Management is positioning the company at the intersection of business and technology to navigate a new paradigm where AI computing rivals traditional SaaS models. Performance in 2025 was impacted by the final stages of the Forrester Decisions migration, resulting in an 8% revenue decline despite improvements in client retention. The company is leveraging proprietary data and human expertise as a 'trust' differentiator against public large language models that management believes suffer from content mi ...

Leadership Changes - Kayak co-founder and CEO Steve Hafner has stepped down after 22 years, with CFO Peer Bueller appointed as the new CEO [1] - Hafner will transition to a newly created role as executive chair, focusing on advancing AI innovation at Booking Holdings [2] Company Background - Kayak was co-founded by Hafner and Paul English in 2004, becoming a leading travel metasearch platform alongside competitors like Skyscanner, Trivago, and Tripadvisor [4] - Booking Holdings acquired Kayak for $2.1 billion in 2013, as part of a strategy to own a metasearch company for in-house marketing and revenue generation from rival advertising [5] Market Dynamics - The rise of Google in generative AI and its dominance in hotel and flight metasearch has diminished the perceived value of metasearch platforms like Kayak [6] - In October 2025, Booking Holdings reported a $457 million writedown on Kayak, citing expected lower future cash flows and higher customer acquisition costs, largely due to changes in Google's search practices [7]

Core Viewpoint - Micron Technology is experiencing significant optimism in the market, with a notable increase in stock price, reflecting strong demand for its products, particularly DRAM, despite the cyclical nature of the industry [1][2][3]. Group 1: Market Performance - Micron's stock has risen by 168%, indicating strong market confidence ahead of earnings reports, although there is a tendency for the stock to sell off post-earnings due to prior buildup [3][2]. - The company is shifting focus from older NAND products to high bandwidth memory DRAM, which is expected to drive future growth [5]. Group 2: Demand and Competition - There is a high demand for DRAM products, with Micron currently holding a lead in the market, facing competition from only two other players [4]. - The demand for hardware, particularly in relation to large language models and data centers, is expected to remain strong, although there are concerns about the sustainability of this demand over the long term [11][10]. Group 3: Global Market Considerations - Micron's exposure to the Chinese market raises concerns due to geopolitical issues, particularly regarding the sale of advanced technology [10]. - The company is expected to maintain strong demand for its products in the next 18 to 36 months, despite potential supply chain challenges [10][11]. Group 4: Industry Dynamics - The competitive landscape is evolving, with companies like Amazon and Alphabet rapidly developing usable technology, indicating a dynamic environment where multiple players can coexist and thrive [12][14]. - The performance of competitors, particularly Nvidia, is noted as a significant factor in the industry, suggesting that competition drives innovation and benefits end consumers [13][14].

Core Insights - Luma AI, a video generation startup backed by Nvidia, is expanding its operations to the U.K. with plans to hire around 200 employees by early 2027, which will constitute about 40% of its workforce [1][2] Funding and Valuation - The company recently announced a $900 million funding round led by Humain, a Saudi Public Investment Fund-owned AI company, resulting in a valuation exceeding $4 billion [2] Technology and Market Focus - Luma AI is developing "world models," AI models capable of learning from various media types, including video, audio, images, and text, which are utilized by large language models like OpenAI's ChatGPT and Google's Gemini [2] - The startup is targeting sectors such as marketing, advertising, media, and entertainment with its video models, which are offered through an API and as part of a content creation suite [3] Strategic Expansion - The CEO of Luma AI, Amit Jain, emphasized that the recent funding and the expansion of global compute infrastructure will enable the company to deliver world-scale AI to creatives globally [4] - The U.K. was chosen as the initial expansion location due to its access to talent and as a gateway to the European market [5]

Large language models might actually be more than just next word predictors. Anthropic has been putting out incredible papers lately that show AI large language models in particular exhibit very human-like behavior at almost every level. Here's the new paper emergent introspective awareness in large language models.So what did anthropic actually test. There were four main experiment types. First injected thoughts.What they did was use two different prompts, one with all caps and one without all caps. And th ...

AI Agents & Business Transformation - AI agents are poised to transform the workplace by acting on suggestions and driving impact in areas like data entry, invoice creation, and client relationship management [16] - Companies should focus on reimagining their business processes to take full advantage of AI agents, rather than simply automating existing human tasks [43] - Early adopters of AI agents can build compounding intelligence advantages, creating learning gaps over competitors and making their competitive moats increasingly difficult to replicate [48][49] Human-AI Collaboration - To stay relevant, individuals and teams need to develop uniquely human abilities ("humics") such as genuine creativity, critical thinking, and social authenticity to maximize value creation with AI [61][53][54][55][56][57] - Managers need to become orchestrators, designing human-agent workflows and focusing on goal setting and boundary definition, rather than task assignment [66] - Building trust between team members and AI agents is crucial, and can be achieved through clarity, transparency, and a gradual collaboration approach [67][68][69] Implementation Strategies - Successful AI transformations require a clear vision from top leadership and investment in people and talents, including creating a center of excellence or AI talent group [85][86] - Companies should start small with pilot projects to demonstrate the capability of AI agents and generate momentum within the organization [88] - Organizations should allocate approximately 20% of employees' working time to stay informed about AI advancements, experiment with new technologies, and develop AI literacy [80] Metrics & Change Management - Organizations need a comprehensive review of metrics for both AI agents and humans, incentivizing humans to experiment and build uniquely human skills [72] - Companies should combine qualitative and quantitative metrics, focusing not only on cost and efficiency but also on improvements in customer and employee experience [74] - Businesses must cultivate change readiness, enabling them to filter information effectively and identify AI technologies that are worth testing and using [77][78][79]

