1. Datadog Datadog (DDOG 1.59%) provides real-time monitoring for IT systems with a particular focus on cloud computing. The company is in a great position to benefit from continued growth in AI spending in two ways. Many growth stocks have gotten expensive, but these three still offer great value for their potential. The S&P 500 has continued its strong performance in 2025. The benchmark index is up 10% year to date as of this writing, following back-to-back gains in excess of 20% in 2023 and 2024. For man ...

Financial Data and Key Metrics Changes - Atlassian closed FY 2025 with revenue exceeding $5.2 billion and free cash flow of over $1.4 billion, achieving a balanced rule of 40 plus performance [8] - Free cash flow for the quarter was $360 million, down 13% year over year, primarily due to strong collections in the prior year [25][26] - The remaining performance metrics indicate a strong foundation for future growth, with a cloud net revenue retention rate of 120% [9] Business Line Data and Key Metrics Changes - The Teamwork platform now serves over 300,000 customers, with significant growth in enterprise sales and a record number of deals over $1 million in annual contract value (ACV) [8][9] - The AI Now user base reached 2.3 million, reflecting a 50% increase from the previous quarter [9] - Core applications such as Jira, Confluence, and Jira Service Management are growing in line or faster than total company revenue, indicating strong demand [11] Market Data and Key Metrics Changes - The company reported a 38% year-over-year increase in the remaining performance obligation (RPO) balance, reaching $3.3 billion, with 74% expected to be recognized as revenue in the next twelve months [42][43] - Data center to cloud migrations increased by 60% year over year, showcasing strong customer commitment to the cloud platform [42][69] Company Strategy and Development Direction - Atlassian is focusing on serving enterprise customers, delivering AI innovations, and enhancing collaboration through its system of work [9][11] - The partnership with Google Cloud is a significant step in Atlassian's multi-cloud strategy, aimed at accelerating cloud transformation and AI solution delivery [10] - The company is committed to long-term growth, with a target of 20% compounded annual growth from FY 2024 through FY 2027 [33][34] Management's Comments on Operating Environment and Future Outlook - Management expressed confidence in the company's ability to maintain growth despite macroeconomic uncertainties, emphasizing the importance of AI and enterprise transformations [33][34] - The management team highlighted that they are not seeing any negative impacts from the integration of code-generating AI tools on their product usage [16][21] - The company anticipates continued strong performance in the enterprise segment, with a robust pipeline of large deals and ongoing improvements in customer success operations [67][72] Other Important Information - Anu, the President of Atlassian, will transition away from her role in December after nearly twelve years, with management expressing gratitude for her contributions [11][12] - The company is investing heavily in R&D and sales to support its strategic priorities, which include enterprise cloud, AI, and system of work [100] Q&A Session Summary Question: Concerns about tool generation tools and developer roles - Management clarified that they are not seeing any negative impact on growth rates or adoption rates of their technical products despite market concerns [16][21] Question: Free cash flow trajectory for 2026 - Free cash flow for FY 2025 was flat at around $1.4 billion, with expectations for correlation to non-GAAP operating income trends moving forward [25][27] Question: Potential inflection points for revenue growth - Management highlighted multiple growth levers, including paid seat expansion, cross-sell, upsell, and new customer growth, with AI providing additional opportunities [33][34] Question: Guidance for data center segment growth - Management noted that Q1 guidance reflects a seasonal decline due to a smaller expiration base and headwinds from prior programmatic changes [76][78] Question: Driving wall-to-wall deployments in enterprises - Management emphasized ongoing consolidation efforts and the growth of business user segments as key strategies to increase penetration in non-technical roles [80][82]

