Join us as we dive deep into the 2025 Stack Overflow Developer Survey, the definitive report on the state of software development. With over 49,000+ responses from 177 countries, this annual survey provides a crucial snapshot into the needs, tools, and technologies shaping the global developer community.

In this episode, we'll explore:

• The Evolving AI Landscape:

  • Discover how developers are exploring new AI agent tools, Large Language Models (LLMs), and community platforms.
  • While a majority of developers (52%) either don't use AI agents or stick to simpler AI tools, and 38% have no plans to adopt them, an impressive 84% of respondents are using or planning to use AI tools in their development process, an increase from last year.
  • Learn about the shifts in sentiment: positive sentiment for AI tools has decreased in 2025 to just 60% (from over 70% in 2023 and 2024).
  • Crucially, more developers actively distrust the accuracy of AI tools (46%) than trust it (33%), with only a fraction (3%) reporting "highly trusting" the output.
  • Understand the biggest frustrations, cited by 66% of developers, which is dealing with "AI solutions that are almost right, but not quite", often leading to the second-biggest frustration: "Debugging AI-generated code is more time-consuming" (45%).
  • Despite these challenges, we'll highlight that approximately 70% of AI agent users agree that agents have reduced the time spent on specific development tasks, and 69% agree they have increased productivity.
  • Many respondents (over 36%) have also learned how to use AI-enabled tools for their job or to advance their career in the last year.
  • Furthermore, find out why Stack Overflow is becoming a new resource for developers who need to solve AI-related issues, with about 35% of visits being a result of such problems.

• Top Technologies & Developer Preferences:

  • Unpack why Cargo, Rust's build tool and package manager, is the most admired (71%) cloud development and infrastructure tool this year.
  • Discover uv, a Python package manager built in Rust, as the most admired (74%) Stack Overflow tag technology.
  • Explore the continued dominance of OpenAI's GPT models, with 82% of developers indicating they used them for development work in the past year, and why Anthropic's Claude Sonnet is the most admired LLM this year.
  • Understand the significant acceleration of Python's adoption, with a 7 percentage point increase from 2024 to 2025, solidifying its role as the go-to language for AI, data science, and back-end development.
  • Learn why Visual Studio Code (75.9%) and Visual Studio (29%) maintained their top spots for developer environments for the fourth year.
  • See how GitHub has stepped up as a more desired collaboration tool than Jira this year.
  • Delve into the top three reasons developers turn their back on a technology: security or privacy concerns, prohibitive pricing, and the availability of better alternatives.

• Developer Profiles & Work Environments:

  • Gain insights into the global developer community, with the United States of America (20.4%), Germany (8.6%), and India (7.2%) as the top countries responding to this year's survey.
  • We'll cover work preferences, with nearly one third of developers (32.4%) working remotely this year, and the US having the highest number of remote developers (45%) among top-reporting countries.
  • Understand that most developers (65%) have been coding for 10 or more years.
  • significantly higher interest in more social and interactive content formats like "Chat (people)" and "Coding challenges," aligning with a motivation to skill up. And note that Stack Overflow remains a frequent destination, with 82% visiting at least a few times per month. Learners also use YouTube for community more than professional developers.

Tune in to gain a deeper understanding of the forces shaping the world of software development!

Dive deep into the rapidly evolving world of Large Language Models (LLMs) with our discussion on Menlo Ventures' '2025 Mid-Year LLM Market Update: Foundation Model Landscape + Economics' report. Released July 31, 2025, this essential update from Tim Tully, Joff Redfern, Deedy Das, and Derek Xiao reveals critical shifts and emerging trends shaping the future of computing.

