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At a park near Canberra, Australia, a series of small white pyramid-shaped boxes are part of a new experiment: Can frog saunas help bring back an endangered species? The green and golden bell frogan iconic Australian amphibian with a call that sounds like a cross between a power tool and a quacking duckis already extinct in the area. Like other frog species around the world, it was a victim of a deadly fungus called chytrid that has been killing amphibians for decades. But scientists are reintroducing the vibrant frog with the hope that a design intervention can help it survive. [Photo: courtesy Simon Clulow/University of Canberra] The sauna is a simple design, with bricks inside a plastic enclosure that heats up in the sun. The bell frog loves sitting in the heatand conveniently the high temperatures kill the fungus. The technology we’re using is extremely low tech, said Simon Clulow, a conservation ecology professor at the University of Canberra leading the research. Thats good because everything we do in science and conservation, ideally, we want to be accessible, affordable, and scalable. [Photo: Tyler Cherry/University of Canberra] A new intervention backed by years of research Clulow started thinking about the idea as a doctoral student, when he noticed that frogs in a university enclosure liked to sit in the holes inside bricks, probably because they could hide away and feel warmer. At the same time, he knew that the chytrid fungus was most dangerous when frogs got cold. That led to this idea: Could you create essentially pockets of disease refuge by creating little hot spots in the environment? he said. [Photo: Tyler Cherry/University of Canberra] Along with other researchers, he initially tested bricks that were painted black, but they didn’t get quite warm enough, so the small plastic greenhouse was added to help keep the bricks hotter. Research has shown that this type of environment makes a difference. “We know for sure if we hold the frogs in a temperature-controlled cabinet at those sorts of temperatures for even just a couple of days, it usually leads to complete clearance [of the fungus],” Clulow said. “But even just short-term spikes clearly have beneficial effects.” The green and golden bell frog used to be common on Australias eastern seaboard. It was widespread in every farm, in everyones ponds, and it was just one of those frogs probably nobody took much notice of because it was absolutely everywhere, Clulow said. Universities often went out to collect the frogs for use in biology classes. Then, in the 1980s, the fungus devastated the population, along with other species of frogs. Only a few isolated pockets of the green and golden bell frogs were left on the coast. [Photo: Tyler Cherry/University of Canberra] The places where the frogs survived were a little warmer in the winter, with water that was slightly more saline. That led to the second part of the intervention in the new studytiny ponds with slightly saltier water, which research has shown also kills the fungus without harming the frogs. (The salinity is only about two or three parts per thousand, not enough to taste salty if you drank the water.) The scientists call the small saline ponds spas, and they’re set up next to the saunas. The new experiment is the largest of its kind. The research team installed 15 experimental wetlands sprawling over hundreds of square miles in Australias Capital Territory, with some areas acting as a control to see how well the interventions work. Theyve released around 450 frogs so far this year; the first generation was raised in captivity and given the extra boost of a vaccine against chytrid. The next generation, born in the wild, will rely on the saunas and spas to treat the fungus. [Photo: Tyler Cherry/University of Canberra] The real-world test When we talked, Clulow had been up until 3 a.m. the previous night tracking the newly released frogs. They’re not hard to spot. “They have a really fantastic, obvious call, a little bit like a motorbike revving up,” he said, demonstrating the sound. The frogs have microchips so they can be tracked. So far, roughly a month after the first frogs were released, the population is thriving. [Photo: Tyler Cherry/University of Canberra] The first big test for the project will be in the upcoming Australian winter (during the North American summer), and then the following winter when the new generation of frogs will need to survive. The outside temperature can dip to negative 5 degrees Celsius, or 23 degrees Fahrenheit. Inside the tiny saunas, it can stay a toasty 77 to 86 degrees Fahrenheit. The research team still needs to prove that the interventions work as well in the wild as they did in the lab, but the solution could potentially be replicated around the world. At least 90 species of frogs have gone extinct because of the fungus; hundreds of others are at risk.