Financial Data and Key Metrics Changes - Atlassian reported over $5.2 billion in revenue and over $1.4 billion in free cash flow for FY 2025, achieving a balanced rule of 40 plus performance [6][10] - Free cash flow for the quarter was $360 million, down 13% year over year, primarily due to strong collections in the prior year [24][25] - The company achieved a cloud net revenue retention rate of 120% [7] Business Line Data and Key Metrics Changes - The Teamwork platform now serves over 300,000 customers, with significant growth in AI usage, reaching 2.3 million AI users, a 50% increase from the previous quarter [6][7] - Core applications such as Jira, Confluence, and Jira Service Management are growing in line or faster than total company revenue [10] - The Teamwork collection has exceeded expectations since its launch, contributing to strong revenue growth [10] Market Data and Key Metrics Changes - Atlassian's enterprise sales teams executed a record number of deals greater than $1 million in annual contract value (ACV), more than doubling year over year [6][10] - Data center to cloud migrations increased by 60% year over year, indicating strong customer commitment to the cloud platform [42][69] Company Strategy and Development Direction - The company is focusing on serving the enterprise, delivering AI innovations, and connecting teams through the Atlassian system of work [7][10] - A partnership with Google Cloud aims to enhance the AI-powered Teamwork platform and accelerate cloud transformation [8][10] - Atlassian is committed to a long-term growth strategy, targeting a compounded annual growth rate of 20% from FY 2024 to FY 2027 [33][34] Management's Comments on Operating Environment and Future Outlook - Management expressed confidence in the company's ability to achieve long-term growth targets despite macroeconomic uncertainties [33][34] - The company sees AI as a significant tailwind for business growth, with expectations of increased software creation and collaboration [20][21] - Management highlighted the importance of customer-centric processes and partnerships to drive enterprise growth [71][72] Other Important Information - Anu, the President of Atlassian, will transition away from her role in December after nearly twelve years [10][11] - The company is investing heavily in R&D and sales to support its strategic priorities [101][102] Q&A Session Summary Question: Concerns about tool generation tools and developer roles - Management stated that they are not seeing any negative impact on growth rates or adoption from the integration of code-generating AI tools, and user growth remains healthy [15][16] Question: Free cash flow trajectory for 2026 - Free cash flow for FY 2025 was flat at $1.4 billion, with expectations that cash flow will correlate with non-GAAP operating income trends moving forward [24][25][26] Question: Potential inflection points for revenue growth - Management highlighted multiple growth levers, including paid seat expansion, cross-sell, upsell, and new customer growth, with AI opening up additional opportunities [33][34] Question: Guidance for data center segment growth - Management explained that Q1 guidance reflects a smaller expiration base and headwinds from prior programmatic changes, leading to a cautious outlook [78][79] Question: Driving wall-to-wall deployments in enterprises - Management emphasized ongoing consolidation efforts and the growth of business user segments, indicating strong momentum in expanding usage across non-technical roles [81][84]

Core Insights - Gamma, an AI startup, has achieved significant milestones with a team of 30, serving nearly 50 million users, and generating an ARR exceeding $50 million while maintaining profitability for over a year [1][2]. Group 1: Team Structure and Management - The founder, Grant Lee, emphasizes the importance of organizational innovation over traditional growth models, advocating for small teams that can achieve substantial impact with fewer resources [4][5]. - The initial team size was under 15 when launching AI features, which was deemed optimal for productivity [5]. - A diverse skill set within the founding team was crucial, with a focus on complementary abilities to avoid conflicts and enhance collaboration [6][7][8]. Group 2: Leadership and Flexibility - The concept of "player-coach" leadership is highlighted, where leaders actively participate in tasks while guiding their teams, fostering agility in a rapidly evolving AI landscape [9][11]. - The company promotes a culture of hands-on involvement, encouraging leaders to engage directly in execution to better understand where AI tools can be integrated [10][12]. Group 3: Sustainable Growth and Innovation - The company prioritizes sustainable business practices over rapid growth, believing that profitability is essential for maintaining control and fostering a sense of ownership among employees [23][39]. - Grant Lee reflects on the lessons learned from previous experiences, advocating for a thoughtful approach to scaling and financing, ensuring that growth aligns with actual market demand [37][45]. Group 4: Product Development and Market Positioning - Gamma's initial focus was on simplifying communication for knowledge workers, evolving to integrate AI capabilities that enhance user experience and engagement [57][58]. - The company has redefined its user onboarding process to showcase AI functionalities from day one, significantly improving user activation and retention rates [60]. Group 5: Future Challenges and Scaling - As Gamma aims to expand its user base to over 100 million, the company faces challenges related to infrastructure and customer service, necessitating careful planning and resource allocation [61][62].

