Figma adds code layers, support for animations, more AI features in new update

techcrunch.com Jun 24, 2026

Figma adds code layers, support for animations, more AI features in new update

Curated by Shubham · TechCapsules · Jun 24, 2026

AI-summarised brief · reviewed before publication

Figma has released an update that adds code layers, support for motion and shaders, and AI-powered features to its design platform. The update enables teams to clone repositories and extract flows from code to design layers for testing. Figma's chief product officer, Yuhki Yamashita, stated that code layers facilitate collaboration between designers, product managers, and programmers by allowing them to iterate on ideas without focusing on pristine code. The update also includes support for animations, transitions, and 3D transforms, as well as integration with AI tools like Weavy and Notion.

💡 Why It Matters

· The update marks a significant shift towards code integration in Figma, enabling designers to work more closely with engineers and product managers.
· By streamlining the hand-off between coding and design, Figma is poised to become an even more essential tool for collaborative design and development.

AI Apps Capsules

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Trillion-Dollar AI Bubble On Verge Of Popping?

The artificial intelligence (AI) industry is facing concerns about its financial sustainability, with some experts warning of a potential "bubble explosion." Noted AI researcher Yann LeCun has stated that the industry's costs are not decreasing quickly enough to match the rising prices of AI services, leading to significant losses for companies. LeCun also highlighted the struggles of xAI, a company acquired by SpaceX, which has resorted to renting out its excess computing infrastructure to competitors. Meanwhile, a recent report found that 95% of organizations see no measurable return on their investment in AI technologies.

💡 The AI industry's financial reckoning could have far-reaching consequences for the tech sector, with potential implications for investors and companies alike. As the industry's costs continue to outpace revenue, companies may be forced to raise prices or cut costs, which could lead to a significant shift in the market.

quantumcomputingreport.com · Jun 24

Aegiq deploys automated AI calibration and NVIDIA-accelerated tensor networks for extreme-scale fluid…

Aegiq, a UK-based photonic quantum computing company, has unveiled technical milestones that integrate artificial intelligence and tensor network mathematics into its hardware operations and high-performance computing software stacks. The developments address key scalability bottlenecks in hardware stability and computational fluid dynamics. By leveraging NVIDIA's AI frameworks and accelerated architecture, Aegiq has demonstrated automated system optimization and logarithmic scaling models capable of handling extreme-scale engineering data.

💡 The integration of AI and tensor network mathematics into Aegiq's hardware operations could revolutionize the field of computational fluid dynamics, allowing for faster and more accurate simulations of complex fluid systems. This could have significant implications for industries such as aerospace and automotive, where accurate fluid dynamics simulations are critical for designing and optimizing new products.

expresscomputer.in · Jun 24

The code writes itself. Now what? The bottleneck isn’t your engineers anymore

Raghav Bansal, a management consultant, highlights the transformative impact of agentic AI development tools on software development. Companies adopting tools like Kiro and Cursor are witnessing significant productivity gains, with projects completed in weeks instead of months. The tools work seamlessly within the software delivery lifecycle, generating architecture, writing code, and creating tests, among other tasks. Early adopters have reported substantial time savings, with one multinational bank completing a quarter-scale modernization project in just two weeks. This shift is changing the bottleneck from developer availability to clarity in decision-making.

💡 The emergence of agentic AI development tools is forcing companies to rethink their priorities, as the time and cost savings are outpacing the ability to decide what to build. This new bottleneck is centered around clarity in decision-making, making product managers, business owners, and domain experts critical to the development process.

artificialintelligence-news.com · Jun 24

Anthropic drops ‘workplace AI agents’ directly inside Slack

Anthropic has launched a beta version of its Claude Tag feature for Enterprise and Team tiers, integrating its chat model directly into shared Slack channels. Users can pull the artificial intelligence model into active group threads by typing @Claude, allowing team members to delegate tasks, review outputs, and pick up discussion threads from previous points. This integration follows a $65 billion funding round and aims to reduce back-and-forth movement between team chats and browser instances. Anthropic's enterprise adoption rate has reached 34.4%, surpassing OpenAI's 32.3% footprint.

💡 The shift to shared workplace AI agents like Claude Tag could fundamentally alter how companies manage knowledge work, reducing task friction and capturing context across changing project teams. By centralizing information logs directly inside active threads, companies can optimize routine knowledge work and reduce time spent on manual codebase tracking or database updates.

memeburn.com · Jun 24

Signal’s President Has a Warning About AI Chatbots in 2026

Signal's president, Meredith Whittaker, has warned about the dangers of AI chatbots in 2026, stating that they are not conscious beings but rather pattern-matching machines. Whittaker emphasizes that AI agents, such as Microsoft Copilot, demand deep system access to users' messages, calendar, and finances, creating a surveillance backdoor. She argues that users do not fully understand what they are agreeing to when using AI-powered services, which are built on data collection and targeted advertising.

💡 The convergence of autonomous AI agents, device-level message scanning, and advertising models that monetize user data is quietly building a surveillance system. This infrastructure threatens users' privacy and autonomy, as they trade off security for convenience and efficiency.

computerweekly.com · Jun 24

Gartner: AI coding agents will cost more than real developers

Research by Gartner Peer Insights has found that 23% of tech leaders are spending $200 to $500 per developer per month on tokens for artificial intelligence (AI) coding agents. The shift from seat-based licensing to consumption-based pricing by AI coding agent providers is introducing highly variable cost structures for software engineering workloads. Gartner warns that companies lack transparency into token consumption, limiting their ability to accurately forecast and control costs. By 2028, AI coding costs are forecasted to overtake the average developer's salary due to rising large language model token consumption.

💡 The rising costs of AI coding agents threaten to upend the economics of software development, forcing companies to justify the value of paying large monthly fees to support AI usage. As costs increase tenfold or even 100-fold, IT leaders must reassess their software engineering processes to identify areas where AI can be optimized and costs can be justified.