to cyber security that addresses people, processes and technology. Key aspects of this aren’t addressed in Cyber Essentials, such as staff awareness training, vulnerability scanning and incident response. Employees are at the heart of any cyber security system, because they are the ones responsible for handling sensitive information. If they don’t understand their data protection requirements, it could result in disaster. Meanwhile, vulnerability scanning ensures that organisations can spot weaknesses in their systems before a cyber criminal can exploit them. It’s a more advanced form of protection than is offered with secure configuration and system updates, enabling organisations to proactively secure their systems. Conversely, incident response measures give organisations the tools they need to respond after a security incident has occurred. Most of the damage caused by a data breach occurs after the initial intrusion, so a prompt and organised response can be the difference between a minor disruption and a catastrophe.

Imagining a world without open standards

The open standard makes portability easier for software developers, provides integrators with choice in the building blocks for solutions, and enables customers to focus on solving business problems rather than integration issues. Open standards eliminate the need for organizations to expend energy wrangling with competitors on defining how systems should work, giving them the space and time to focus on building and improving how those systems actually do work. The real benefits, though, are downstream of vendors: open standards mean that businesses can effectively communicate and collaborate both internally and with peers. They mean that the expertise built up by a professional in one market or business can be taken with them wherever they want to work. They mean that a lack of knowledge resources is not the barrier that prevents businesses from making the move towards better, more efficient ways of working. In imagining a world without open standards, then, the image is one of businesses constantly having to navigate between the walled gardens of different technology vendors, reskilling and rehiring as they do so, before they can even begin the serious work of delivering value from that technology.

Good Habits That Every Programmer Should Have

We can become good at a specific technology by working with a particular technology for a long time. How can we become an expert in a specific technology? Learning internals is a great habit that supports us to become an expert in any technology. For example, after working some time with Git, you can learn Git internals via the lesser-known plumbing commands. You can make accurate technical decisions when you understand the internals of your technology stack. When you learn internals, you will indeed become more familiar with the limitations and workarounds of a specific technology. Learning internals also helps us to understand what we are doing with programming every day. Motivate everyone to learn further about their tools’ internals! ... Sometimes, we derive programming solutions from example code snippets that we can find on internet forums. It’s a good habit to give credit to other programmers’ hard work when we use their code snippets, libraries, and tools, even though their licensing documents say that attribution is not required.

Reducing Cybersecurity Security Risk From and to Third Parties

There are a number of ways in which organizations may be able to obtain attack information from third parties, if they agree. Ideally, such requirements should be included in service agreements and partnership contracts for vendors, outsourcers, and partners, as listed in the article, “Using Contracts to Reduce Cybersecurity Risks.” Employment contracts, nondisclosure agreements and license agreements may also include requirements that protect organizations against third-party risk. While it is helpful to request vendors, outsourcers and partners to commit to risk reduction in the contractual terms and conditions, it is even more beneficial for an organization to have direct access to partners’ and suppliers’ security monitoring systems. ... More modern forms of protection monitor messages for origin and content and respond with information about unauthorized sources—as with IDSs—or preventive action—as with IPSs. Advancements in these systems include observation of unusual behavior and the use of artificial intelligence (AI) to determine threats.

How Upskilling Could Resolve The Cybersecurity Skills Gap

With a shortage of new candidates, upskilling provides the answer to the cybersecurity skills gap. And it brings multiple benefits for both employees and businesses. One of the first is that, ultimately, cybersecurity is everyone’s business. From the CEO to the new employee at home, everyone has a role to play in ensuring systems are robust in the face of a growing wave of attacks. While this does not mean that everyone in a company needs to be a cybersecurity professional, it does mean that everyone should be aware of the risks, how to spot potential vulnerabilities and attacks and the practical measures they must take to prevent them. However, it can also produce a supply of cybersecurity professionals. Waiting for qualified entrants to the jobs market will take too long and, in practice, it’s likely they will not be qualified for long! The cybersecurity environment changes so rapidly, the knowledge many graduates gain at the start of their course may not be relevant by the end. Instead, identifying existing staff with the soft skills,or power skills, to develop, adapt, and learn may be the quickest and easiest path to take.

12 tips for achieving IT agility in the digital era

“If your tech stack is streamlined, easy to access, and easy to use, your workforce can quickly respond to business or customer needs seamlessly,” says Fleetcor’s duFour. Key to this is getting a handle on application sprawl by rationalizing the IT portfolio. Voya Financial’s simplification journey began with such an effort, a process that reduced its application footprint by 17% and its slate of technology tools by one quarter. The work continues as part of its cloud migration work. “This practice is instilling standards and discipline that will only help to ensure our environment remains uncluttered and contemporary for the long term,” Keshavan says. As a result, the IT group is faster and more flexible, recently deploying five new cloud services for data science and analytics developers to use within four hours —something that would have taken a cross-functional IT team several weeks to deploy in the past. Reining in application sprawl has also been valuable at Snow Software. “Oftentimes, companies and teams will invest in applications with similar purposes,” says Snow Software CIO Alastair Pooley.

True Component-Testing of the GUI With Karate Mock Server

There’s an important reason why old-style end-to-end tests are often more expensive than needed: you tend to test paths that are not relevant to the frontend logic. Each of these adds to the total test suite run. Consider a web application for your tax return. The user journey in this non-trivial app consists of submitting a series of questionnaires, their content customized depending on what you answered in previous steps. There is likely some logic on the frontend to manage the turns in that user journey, but the number-crunching over your sources of income and deductibles surely happens on the backend. You don’t need a GUI test to validate the correctness of those calculations. With a mock backend that would be entirely pointless. You set it up to tell the frontend that the final amount to pay is 12600 Euros. You can test that this amount is properly displayed, but there’s no testing its correctness. All the decisions are made (and hopefully tested) elsewhere, so we can treat it as a hardcoded test fixture.

Quote for the day:

"Leaders begin with a different question than others. Replacing who can I blame with how am I responsible?" -- Orrin Woodward