Core Viewpoint - The article emphasizes the importance of organizational innovation in AI startups, highlighting that a small, efficient team can achieve significant impact without the need for large-scale hiring and excessive funding [4][9][38]. Group 1: Company Performance and Strategy - Gamma, an AI startup, has a team of 30 people serving nearly 50 million users, with an ARR exceeding $50 million and has been profitable for over a year [2][3]. - The founder, Grant Lee, believes that the traditional model of raising large amounts of capital and hiring hundreds of employees is outdated [5][9]. - The company focuses on maximizing the impact of each employee by hiring versatile individuals who can solve problems across different domains [7][19]. Group 2: Organizational Design and Culture - The company aims to avoid creating "expert silos" by hiring multi-talented individuals and adopting a "player-coach" model, where leaders also contribute to execution [7][14]. - Grant Lee emphasizes the need for a feedback culture within the team to ensure continuous improvement and accountability [24]. - The company values proactive employees with a strong willingness to learn and adapt quickly to new skills, prioritizing generalists over specialists [19][49]. Group 3: Funding Philosophy - The company adopts a cautious approach to funding, preferring to focus on sustainable growth rather than rapid expansion through excessive financing [9][43]. - Grant Lee advocates for a long-term relationship with investors, treating financing as a partnership rather than a quick transaction [41]. - The company aims to achieve profitability before seeking further funding, ensuring that each new hire is driven by actual market needs [43][44]. Group 4: Product Development and Market Position - Gamma's initial focus was on simplifying communication for knowledge workers, with a shift towards integrating AI to enhance content creation processes [56]. - The company experienced significant user growth after launching AI features that assist in drafting and searching for relevant images [58]. - The founder acknowledges the rapid evolution of the AI landscape, emphasizing the need for companies to remain adaptable and vigilant against emerging competition [51][54].

Core Insights - GitLab (GTLB) is experiencing strong demand for its DevSecOps platform, driven by partnerships with major cloud providers like Google Cloud, AWS, and Zscaler, which enhance its reach among large enterprise customers [1][4][12] Group 1: Partnerships and Integrations - GitLab announced the general availability of GitLab Duo with Amazon Q, integrating AI agents to accelerate development and streamline security processes [2] - The collaboration with Google Cloud is improving developer productivity by enhancing authentication and application deployment [3] - Zscaler's selection of GitLab as a partner reinforces its position in the DevSecOps market by enhancing security and expanding enterprise adoption [4] Group 2: Customer Growth and Market Position - In Q1 FY26, GitLab saw a 13% year-over-year increase in customers with over $5K in Annual Recurring Revenue (ARR), reaching 10,104, and a 26% increase in customers with over $100K in ARR, totaling 1,288 [5][12] - GitLab operates in a highly competitive environment, facing significant competition from Microsoft, Atlassian, and other DevSecOps platforms [6][7][8] Group 3: Financial Performance and Valuation - GitLab's shares have declined by 18.6% year to date, contrasting with a 10.6% return in the broader Zacks Computer & Technology sector [10] - The forward 12-month Price/Sales ratio for GitLab is 7.21X, higher than the industry average of 5.90X, indicating a premium valuation [13] - The Zacks Consensus Estimate for Q2 FY26 earnings is 16 cents per share, reflecting a 6.67% year-over-year increase, while the estimate for FY26 earnings is 75 cents per share, suggesting a 1.35% growth [15]