Category:
E-Commerce
A new word has entered the business headline writers lexicon over the last month: the SaaSpocalypse. Between mid-January and mid-February 2026, around a trillion dollars was wiped from the value of software stocks. The S&P North American Software Index posted its worst monthly decline since the 2008 financial crisis. Individual stocks have been savaged, with even Microsoft, the ultimate tech blue chip, falling by more than 10%. The panic is real. But is it rational? The catalyst for this turmoil was a series of product launches from AI companiesmost notably Anthropics Claude Cowork tool and its subsequent upgradesdemonstrating that AI agents are now capable of handling complex knowledge work autonomously. The markets interpretation was both swift and brutal: If AI agents can do what enterprise software does, then enterprise software is finished. That narrative is clearly persuasive to those who have been busily dumping stocks. But it rests on a fundamental misunderstanding of what enterprise software is, what it does, and why replacing it isnt the straightforward proposition the market appears to believe. {"blockType":"mv-promo-block","data":{"imageDesktopUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/10\/creator-faisalhoque.png","imageMobileUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/10\/faisal-hoque.png","eyebrow":"","headline":"Ready to thrive at the intersection of business, technology, and humanity?","dek":"Faisal Hoques books, podcast, and his companies give leaders the frameworks and platforms to align purpose, people, process, and techturning disruption into meaningful, lasting progress.","subhed":"","description":"","ctaText":"Learn More","ctaUrl":"https:\/\/faisalhoque.com","theme":{"bg":"#02263c","text":"#ffffff","eyebrow":"#9aa2aa","subhed":"#ffffff","buttonBg":"#ffffff","buttonHoverBg":"#3b3f46","buttonText":"#000000"},"imageDesktopId":91420512,"imageMobileId":91420514,"shareable":false,"slug":""}} More Than a Tool The simple premise behind the market turmoil is that AI agents will, in the not-too-distant future, be able to perform most or all of the tasks that are currently performed by enterprise software. But this vision of the future misunderstands enterprise software at a fundamental level. Enterprise software isnt just a set of tools. It encodes the enterprise itself. Decades of business rules, process flows, governance structures, compliance requirements, data definitions, and role-based permissions are held within these systems. When a company runs on SAP, Salesforce, Microsoft, or ServiceNow products, its not simply using a suite of software that sits on top of the organization. These systems hold the organizations operating architecture in digital formthe institutional memory of how the business actually works in practice, every day, at every level. Replacing enterprise software with a fully agentic enterprise isnt just a matter of swapping one piece of technology for another. The moat around enterprise software isnt the code. Its the accumulated domain knowledge, the business logic, and the deep integration with how organizations actually operate. Three Fallacies Driving the Panic The case for wholesale replacement rests on three assumptions. Each collapses under scrutiny. The first is the change management fallacy. Putting enterprise software in place is not like installing an app; these are often multiyear organizational transformations involving workflow redesign, data migration, retraining, and deep integration across departments. Companies typically change ERP systems every 5 to 10 years, and even routine migrations require months of rigorous preparation. The notion that organizations will undertake wholesale replacement of their entire enterprise architecturenot with new software, but with an entirely different paradigmignores the reality that change management is one of the hardest things organizations can attempt. The disruption involved in even incremental software upgrades creates significant operational risk. A complete paradigm shift involves risks to the business of an entirely different order of magnitude. The second is the economic fallacy. Even if replacement were technically feasible, there is no compelling reason to believe it would be cheaper. Token-based AI pricing is expensive at the enterprise scale, and the world in which running agents across an entire organizations operations could cost less than current SaaS subscriptions is not yet the world in which we live. Token costs will fall over timewe can be sure of thatbut building a case for wholesale replacement on the assumption that they will fall far enough and fast enough to undercut the established economics of enterprise software involves stacking assumption on top of assumption. Token costs are only one part of the equation. The true cost of running agentic systems includes orchestration, integration, data pipelines, monitoring, security, auditability, and the human time required to supervise and correct outputs. The last item is the one most easily underestimated: As agents take on more autonomous and more consequential work, assurance costs will rise, not fall. And even before you reach the question of ongoing costs, the price of the transition itselfthe data migration, workflow