In this episode, we unpack the latest data from a survey of over 150 technical leaders across startups and enterprises, exploring:

• Anthropic's ascendancy as the new enterprise LLM leader, now commanding 32% of enterprise usage and surpassing OpenAI, which holds 25%. We'll discuss how innovations like Claude Sonnet 3.5, 3.7, and 4 propelled this growth.
• The significant shift in AI spend from model training to production inference, with LLM API spending more than doubling from $3.5 billion to $8.4 billion in just six months, marking a clear move towards models running in production.
• The emergence of code generation as AI’s first breakout use case, with Claude quickly becoming the developer’s top choice, capturing 42% market share—more than double OpenAI's.
• The breakthrough importance of Reinforcement Learning with Verifiers (RLVR) as the new path to scaling intelligence, pushing the envelope beyond traditional pre-training limits.
• Why 2025 is known as the 'year of agents,' as LLMs are increasingly trained to think step-by-step, reason through problems, and integrate external tools, dramatically boosting their real-world utility.
• The stagnation of open-source model adoption in the enterprise, which has seen market share slightly decline. We'll examine the persistent performance gap with closed-source frontier models, technical complexities, and enterprise reluctance to use certain foreign APIs as key contributing factors.
• The surprising market dynamic where enterprises prioritize and pay for performance over price, consistently upgrading to the best-performing models even as older ones become cheaper. Builders rapidly switch to newer, higher-performing models, with 66% upgrading within their existing provider.

Join us to understand these pivotal market dynamics and gain insights into where long-term value might accrue in the LLM ecosystem."

This podcast explores "America's AI Action Plan," a strategic document published in July 2025 by The White House. The plan outlines a national security imperative for the United States to "achieve and maintain unquestioned and unchallenged global technological dominance" in artificial intelligence (AI). It asserts that whoever has the largest AI ecosystem will establish global AI standards and gain extensive economic and military advantages, making it "imperative that the United States and its allies win this race".

The plan envisions AI ushering in a "new golden age of human flourishing, economic competitiveness, and national security for the American people," driving an industrial revolution, an information revolution, and a renaissance simultaneously.

The "AI Action Plan" is structured around three core pillars:

• Pillar I: Accelerate AI Innovation – This pillar focuses on creating conditions for private-sector-led innovation to flourish by removing "red tape and onerous regulation". It also emphasizes ensuring "frontier AI Protects Free Speech and American Values," encouraging "Open-Source and Open-Weight AI," enabling "AI Adoption," empowering "American Workers in the Age of AI," supporting "Next-Generation Manufacturing," investing in "AI-Enabled Science," building "World-Class Scientific Datasets," advancing "the Science of AI," investing in "AI Interpretability, Control, and Robustness Breakthroughs," building an "AI Evaluations Ecosystem," and accelerating "AI Adoption in Government" and within the "Department of Defense," while protecting "Commercial and Government AI Innovations" and combating "Synthetic Media in the Legal System".
• Pillar II: Build American AI Infrastructure – This pillar addresses the need for vast AI infrastructure and the energy to power it. Key areas include creating "Streamlined Permitting for Data Centers, Semiconductor Manufacturing Facilities, and Energy Infrastructure while Guaranteeing Security," developing a robust "Grid to Match the Pace of AI Innovation," restoring "American Semiconductor Manufacturing," building "High-Security Data Centers for Military and Intelligence Community Usage," training a "Skilled Workforce for AI Infrastructure," bolstering "Critical Infrastructure Cybersecurity," promoting "Secure-By-Design AI Technologies and Applications," and promoting "Mature Federal Capacity for AI Incident Response".
• Pillar III: Lead in International AI Diplomacy and Security – This pillar focuses on America's role in the global AI competition. It proposes to "Export American AI to Allies and Partners," "Counter Chinese Influence in International Governance Bodies," strengthen "AI Compute Export Control Enforcement," plug "Loopholes in Existing Semiconductor Manufacturing Export Controls," align "Protection Measures Globally," ensure the "U.S. Government is at the Forefront of Evaluating National Security Risks in Frontier Models," and "Invest in Biosecurity".

The plan highlights several cross-cutting principles, including ensuring American workers benefit from AI opportunities and creating high-paying jobs, developing AI systems that are "free from ideological bias" and pursue "objective truth", and preventing advanced technologies from being "misused or stolen by malicious actors" while monitoring for "emerging and unforeseen risks from AI". This podcast provides a detailed look into the roadmap for America's victory in the AI race.

Dive into the 2025 State of AI Report: The Builder's Playbook podcast, your essential guide for building and operationalizing AI products to gain a competitive advantage. This deep dive unpacks the "how-to" of conceiving, delivering, and scaling AI-powered offerings end-to-end.