Core Insights - GitLab (GTLB) is experiencing strong demand for its DevSecOps platform, with significant contributions from solutions like GitLab Ultimate, Dedicated, and GitLab Duo, leading to increased customer adoption and relationship expansion [1][10] - The company's financial performance reflects this demand, with total revenues of $214.4 million in the first quarter of fiscal 2026, marking a 27% year-over-year increase [1] Customer Growth - GitLab's expanding clientele is evident, with customers generating over $5K in Annual Recurring Revenue (ARR) increasing to 10,104, a 13% year-over-year rise [2] - Customers with more than $100K in ARR grew to 1,288, up 26% year-over-year, indicating GitLab's success in attracting and retaining large enterprise customers [2] Product Innovations - The company announced the general availability of GitLab 18, which includes major innovations in core DevOps workflows, security, compliance, and AI capabilities [3] - GitLab Duo with Amazon Q was also launched for Ultimate self-managed customers on AWS, alongside achieving FedRAMP Moderate Authority to Operate for GitLab Dedicated for Government [3] Strategic Partnerships - GitLab benefits from a robust partner network, including major cloud platforms like Google Cloud and Amazon Web Services (AWS), which aids in expanding its presence among large enterprises [4] Competitive Landscape - GitLab operates in a highly competitive environment, facing significant competition from Microsoft, Atlassian, and other DevSecOps platforms [5][6][7] - Microsoft has strengthened its position through the integration of GitHub and Azure DevOps, making it a formidable rival for GitLab [6] Stock Performance and Valuation - GitLab's shares have declined by 17.7% year to date, contrasting with a 7% return from the broader Zacks Computer & Technology sector [8] - The stock is trading at a premium, with a forward 12-month Price/Sales ratio of 7.51X compared to the industry average of 5.74X, and it currently holds a Value Score of F [11] Earnings Estimates - The Zacks Consensus Estimate for second-quarter fiscal 2026 earnings is 16 cents per share, reflecting a 6.67% year-over-year increase [13] - The consensus for fiscal 2026 earnings is set at 75 cents per share, indicating a 1.35% year-over-year growth [13]

Core Viewpoint - The article discusses the significant updates to Anthropic's Claude, particularly the introduction of the Model Context Protocol (MCP), which is becoming an industry standard for integrating large model applications with external data sources and tools [4][5]. Group 1: MCP and Its Features - MCP (Model Context Protocol) is a communication protocol proposed by Anthropic that allows seamless integration of large model applications with external data sources, enhancing the quality and relevance of AI-generated responses [4]. - MCP has gained widespread recognition and adoption in the industry, being compared to a Type-C interface for AI applications [5]. - The MCP functionality is now available on the Claude web version, integrating with ten applications including GitLab, PayPal, and Cloudflare, allowing developers to create their own integrations within 30 minutes [9]. Group 2: Updates and Functionalities of Claude - Claude has introduced new features such as Integration and Research, expanding its capabilities to access more data sources, including those from MCP applications [6][18]. - The Research function allows Claude to conduct in-depth investigations across hundreds of internal and external sources, generating comprehensive reports by breaking down requests into smaller parts [17][20]. - Claude can now perform tasks such as scheduling plans in Jira based on documents and analyzing user feedback through AI customer service software [11][13]. Group 3: User Accessibility and Future Implications - The updates to Claude are currently available to Max, Team, and Enterprise users, with plans to extend to Pro users in the future [1]. - The integration of MCP into the web version of Claude signifies a shift towards a SaaS (Software as a Service) model, potentially leading to a new era of application accessibility and functionality [2].

