Amit Rathore

We chose a good subject for our march Autotech Council meeting, and after this year's CES, it seems even more obvious. Our meeting on the AI Defined Vehicle will show how it's a natural next step after the Software Defined Vehicle phase that we've been in Tesla launched the Model S in 2012. Now, most carmakers have SDVs. It's time to layer on the AI in user-facing roles, and in invisible functions managing the vehicle.

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A useful discussion of the differences between co-pilots, agents and AI workflows. From Jack Mu at Paragon. Clarity leads to better design, and to better pricing. https://lnkd.in/g_Xkf5AT? #AI #agents #copilots #workflows

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The following article is a couple years old (and my personal favorite I’ve written) but there’s more urgency then ever to incorporate foresight and applied futures into strategy work because of the mind blowing exponential growth of new technologies. Build for the needs of tomorrow and expect the ground beneath your current strategy to shift. The same methods that reveal opportunity also expose where your current bets become liabilities as markets, regulations, and societal expectations evolve.

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AI Agents: Powerful, But Not Plug-and-Play After reviewing this insightful article on the challenges of AI agents (link: https://lnkd.in/gaw97Mwv) I wanted to echo a hard-earned truth: Teams without real-world experience in deploying AI automations are walking clients off the hype train and into the trough of disillusionment. The right approach to AI isn't blind automation — it's strategic augmentation. From our work supporting high-stakes environments like nuclear operations, mechanical repair, and surgery, we've seen firsthand how critical it is to apply guardrails, checkpoints, and human-in-the-loop oversight to mitigate hallucinations and ensure reliable, deterministic outcomes. Beware automation providers pushing no-code/low-code tools that “replace your team.” That pitch might sound great — until you realize there's no one left to supervise the machine. We believe in professional-grade automation: Tools that empower your existing team to work smarter — freeing them to focus on what really matters: customer experience, strategy, and growth. If you're thinking about integrating AI agents into your business operations, don't fall for hype. Find a partner who knows how to balance innovation with precision. Reach out to Aptitude AI for your free Automation Audit: https://lnkd.in/g8sWBgA5 #AIAgents #Automation #ProcessEngineering #DigitalTransformation #ResponsibleAI

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Most teams don’t struggle with AI agents because the technology is immature. They struggle because prompting is not treated with design discipline. An agent prompt is not a single instruction. It’s a system of assumptions, constraints, and decision rules. When those aren’t explicit, reliability breaks down fast. That’s why two teams can use the same models and get completely different outcomes. This guide breaks down how to design agent prompts the way operators design systems. Intentionally, repeatably, and with scale in mind. Full breakdown here: https://lnkd.in/gzhuQgRW #Agents #Prompting #AI

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For VoiceAI technology to mature and lead to real world use cases more successfully, the models need to be able to both listen while talking and talk while listening. And be able to change their responsiveness and interruption sensitivity dynamically based on context. This is not withstanding the underlying problem that models still can't discern the difference between "uh huh" in the context of agreeability vs "uh huh" in the context of communicating confusion. ----------------------------------------------- read more: https://lnkd.in/eqeDhdt3 Conversational AI has forced an impossible choice. Traditional systems (ASR→LLM→TTS cascades) let you customize the voice and role, but conversations feel robotic with awkward pauses, no interruptions, and unnatural turn-taking. Full-duplex models like Moshi finally made AI conversations feel natural with real-time listening and speaking, but locked you into a single fixed voice and role. #NVIDIA #PersonaPlex breaks this trade-off. Select from a diverse range of voices and define any role through text prompts. Need a wise assistant, a customer service agent, a fantasy character, or just someone to talk to? PersonaPlex delivers truly natural conversations while maintaining your chosen persona throughout. It handles interruptions, backchannels, and authentic conversational rhythm. For the first time, you get both the customization you need and the naturalness that makes conversations feel genuinely human.