Performance Overview - The Akre Focus Fund's Institutional share class reported a third quarter 2025 performance of -3.65%, significantly underperforming the S&P 500 Total Return, which was at 8.12% [3][4] - For the trailing 12-month period ending September 30, 2025, the Fund's Institutional share class achieved a return of 3.71%, compared to 17.60% for the S&P 500 Total Return [3] Key Holdings Impact - The primary contributor to the Fund's poor performance was a 26.06% decline in the share price of Constellation Software, which accounted for a 3.56% detriment to the Fund's performance in the quarter [5][6] - Constellation Software has been held by the Fund for over 11 years, with a compound annual rate of return of 24.97% since its initial purchase [7] Long-term Perspective on Constellation Software - Despite the recent drawdown, the Fund maintains confidence in Constellation Software's ability to navigate technological changes and protect its market position [8][9] - Constellation has demonstrated a compound annual total revenue growth rate of approximately 20% over the past decade, indicating strong underlying business performance [8] Leadership Transition - Mark Leonard, the founder of Constellation Software, announced his immediate step down from the President role due to health issues, raising concerns about leadership continuity [12][10] - The Fund expresses optimism regarding Mark Miller, the new President, who has been with Constellation since its first acquisition and is expected to uphold the company's foundational principles [14] Sector and Holdings Composition - As of September 30, 2025, the top five holdings in the Fund included Mastercard (12.4%), Brookfield Corp (10.6%), and Constellation Software (10.1%) [28] - The sector weightings revealed a significant concentration in Financials (52.1%) and Information Technology (20.7%) [28]

Core Insights - OpenAI is exploring partnerships with Broadcom to leverage custom silicon for AI applications, similar to Google's TPU model, which has proven successful in reducing costs significantly [1][2][6] - Broadcom's AI chip business is projected to reach nearly $20 billion, with a substantial portion of revenue coming from Google, indicating a strong market position [1][3] - The cost of chips constitutes 60-70% of data center expenses, making it crucial for companies to source chips at the lowest possible cost to enhance profitability [6][7] Group 1: Cost Efficiency and Custom Silicon - OpenAI aims to reduce costs by 30-40% per gigawatt through the use of Broadcom's chips, which are expected to be cheaper than competitors like Nvidia and AMD [2][3][7] - The integration of custom silicon is essential for optimizing performance per watt, which is a key consideration for AI data centers [9][10] - Google has demonstrated that custom silicon can provide superior performance, as seen in their successful deployment of YouTube videos [9][10] Group 2: Competitive Landscape - Other companies like Amazon and Microsoft are also pursuing custom silicon solutions but have not achieved the same level of success as Google with Broadcom [5][6] - The competitive advantage of Broadcom lies in its ability to offer both merchant and custom silicon tailored to specific needs, which is critical for companies looking to optimize their AI infrastructure [4][7] - The focus on minimizing latency and maximizing performance per watt is driving the demand for custom silicon in the AI sector [9][10]

AI Investment & Infrastructure - OpenAI's AI infrastructure buildout is estimated at $850 billion, potentially requiring the equivalent of 17 nuclear reactors [1] - OpenAI's projects from the past 2 days amount to nearly half of the $2 trillion global AI infrastructure surge forecast by HSBC [2] - Alibaba is increasing its AI model and infrastructure spending, adding to the existing $53 billion commitment [6] - Alibaba is opening new data centers in Brazil, France, and the Netherlands to improve model speed and user proximity [9] Market Dynamics & Competition - The AI sector is experiencing a technological revolution requiring significant infrastructure investment [4] - Demand for AI is rapidly growing, with OpenAI experiencing a tenfold increase in the last 18 months [3] - The US is currently ahead in AI spending compared to China [7] - Chinese companies like Tencent and BU are competing with global model makers like Anthropic and OpenAI [10] - Alibaba aims to become a more self-sufficient hyperscaler in the AI competition [10] Investment Risks & Rewards - The AI sector is expected to experience cycles of over and underinvestment, with potential for both gains and losses [5] - The long-term value of AI technology is projected to be significant for society [6] - Companies are being rewarded in the stock market for announcing substantial AI investments [12] - The risk of underinvesting in AI is currently perceived as more prominent than overinvesting [14]

Research Methodology & Focus Shift - The initial research aimed to predict naval movements and oil prices using satellite data but shifted to the effect of inflation on different income groups due to limited resources [5] - The research focus changed from inflation's impact on income groups to helping researchers conduct short-term research, using inflation as a case study [14][15] - The study incorporated mixed methods research, including quantitative analysis (regression models), thematic analysis of documents from government agencies, NGOs, and institutions like the World Bank, and surveys [12][13][16] Challenges & Solutions in Short-Term Research - Short-term research faces challenges as numbers may not have time to stabilize, leading to jittery models and patterns [10] - The researcher initially struggled with regression models that yielded already known information about inflation's impact [8] - To address the limitations of short-term data, the researcher supplemented quantitative analysis with thematic analysis of documents and surveys to humanize the research [12][13] Role of LLMs in Research - Large language models (LLMs) were used to determine the optimal sequence for mixed methods research, comparing quantitative-before-qualitative and qualitative-before-quantitative approaches [17][18][19] - The LLM analysis indicated that starting with quantitative analysis followed by qualitative analysis yielded richer interpretations [19] - The use of LLMs in research received mixed reactions from reviewers, with some seeing it as a red flag and others as a novel contribution [20][21] Key Takeaways & Recommendations - Researchers should be flexible and open to pivoting from their initial plans and hypotheses [24] - The research emphasizes the importance of open access and sharing knowledge in science [15] - The study suggests researchers should be open to learning and unlearning, actively researching in the field and discovering insights unexpectedly [25]