redesign, retraining, and inevitable disruption to operationswould be enormous. The economic argument for replacement isnt just weak; at present, it barely exists. This isnt to say that its not plausible in some future world. But until we have a convincing map that leads there, its not a serious proposition. The third, and possibly the most important, is the general-purpose agent fallacy. The assumption behind the market panic is that powerful, general-purpose AI agents will take over enterprise functions wholesale. But this doesnt reflect how AI actually delivers value today, and it may not reflect how agents ever deliver value. Research consistently shows that AI works best when its targeted at specific problems with rich contextual grounding. A study conducted by the Australian government found that broad-access AI tools produced significant improvements in basic tasks like summarizing information and preparing first drafts, but that their lack of fit to users specific contexts undermined efficiency gains in more complex work. The result was a productivity paradox: Time saved through automation was consumed by checking and correcting outputs that lacked the domain-specific nuance the work required. This finding has direct implications for the SaaSpocalypse thesis. General-purpose agents deployed to replace enterprise software will face exactly the same problem. Without deep local contextthe profound domain knowledge and specific workflow logic that enterprise software encodesthey will produce generic, unreliableoutputs that require constant human correction. To work effectively at the enterprise level, agents need to be narrow, contextually rich, and tightly integrated with specific workflows. And once you start building agents that way, youre not replacing software as a service. Youre rebuilding it through an agentic lensat enormous cost and with no guarantee that the result will be better than what you already have. What Leaders Should Do None of this means the landscape isnt shifting. AI is changing how people interact with software and how organizations think about their technology investments. But the right response isnt to tear up the enterprise architecture. Its to evolve it. Rather than reacting to the panic, leaders should take three concrete steps. 1. Audit your vendors AI road maps. The strongest enterprise software providers are already integrating agentic capabilities into their platforms. If yours arent, thats a genuine concern, and it may be time to look for vendors who are. The question isnt whether to adopt AI, but whether your existing partners are doing it for you. 2. Invest in data quality and process documentation. The effectiveness of any AIwhether embedded in your software or deployed as agentsdepends on the quality of the data and the clarity of the processes it works with. This is the foundational investment, and it pays off regardless of where the technology lands. 3. Evaluate agentic approaches for genuinely new workflows. Where youre building new capabilities or addressing needs that your current software stack does not serve, purpose-built agentic solutions may be more effective and more flexible than new SaaS implementations. This is where the technologys real greatness lies. Further reading Do you really know what agent means? – Fast Company How AI is changing what it means to be the CEO – Fast Company The Trillion-Dollar Question The SaaSpocalypse makes for dramatic headlines. But the idea on which those headlines are basedthat AI agents will soon be eating the lunch of enterprise software providersis founded on a misunderstanding about what enterprise software does. Its not just a tool that performs tasks. Its the digital encoding of the organizations institutional architecture. That isnt something a general-purpose tool can easily replace. The real risk for business leaders isnt that they will be too slow to abandon their enterprise platforms. Its that they will be stampeded by market panic into undervaluing the systems and institutional knowledge they already have. AI will reshape enterprise softwarethat much is certain. But there is a meaningful difference between a technology that changes how software works and one that makes software unnecessary. That distinction matters. And for the moment at least, the market has lost sight of it. {"blockType":"mv-promo-block","data":{"imageDesktopUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/10\/creator-faisalhoque.png","imageMobileUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/10\/faisal-hoque.png","eyebrow":"","headline":"Ready to thrive at the intersection of business, technology, and humanity?","dek":"Faisal Hoques books, podcast, and his companies give leaders the frameworks and platforms to align purpose, people, process, and techturning disruption into meaningful, lasting progress.","subhed":"","description":"","ctaText":"Learn More","ctaUrl":"https:\/\/faisalhoque.com","theme":{"bg":"#02263c","text":"#ffffff","eyebrow":"#9aa2aa","subhed":"#ffffff","buttonBg":"#ffffff","buttonHoverBg":"#3b3f46","buttonText":"#000000"},"imageDesktopId":91420512,"imageMobileId":91420514,"shareable":false,"slug":""}}
Category:
E-Commerce
