Latest Interviews
Showing 1–6 of 6 interview transcripts.
Clear all filters- a16z1h 20m
How Decagon Runs 90% of Its Agents on Open-Source Models
Sarah Wang, Kimberly Tan, Jesse Zhang, Ashwin Sreenivas
Decagon Labs challenges the prevailing 2026 narrative that AI agents will replace all software by establishing a dedicated "model factory" that prioritizes open-source fine-tuning over frontier models to achieve superior latency for voice interactions. The company differentiates its enterprise deployment through a "glass box" approach and its Duet Autopilot system, which automates the creation of agent procedures and reduces production timelines from years to months. Despite rapid international expansion and the lowering of technical barriers, Decagon contends that the primary constraint remains human talent acquisition while affirming that AI will drive new service demand rather than eliminating careers or rendering legacy SaaS obsolete.
- a16z23 min
How AI Will Impact Emergency Response: The Tech That Could Soon Save Your Life w/ Michael Chime
Prepared is an AI assistant platform currently deployed across 6,000 US 911 centers that automates non-emergency workflows and augments emergency response with real-time transcription, translation, and quality assurance. Founded by an industry veteran who recognized critical infrastructure gaps in legacy dispatch systems, the company has scaled to process over 20 million calls annually after securing $130 million in Series C funding. By offloading mundane tasks and filling capability gaps such as language barriers, the system allows operators to function more like air traffic controllers while maintaining strict data privacy compliance.
- a16z15 min
Unbundling the BPO: How AI Is Disrupting Outsourced Work
A $300 billion Business Process Outsourcing (BPO) market dominated by firms like Accenture and Wipro is undergoing a fundamental transformation as Voice AI and autonomous browser agents dismantle traditional reliance on human labor. By enabling near-zero latency processing of unstructured data across sectors ranging from healthcare to logistics, these AI-native technologies offer founders a pathway to create new value by automating complex workflows previously inaccessible to small and medium enterprises. As the industry evolves over a two-to-three-year horizon, success will depend on strategically targeting high-impact use cases where AI can flatten operational costs while navigating the structural inertia of legacy labor-heavy models.
- a16z42 min
Agents, Lawyers, and LLMs
Harvey, a domain-specific AI firm led by product leader Matish, automates legal workflows for transactional, litigation, and in-house sectors by replicating law firm hierarchies through agentic systems rather than simple chat interfaces. The company scales its adoption by employing lawyers as account executives and maintaining strict data security via an "eyes off" policy and exclusive reliance on Azure-deployed OpenAI models. As demand shifts from skepticism to active integration requests, Harvey focuses on deep workflow embedding and custom fine-tuning to return 30–40% of attorney time to high-value creative work while expanding into tax, finance, and HR verticals.
- a16z15 min
RIP to RPA: How AI Makes Operations Work
Steph Smith, Kimberly Tan, Camilla
The evolution from rigid Robotic Process Automation to AI agents powered by Large Language Models enables the handling of unstructured data and complex workflow deviations that previously required manual intervention. Industry examples like Tenor demonstrate how vertical, self-serve solutions in healthcare and logistics can eliminate low-value administrative tasks while horizontal enablers provide the foundational extraction capabilities for broader adoption. As these technologies mature over the next decade, the market is shifting from niche, high-labor-cost sectors to deep integrations with core systems, ultimately replacing manual data entry with intelligent automation that allows human workers to focus on higher-value creative roles.
- a16z12 min
Big Ideas 2024: New Applications for Computer Vision and Video Intelligence with Kimberly Tan
A16Z partners identified a pivotal 2024 thesis centered on applying computer vision to real-world industries, driven by the convergence of abundant video data, affordable edge computing, and transformer-based model innovation. Kimberly Tan highlighted the emergence of hybrid hardware-and-software business models, exemplified by Flock Safety, which are now expanding from residential safety into transportation, agriculture, and mining sectors to solve labor shortages. This shift enables natural language querying of visual data for efficiency and compliance while mitigating privacy risks through strict regulatory design and non-biometric tracking.