Join us as we explore core dimensions of the builder's playbook, including Product Roadmap & Architecture, Go-to-Market Strategy, People & Talent, Cost Management & ROI, and Internal Productivity & Operations. We draw on proprietary survey results and insights from AI leaders across the ICONIQ community to offer a blueprint for anyone tasked with turning generative intelligence from a promising concept into a dependable, revenue-driving asset.

Key topics we'll cover:

• AI Product Development: Understand why AI-native companies are moving faster through the product lifecycle, with approximately 47% of their primary AI products already reaching critical scale and proven market fit. Discover that agentic workflows and application layers are the most common types of AI products being built across both AI-native and AI-enabled companies, with notably around 80% of AI-native companies currently building agentic workflows.
• Model Usage & Infrastructure: Learn how companies prioritize model accuracy above all other factors when choosing foundational models for customer-facing use cases. We'll discuss the increasing trend of companies adopting a multi-model approach to AI products and the dominance of fully cloud-based solutions and reliance on external AI API providers for training and inference infrastructure.
• Challenges & Optimization: We'll address the top challenges noted by companies when deploying models, such as hallucinations, explainability & trust, and proving ROI. Find out how organizations are optimizing AI infrastructure costs by exploring open-source models and focusing on inference efficiency.
• Talent & Costs: Explore insights into the increasing presence of dedicated AI leadership as companies grow, the finding that AI/ML engineers take the longest time to hire on average, and how companies are allocating approximately 10-20% of their R&D budget to AI development. We'll highlight that API usage fees are cited as the most challenging infrastructure cost to control, and inference costs and data storage & processing costs surge post-launch, especially for high-growth companies.
• Internal Productivity: Understand how annual internal AI productivity budgets are set to nearly double in 2025 across all revenue tiers, with cost being the most important consideration when choosing models for internal AI use cases. Discover the significant impact of coding assistance, which is by far the leading use case in terms of tangible impact on productivity, and how most companies are tracking productivity improvements and cost savings from internal AI use.

This podcast is ideal for architects, engineers, and product leaders aiming to harness AI expertise, foster cross-functional collaboration, and sustain long-term innovation. Tune in for expert insights into AI strategy, development, scaling, and cost management derived from a comprehensive April 2025 survey of 300 executives at software companies building AI products.

Unlock the Future of Business: Insights from the Q2 2025 AI Pulse Survey

Is your organization ready for the AI revolution? In this insightful podcast, we dissect the key findings from the Q2 2025 AI Quarterly Pulse Survey, revealing how AI is rewriting the playbook and why 82% of leaders agree their industry's competitive landscape will transform in the next 24 months.

Discover where organizations are strategically allocating their Gen AI budgets, with cyber and data security (67%), risk and compliance (52%), and operations (48%) leading the charge. Learn how implementations are already delivering significant ROI, with productivity (98%) and profitability (97%) continuing as top metrics. We also explore critical decision points for choosing a GenAI (LLM) provider, where data privacy and security (74%) are paramount.

Delve into the world of AI agents: understand why 90% of organizations are moving beyond experimentation, with 33% already deploying agents and 57% piloting them. While Chief Information Officers (CIOs) lead AI strategies across 87% of enterprises, we confront the primary obstacles to agent deployment, including technical skills gaps (59%), workforce resistance to change (47%), and system complexity (39%). Hear how leaders believe AI agents will enhance job satisfaction (87%), become valued teammates (86%), and redefine performance metrics (87%).

We also tackle the escalating concerns around data privacy (69%), regulatory issues (55%), and data quality (56%), which are at their highest in three quarters. Explore how leaders are mitigating risks, with 55% requiring human-in-the-loop oversight for autonomous agents. Finally, gain crucial insights into the potential impact of tariffs on AI, with 57% of leaders agreeing they will increase overall planned investment in AI, and 73% believing they will increase focus on AI efficiency and optimization.

Tune in to stay ahead of the curve, understand the strategic imperatives, and navigate the challenges of the rapidly evolving AI landscape, directly from the insights of the latest industry pulse.