When a new general-purpose technology emergesbe it railroads, electricity, computers, etc.companies react in predictable ways. A small minority tries to reinvent themselves around it; the majority looks first for ways to cut costs. Right now, in the middle of the most significant technological inflection since the internet, many organizations are choosing the second path. They deploy artificial intelligence to automate call centers, reduce head count in back offices, and squeeze marginal gains out of existing processes. They measure AI ROI in payroll savings and hours reclaimed. It feels rational. It feels disciplined. It feels safe. It is also the fastest way to miss the real opportunity. Innovation waves are not efficiency programs AI is not a new SaaS tool, nor is it merely a workflow enhancement. It is a rapidly evolving general-purpose technology advancing from large language models to agentic systems and toward systems that learn from interaction with environments (the so-called world models that can simulate, plan, and act). When the underlying capability is shifting every few months, optimizing for cost reduction is like trying to improve the fuel efficiency of a car while its engine is being replaced with a jet turbine. The organizations that win in moments like this do not start by asking, Where can we eliminate labor? They ask, What becomes possible that was previously impossible? Those are radically different questions. The productivity paradox should have been a warning In the early 1990s, economists puzzled over a surprising phenomenon: Computers were everywhere, yet productivity statistics stubbornly refused to reflect their impact. In a press article, Nobel laureate Robert Solow famously quipped, You can see the computer age everywhere but in the productivity statistics. That observation became known as the “productivity paradox.” At the time, many assumed the paradox was a failure of technology. My own research from that time examined why the paradox appeared at all, showing that productivity measurement lags widely behind actual transformational change and that the mechanisms of value creation were not captured by conventional metrics. The explanation was obvious only in hindsight. The gains were diffuse, uneven, and entangled with organizational change. Companies had digitized old processes instead of redesigning them. Today we are watching the same pattern unfold with AI. AIs impact wont show up neatly in cost metrics Artificial intelligence does not produce clean, linear productivity gains that fit neatly into quarterly dashboards. Its effects are asymmetrical. One employee using AI effectively may outperform 10 peers. Another may misuse it, degrade quality, or even endanger our corporate cybersecurity plans. Some teams redesign workflows entirely, while others bolt AI onto legacy processes and call it transformation. The result is what researchers now call measurement myopia: the inability of traditional metrics to capture improvements that are real but not directly tied to hours worked or cost saved. Trying to measure AIs value solely through immediate cost savings is like trying to measure the value of electricity by counting candles not purchased. Efficiency is the comfort strategy, but not the opportunity one Cost-cutting is attractive because it fits existing governance structures. CFOs understand it. Boards reward it. Metrics are clear. Exploration is messier. It requires experimentation without guaranteed returns. It demands a tolerance for failure. It produces intangible benefits before visible ones. But in periods of fast innovation, efficiency is often the comfort strategy of laggards who dont yet understand what is happening. If AI is treated primarily as a head-count-reduction tool, organizations will optimize the present and sacrifice the future. They will standardize mediocrity instead of discovering leverage. Exploration, not exploitation, builds capability Advocating exploration does not mean abandoning discipline. It means redefining it. Leaders should be asking: What new products can we build with AI-native capabilities? What decisions can we delegate to systems that learn from feedback? How can we redesign workflows, not just automate them? Companies should mandate controlled experimentation across teams, not restrict AI usage to narrow cost-justification pilots. They should treat AI like an R&D posture rather than a shrink-the-budget posture. Organizations that treat AI as an exploratory layerencouraging teams to test, prototype, recombine, and rethink workflowswill build institutional fluency. They will develop internal champions. They will uncover unexpected value that no top-down cost initiative would have surfaced. The real risk isnt overspending. Its under-imagining The greatest risk in this moment is not overspending on AI. It is under-imagining it. Companies that chase short-term efficiency gains may report modest improvements and declare success. Meanwhile, more ambitious competitors will redesign their operations, products, and customer experiences around capabilities that didnt exist two years ago. Over time, the gap will not be a few percentage points of margin. It will be strategic. In periods of rapid technological change, survival does not belong to the most efficient. It belongs to the most adaptive.
Category:
E-Commerce
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