Core Viewpoint - SoundHound AI is positioned as a potential rebound candidate in the AI sector, with significant stock price declines over the past year, suggesting a possible recovery by 2026 [1][2]. Company Overview - SoundHound AI initially gained attention after Nvidia acquired a stake in the company, but the stock price fell sharply after Nvidia sold its shares for profit [2]. - The company has evolved from a music recognition app to a voice AI platform, demonstrating adaptability in the tech landscape [3]. Technology and Innovation - SoundHound's voice technology goes beyond basic transcription, utilizing patented "speech-to-meaning" and "deep meaning understanding" technologies to interact more naturally with users [4]. - The company has established a presence in the automotive sector, enabling voice commands for navigation and real-time assistance from auto manuals [5]. - In the restaurant industry, SoundHound's technology facilitates order-taking through various channels, enhancing operational efficiency [6]. Strategic Developments - The acquisition of Amelia, a provider of virtual agents, has allowed SoundHound to enhance its voice platform and pivot towards voice-powered AI agents capable of complex interactions [7][8]. - The new Amelia 7 platform is being rolled out to major customers, focusing on AI agents that can handle intricate customer and employee interactions [9]. Market Position and Growth Potential - As the industry shifts from generative AI to AI agents, SoundHound's voice-first approach may provide a competitive advantage [10]. - The company has experienced rapid revenue growth, with a doubling of revenue in the first nine months of the year and a 68% increase in the last quarter [11]. - SoundHound is approaching EBITDA profitability, with expectations to achieve this milestone in Q4 if revenue targets are met [11][12]. - The company has significant growth potential as it embarks on its AI agent journey, with prospects for continued revenue growth and improved gross margins [12].

3/ What’s next:The conversation then turns toward the broader context:As AI agents begin operating online, they’ll need the same guarantees that financial systems require — verifiable behavior, not blind trust.Polyhedra’s upcoming verifiable AI layer provides exactly that:· Cryptographic assurance about which model produced an output· Protection against tampered or spoofed responses· A foundation for responsible, auditable agent behavior across the internetFor Ocash specifically:· Testnet is live· Mainnet a ...

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Are you ready to talk to an AI about your next refund? Launched in 2023, the startup is already a $1.5 billion unicorn, leveraging AI agents that handle common tasks (like returns and credit card replacements) with empathy and nuance—minus the human element of exhaustion or bad attitudes. Read more: https://t.co/4nD8bOLbZo #ForbesUnder30 (Photo: Sebastian Nevols for Forbes) ...

AI agents are the future of DeFi.But they’re only as effective - and secure - as the stack they’re built on.Use 1inch Business for:<100ms latency99.9% uptimeBuilt-in MEV protectionAnd more - across 15 Web3 APIs enterprises trust to scale. https://t.co/pCe5Qp1n8z ...

My partners at Talus just released their tokenomics.30% to community and ecosystem growth.Talus is building in the automation vertical which already is a $20B+ USD market, with n8n proving demand (but centralized).With Nexus, they already have a functional decentralized-automation network operating in pre-mainnet, targeted for Q1 2026.It enables devs to launch verifiable revenue-generating AI agentsPartnerships with Sentient, Walrus and more.TGE could be coming soon, worth paying attention toTalus Foundatio ...

Company Overview - Decagon 是一家成立仅两年的公司，由连续创业者创立 [1] - Decagon 的 AI 代理已被 100 多家公司用于处理客户服务任务 [1] Competitive Landscape - Decagon 是一家年轻且渴望成功的团队，面临着资源充足的行业巨头的竞争 [1]

Amazon previews 3 AI agents, including ‘Kiro’ that can code on its own for days https://t.co/245be8foqh ...

Core Insights - Okta Inc reported a strong performance for Q3 fiscal 2026, exceeding both revenue and earnings expectations [1][2] Financial Performance - Q3 revenue reached $742 million, surpassing analyst estimates of $730.36 million [2] - Adjusted earnings for the third quarter were 82 cents per share, exceeding expectations of 76 cents per share [2] - Total revenue increased by 12% year-over-year, with subscription revenue rising by 11% [3] - Remaining performance obligations at the end of the quarter totaled $4.29 billion, reflecting a 17% year-over-year increase [3] - Net cash provided by operations was $218 million, up from $159 million in the same quarter last year [3] - Free cash flow for Q3 was $211 million, an increase from $154 million year-over-year [3] Cash Position and Outlook - Okta ended the quarter with approximately $2.46 billion in cash, cash equivalents, and short-term investments [4] - The company expects Q4 revenue to be between $748 million and $750 million, compared to estimates of $737.92 million [4] - Projected Q4 adjusted earnings are between 84 to 85 cents per share, aligning with estimates of 84 cents per share [4] - Full-year revenue guidance has been raised to between $2.906 billion and $2.908 billion, compared to previous estimates of approximately $2.89 billion [5] - Full-year earnings guidance is now expected to be between $3.43 and $3.44 per share, up from estimates of $3.37 per share [5] Market Reaction - Following the earnings report, Okta shares fell by 4.31% in after-hours trading, priced at $78.34 [6]

Core Argument - The IDE is not dead; human interaction with source code remains essential, even with AI assistance [1][8][11] - Source code is a language intended for human consumption, requiring visual interfaces for understanding AI agent actions [3][8][9] - The best user interface for code interaction is likely a GUI, optimized for presenting and navigating source code [12][13] Zed's Vision and Strategy - Zed aims to provide the ultimate interface between humans, source code, and AI agents, acting as a "Switzerland" for collaboration [41][40] - Zed is building a vertically integrated environment with fine-grained tracking of code evolution, enabling anchored conversations and interactions [38][39][40] - Zed's architecture prioritizes performance, aiming for zero perceptible lag in keystroke feedback [30][31] - Zed is designed as an inherently collaborative environment for multiple humans and AI agents [81][82] Agent Client Protocol (ACP) - ACP aims to democratize AI agent integration, allowing developers to use various agents with a great UI, similar to the Language Server Protocol [44][46] - ACP facilitates the externalization of agent intelligence, enabling different agents to compete and specialize in particular problems [45][46] AI's Role in Coding - LLMs are good at generating code from well-known knowledge and implementing code from abstract models [71][75] - LLMs are less helpful when the task involves novel problem-solving or when the code is not the primary constraint [72][73][76] - The industry is exploring how to manage multiple conversations with multiple agents and make those conversations more valuable [88] User Base and Adoption of AI - Zed has approximately 170,000 active developers, many of whom are experienced engineers [2][54] - About half of Zed users are using edit prediction, and a quarter are using agentic editing [56] Future IDE Evolution - The IDE will evolve into a collaborative environment where conversations with agents can be shared with human teammates [82] - Codebases will become metadata backbones, with conversations, edits, and context linked directly to the code [83][84] - The IDE interface will evolve to put conversations front and center, potentially modeling conversations as evolving documents [85][89]