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EXCLUSIVE: Under the covers of the $18m Thread investment round Harry Brelsford interviews Matt Linn, co-founder and COO of Thread, an AI service desk that automates non-billable resources on the service desk, making them billable and reducing service costs through agentic workflows. Linn shares his background from a 10-year career with an MSP in New York City. Thread is announcing a new round of fundraising at the Series A stage to accelerate R&D and build faster. The company emphasizes its unique brand and customer-centric approach, showcasing this through creative booths at events. For 2026, Thread plans to enhance product offerings with better context for agents, more auto resolutions, and zero-touch tickets.   WATCH THE PODCAST HERE   Matt Linn's Background and Introduction to Thread - Harry Brelsford introduces Matt Linn, co-founder and COO of Thread, a company described as a "Wall Street darling" in the MSP industry. - Matt Linn shares his background, mentioning his 10-year career with an MSP in New York City called RFA, which focused on hedge funds and private equity funds. - Matt explains his passion for solving industry problems and his decision to create Thread to enhance the MSP business model. - Harry Brelsford asks Matt to provide a concise elevator pitch for Thread. Thread's Elevator Pitch and AI Service Desk - Matt Linn describes Thread as an AI service desk that automates non-billable resources on the service desk, making them billable and reducing service costs through agentic workflows. - Thread aims to create a new business model for MSPs with better unit economics and competitiveness at scale. - Harry Brelsford inquires about any breaking news from Thread. - Matt announces a new round of fundraising at the Series A stage, aiming to accelerate R&D to build bigger, better, and faster than ever. Brand Recognition and Innovative Booths - Harry Brelsford comments on Thread's strong brand recognition and the positive feedback they receive. - Matt emphasizes the importance of Thread's radical and customer-centric approach, highlighting their unique and intentional marketing strategies. - Matt shares examples of Thread's creative booths at events, such as a carnival nightmare theme and a Candy Cane Lane booth, to illustrate their commitment to innovation and customer experience. - Harry recalls past experiences with Thread's themed events, including a party bus and various costumes, showcasing their creative marketing efforts. Future Plans and Final Thoughts - Harry Brelsford asks Matt about any upcoming plans for 2026. - Matt reveals that Thread will be investing heavily in product development, focusing on providing better context for agents, more auto resolutions, and zero-touch tickets. - Harry thanks Matt for his participation and mentions the positive feedback on the MSP forecast. - Matt concludes by reiterating Thread's commitment to innovation and improving service efficiency for MSPs. https://tel…

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The next frontier of AI isn't just about choosing the right model. It's about building moats through implementation. Across the Emergence Capital portfolio, companies like Bland and Federato are scaling faster by embedding Forward-Deployed Engineers. These engineers bridge the gap between AI and reality, ensuring real results in production. Read more from my colleagues Gordon and Kyle on why FDEs are the key to unlocking AI's full value. https://lnkd.in/gcsRRGX2

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As mentioned, over the weekend I went deep into research with Claude to answer a question that folks have been debating a lot lately: are we actually in an AI bubble, and if so, where in the curve are we? My gut has been telling me that if we are in a bubble, we are still much closer to the beginning than the middle or the end. After spending hours digging through data, economic models, and market behavior, that instinct looks pretty aligned with the evidence. Here are the three metrics that will determine how this plays out: 🔹 Daily active usage of AI tools must cross 15 percent of U.S. adults to signal mainstream adoption. Today we sit around 7 to 8 percent, projected to reach 11 to 14 percent by the end of 2026. 🔹 Enterprise pilot to production conversion rates need to hit 40 percent by late 2026. Right now we’re at roughly 31 percent, with 42 percent of pilots abandoned. 🔹 Foundation model profitability has to arrive by 2028 to 2029 to justify the current infrastructure spend before debt maturities force restructuring. OpenAI projects 2029 to 2030, which requires 10x revenue growth. Taken together, the picture is clear: we look a lot more like the dot-com era at 1995 to 1996 than 1999 to 2000. The real mania hasn’t hit yet. The infrastructure buildout is happening in anticipation of the transformation, not as a reaction to peak speculation. The consolidation phase likely lies ahead, not behind. The nuance matters... The technology works. The business models are still forming. The timing is probably wrong for most investors. But the transformation is real. Whether you see the current moment as overblown or overdue depends entirely on your time horizon: 🔹 2025 to 2027: high risk for early stage AI startups and late-stage investors 🔹 Recession outlook: AI is not the primary driver; traditional macro indicators still matter far more 🔹 2028 to 2032: messy but meaningful productivity gains 🔹 2030 and beyond: AI becomes a foundational economic engine regardless of the short-term chaos The next 12 to 18 months will be the most critical period yet. If conversion, usage, and model economics improve, the current buildout accelerates. If they stall, the industry hits a forced reset that delays but does not stop long-term impact. Later this week, I am planning to share a second round of research looking beyond AI to the broader economic environment, including structural risks that could drive a recession or market correction in the US. #AIBubble #AIEconomy #TechForecasting #AITrends #AINews #AIInfrastructure

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