What happens when the world’s most powerful technology evolves faster than anything in human history? In this episode, we break down the landmark BOND May 2025 report on artificial intelligence trends—featuring explosive data, real-world examples, and forward-looking analysis.

We unpack why AI adoption is outpacing the internet, how tech giants and startups are burning billions to win the global AI arms race, and what it means when ChatGPT reaches 800M weekly users in under two years.

Discover the compounding effects of AI—from language models to autonomous systems, and from digital infrastructure to geopolitics. We connect the dots across compute costs, open-source models, China’s rapid rise, and how AI is fundamentally rewriting the rules of work, creativity, and competition.

If you're a business leader, technologist, investor, or just trying to stay ahead of the AI curve—this episode delivers critical insights in plain language, with smart metaphors, strategic framing, and predictions that might just reshape your worldview.

🔎 Topics we cover:

• AI usage & CapEx growth: Why the curves are bending up-and-right

• The convergence of geopolitics and AI innovation

• Why ChatGPT’s growth dwarfs Google’s early years

• Risks and opportunities in the AI monetization race

• The “AI factories” behind the scenes (with NVIDIA, Google, Amazon)

• What the future of work, healthcare, and creativity may look like in 2030

• And... why “statistically, the world doesn’t end that often” (a quote you won’t forget)

In this episode, we explore a pivotal shift in AI: the transition from data trained on human examples to systems that learn from real-world experience. Inspired by the paper “Welcome to the Era of Experience” by David Silver and Richard S. Sutton, we dive into why imitation-based AI like LLMs is reaching its limits—and how reinforcement learning and autonomous agents are set to surpass human knowledge. Discover how experiential learning could power breakthroughs in science, education, and health, and what it means for safety, planning, and human-AI alignment. If you're curious about the next frontier of AI, this episode is your guide.

In this episode, we unpack Google DeepMind’s influential position paper outlining a new framework for defining and tracking the development of Artificial General Intelligence (AGI). The authors propose a leveled ontology of AGI based on performance and generality, offering a shared language for assessing AI capabilities, risks, and progress. We explore why defining AGI through a staged matrix matters, how current systems like ChatGPT fit into the "Emerging AGI" category, and what it means for policymakers, researchers, and society. Tune in to learn how this framework shapes the future of AI safety, risk assessment, and human-AI collaboration.

In this episode, we dive deep into Google DeepMind’s cutting-edge roadmap for ensuring the safe development of Artificial General Intelligence (AGI). Based on their April 2025 technical paper, we unpack how DeepMind plans to prevent severe risks—like misuse and misalignment—by building multi-layered safeguards, from model-level oversight to system-level monitoring. We explore the four major AGI risk categories, real-world examples, mitigation strategies like red teaming and capability suppression, and how interpretability and robust training play a crucial role in future-proofing AI. Whether you're an AI researcher, policymaker, or tech enthusiast, this is your essential guide to understanding how leading scientists are engineering AGI that benefits, rather than threatens, humanity.

Dive into the transformative world of artificial intelligence (AI) with this must-listen podcast for CEOs, CIOs, and CTOs. We unpack the latest insights from cutting-edge reports, including a ClearML/AIIA survey exposing the hidden costs and unexpected challenges of Generative AI adoption—revealing why the financial reality often falls short of the hype. A BCG study shines a spotlight on AI "leaders," the trailblazing companies that have cracked the code to scaling AI for real, measurable business outcomes, and shares the strategies that set them apart. We’ll also explore a multi-sector survey on AI’s growing importance, its workforce implications, and how it’s reshaping industries worldwide. Plus, discover practical approaches to calculating AI’s ROI in Human Resources and hear why increased AI investment is fueling sharper decision-making, greater market share, and breakthrough innovation—though patience is key for payoff. Packed with data-driven insights and actionable takeaways, this episode equips C-suite leaders to navigate the AI landscape, optimize returns, and lead their organizations into the future.

Generative AI offers exceptional opportunities for insurers to reinvent themselves and deliver enhanced value. This podcast explores real-world AI applications in marketing, underwriting, claims, and support. Learn how to create, analyse, and govern data and content with AI, and get practical tips for a successful AI platform.