Financial Data and Key Metrics Changes - Total revenue for Q3 2025 reached $1.4 billion, with cloud revenue growing 25% year over year and a free cash flow margin of 47% [6][10]. - Gross margins improved to 86%, exceeding prior guidance, driven by price increases and engineering investments [40][41]. Business Line Data and Key Metrics Changes - Cloud revenue growth was primarily driven by increased adoption of premium enterprise editions, which rose over 40% year on year [14]. - Data center growth was mainly attributed to pricing, offset by strong migrations to cloud and fewer multiyear agreements [24][25]. Market Data and Key Metrics Changes - The company achieved FedRAMP Moderate Authorization for U.S. Federal Government customers, expanding its cloud platform offerings [9]. - Over 300,000 customers, including major enterprises like Mercedes and SAP, utilize Atlassian's solutions [9]. Company Strategy and Development Direction - Atlassian is focusing on integrating AI capabilities into its core products, with Robo being central to this strategy [7][10]. - The company aims to scale to $10 billion in revenue and beyond, leveraging its strategic priorities in enterprise solutions and AI advancements [10]. Management's Comments on Operating Environment and Future Outlook - Management expressed confidence in achieving a 20% compound annual growth rate (CAGR) through FY 2027, despite macroeconomic uncertainties [18][19]. - The company is adapting to longer deal cycles due to the complexity of enterprise deals, which is seen as a natural evolution rather than a macroeconomic issue [28]. Other Important Information - The introduction of the Teamwork Collection is expected to simplify purchasing for customers and drive long-term revenue growth [69][70]. - The isolated cloud offering is designed to meet the needs of large and complex organizations, providing dedicated resources [76]. Q&A Session Summary Question: Impact of embedding Robo on near-term revenue growth - Management noted that embedding Robo is expected to enhance user adoption and long-term growth potential, despite potential short-term revenue trade-offs [14][15]. Question: Cloud revenue growth and deal timing - Management acknowledged that enterprise deals were back-end loaded, impacting Q3 cloud revenue growth, but expected recognition in Q4 [23]. Question: Transition to annualized data center agreements - Management indicated that the change in agreement duration would lead to better cloud revenue growth contributions in FY 2026 and FY 2027 [36]. Question: Gross margin and efficiency gains - Management highlighted that gross margins of 86% were driven by price increases and efficient cloud infrastructure management, with expectations for continued improvements [40][41]. Question: Effect of tariffs on customer businesses - Management reported no significant macro impact from tariffs, emphasizing a strong pipeline and customer demand for cloud upgrades [54][55]. Question: CRO transition and go-to-market strategy - Management confirmed that the new CRO is adapting well, and the go-to-market strategy continues to evolve to meet customer needs [86][87].

Financial Data and Key Metrics Changes - The company reported total revenue of $1.4 billion for Q3, with cloud revenue growing by 25% year over year and a free cash flow margin of 47% for the quarter [8][20][41] - Gross margins reached 86%, exceeding prior guidance, driven by price increases and engineering investments [41][43] Business Line Data and Key Metrics Changes - Cloud revenue growth was impacted by enterprise deals landing later than expected, affecting the growth rate recognized in Q3 [25][48] - Data center growth was primarily driven by pricing, offset by strong migrations to cloud and fewer multiyear agreements [26][27] Market Data and Key Metrics Changes - The company achieved FedRAMP Moderate Authorization for U.S. Federal Government customers, expanding its cloud platform offerings [10] - Over 300,000 customers, including major enterprises like Mercedes and SAP, utilize Atlassian's solutions [10] Company Strategy and Development Direction - The company is focusing on embedding AI capabilities into core products, aiming for user expansion and maximizing adoption [15][16] - The strategic goal is to scale to $10 billion in revenue and beyond, leveraging advancements in AI and enterprise solutions [11][20] Management's Comments on Operating Environment and Future Outlook - Management remains confident in achieving a 20% compound annual growth rate (CAGR) through FY '27, despite macroeconomic uncertainties [21][67] - The company is adapting its go-to-market strategy to better serve enterprise customers, reflecting a shift in customer mix and needs [86][88] Other Important Information - The introduction of the Teamwork Collection is seen as a long-term growth driver, simplifying purchasing behavior for customers [68][70] - The company is committed to maintaining structural efficiency gains and optimizing cloud costs while expanding its AI capabilities [42][81] Q&A Session Summary Question: Impact of AI adoption on revenue growth - Management noted that AI adoption is still in early stages, with many enterprises experimenting and cautious about deployment [91][92] Question: Changes in go-to-market strategy with new CRO - The company is continuously evolving its go-to-market strategy to adapt to customer needs and market dynamics, with the new CRO bringing valuable experience [86][89] Question: Effect of tariffs on customer businesses - Management indicated that the business remains healthy and customers are eager to upgrade to the cloud, with no significant macro impacts observed [54][55]