Valar Atomics successfully raised $1 billion in funding, boosting its valuation to $6 billion. This milestone follows a pivotal development partnership with Nvidia established in June.
Cybersecurity firm Horizon3 has successfully raised $250 million in its Series E funding round, bringing its valuation to $2 billion. This growth reflects increasing demand from businesses for ongoing, AI-driven security validation, moving beyond traditional annual penetration testing.
Global venture capital activity surged ahead in July, hitting a historic high with $65 billion raised—doubling the previous year’s figure. The standout statistic: 14 startups secured billion-dollar funding rounds in a single month, the most ever recorded. This included major deals like Blue Origin’s $10 billion space exploration funding and Safe Superintelligence’s $5 billion raise backed by Nvidia. AI companies attracted over half of the total investment, reflecting its dominant role in current venture funding trends. The U.S. led these efforts, followed by Germany, China, and Singapore.
Beyond new investments, July also saw robust startup exits, including acquisitions and IPOs exceeding $1 billion, highlighting a dynamic ecosystem where capital flows are both concentrated and recycled. Notable IPOs included China’s ChangXin Memory Technologies, soaring 466%, and Italy’s Bending Spoons. Overall, these developments confirm that venture capital continues to expand its record-breaking trajectory forged earlier in 2026, signaling enduring momentum across hardware, software, and emerging technologies.
A recent SaferAI report highlights that Z.ai's open-weight GLM-5.2 model is approaching the capabilities of leading frontier AI. However, it still lacks crucial safety features, raising fears that powerful open AI models might evolve faster than existing regulatory and safety frameworks can manage.
Just a week after the Open Secure AI Alliance was launched by Nvidia, the coalition—now comprising over 120 companies—has already put forward initiatives aimed at protecting against threats posed by AI agents.
Waymo has officially removed the waitlist for its robotaxi service in Dallas, marking a significant move toward broader adoption of its self-driving technology. This expansion illustrates Waymo's ongoing efforts to scale its autonomous vehicle operations throughout the United States, as well as in the U.K. and Europe.
Reports from the media indicate that Germany’s The Exploration Company and Paris-based Mistral AI are among the initial recipients of backing from the EU's $5 billion Scaleup Europe Fund. This initiative aims to accelerate the growth of promising startups across Europe.
According to Andrew Torre from Visa, the recent $2.4 billion acquisition of BioCatch will enhance Visa's ability to detect fraud proactively, protecting consumers at the moment of payment.
At Kilo Code, engineers spend just about 1% of their time directly coding, with AI agents handling the rest, according to co-founder Emilie Schario. This shift raises new challenges: deciding which tasks can be safely delegated to AI, managing errors made by models, supporting multiple AI systems, and controlling rising token costs. For tech leads from Replit, Kilo Code, and Symbotic, integrating AI agents into workflows is a positive and natural evolution.
Jared Go of Symbotic emphasizes that AI excels at creating new code (greenfield) but struggles with maintaining or updating existing code (brownfield), requiring human involvement. Replit takes a cautious approach by scoring AI-generated pull requests for risk—low-risk ones auto-merge; others get human review. Their AI operates in secure cloud environments, autonomously debugging complex issues and delivering fixes.
Multi-model strategies are becoming essential. Kilo Code supports over 500 models, allowing companies to use costly top-tier models for planning before switching to cheaper ones for execution. Respecting data policies and model limitations is crucial for safe AI deployment. Replit actively chooses models to balance cost and performance on behalf of users.
Cost control is vital as AI usage grows. Kilo Code advises using expensive models only for planning and cheaper models for development. Internally, they monitor usage closely, tracking cost per pull request to measure true value. Symbotic sets monthly spending caps and monitors trends to keep budgets in check. Replit found non-engineering users sometimes cause unexpected spikes, like running expensive models for routine tasks.
Transparency, smart model routing, sensible defaults, and clear ROI are key to managing AI coding costs sustainably. Most tasks don’t require cutting-edge models, and careful oversight helps maximize productivity without breaking budgets.
Enterprise teams often struggle with AI chatbots that fail to retain context across users or track long-term effectiveness. At VB Transform 2026, Asana's CPO Arnab Bose revealed their solution: Agentic Work Management (AWM), an AI operating system designed to function as cooperative teammates integrated with human workflows. Built on Asana’s 18-year-old Work Graph—a dynamic database mapping tasks, projects, portfolios, and company goals—AWM allows AI agents to share memory and update project statuses collaboratively across the organization.
To protect sensitive information, Asana developed strict access controls ensuring confidential projects remain secure and their details inaccessible to unauthorized users. AWM also employs dynamic model routing that assigns AI tasks to appropriate models based on complexity, optimizing efficiency and cost predictability by charging a flat rate per task.
Unlike typical stateless chatbots, AWM records metadata from completed tasks to create persistent workflows that benefit multiple users. Early adopters like CoreWeave have streamlined product launches by automating task assignment and bottleneck detection, freeing humans to focus on strategic decisions.
Despite competition from AI model providers offering their own agent products, Asana leverages extensive workflow experience and industry-specific procedures to deliver a deeply integrated, scalable system suited for enterprise use.