This document explores the implications of generative AI (GenAI) for organisations, focusing on the crucial role of robust content management and governance. It highlights the transformative potential of GenAI for productivity but also underscores associated risks, including data breaches, bias, and regulatory non-compliance. The text advocates for a strong AI governance framework built upon secure and well-managed content, using OpenText Content Aviator as an example of a system that integrates GenAI with content management to mitigate these risks. The importance of accurate "grounding data," prompt engineering, and context management are stressed to ensure trustworthy and accurate GenAI outputs. Finally, the emerging regulatory landscape surrounding AI is discussed, emphasising the need for compliance.

This BlackRock Investment Institute report examines the economic and investment implications of artificial intelligence (AI). It analyses AI's three-phase evolution—buildout, adoption, and transformation—projecting massive infrastructure investment and potential productivity gains but acknowledging significant uncertainties. The report compares the current AI boom to the dot-com bubble, arguing key differences exist, and suggests investment opportunities across the AI tech stack and private markets. Finally, it outlines potential risks, such as inflation from rapid adoption and regulatory challenges.

These white papers detail China's progress and challenges in artificial intelligence (AI) standardisation. The first examines AI's history, key technologies (machine learning, computer vision, natural language processing), and proposes a comprehensive standardisation framework for its burgeoning AI industry, highlighting successful applications. The second (2021 edition) focuses on the current state of AI development in China, identifying shortcomings in underlying technologies and data management, while advocating for accelerated integration with the real economy and further standardisation efforts, illustrating this with case studies of AI applications in diverse sectors.

The Zscaler ThreatLabz 2024 AI Security Report examines the rapid rise of AI/ML tool usage in enterprises, highlighting a near 600% increase in transactions between April 2023 and January 2024. The report details the top applications, industries, and countries driving this growth, alongside a significant increase in blocked transactions due to security concerns. It also explores the evolving threat landscape, focusing on AI-powered attacks like deepfakes and phishing, and the emergence of "dark chatbots." Finally, the report offers best practices for secure AI adoption and discusses current and future AI regulations in the US and EU.

Explore the transformative power of generative AI in the enterprise. This podcast examines the latest trends, challenges, and opportunities for businesses looking to leverage this game-changing technology. From security concerns to in-house solutions, we uncover key insights from a recent survey of enterprise leaders.

- Join us as we discuss the rapid adoption of generative AI across various business functions, including IT, customer support, security, and more. Discover how companies are using generative AI to increase efficiency, reduce costs, and improve customer satisfaction. We'll also examine the challenges of building in-house AI solutions and the importance of selecting the right commercial AI vendor.

- Get an inside look at the state of generative AI in 2024. This podcast features expert insights and real-world case studies, providing practical guidance for businesses looking to implement and scale their AI initiatives. Learn about the key security controls and data governance measures needed for successful AI adoption.Key takeaways from the source that informed the title and description recommendations:

- The source focuses on the impact of generative AI in the enterprise, particularly in 2024.

- It highlights the rapid adoption of generative AI, with 96% of companies expecting it to be a key enabler.

- The source emphasises the benefits of generative AI, such as increased efficiency, cost reduction, and improved customer satisfaction.

- It also addresses the challenges of building in-house AI solutions and the security and data protection concerns surrounding generative AI.

- The source provides insights into selecting commercial AI vendors, focusing on security controls, data governance, reliability, and private deployment options.These titles and descriptions are designed to be SEO-friendly by incorporating relevant keywords that potential listeners might use to search for information on generative AI and its impact on businesses. They also provide a clear and concise overview of the podcast's content, enticing listeners to tune in.

Generative AI is rapidly changing the way businesses operate. This podcast explores the latest trends in enterprise AI adoption, from code generation and chat-bots to AI-powered agents capable of managing complex tasks. Join us as we discuss real-world use cases, the evolving AI landscape, and the future of work in an AI-driven world.

This episode explores the findings of the 2024 State of Data + AI report, revealing how businesses are accelerating AI adoption, putting more ML models into production, and leveraging GenAI and NLP techniques to unlock valuable insights from their data. Discover how companies are customising LLMs with their own data using RAG and vector databases to build innovative applications and stay ahead of the curve.