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We are announcing potpie AI $2.2M pre-seed fundraise to advance Spec-Driven Development for large enterprise codebases. The round is led by Emergent Ventures , with participation from All In Capital , DeVC , and PointOne Capital , along with the support of some amazing angel investors from companies including...

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New course: Spec-Driven Development with Coding Agents, built in partnership with JetBrains, and taught by Paul Everitt | @[email protected]. Vibe coding is fast, but often produces code that doesn't match what you asked for. This short course teaches you spec-driven development: write a detailed spec defining what to build, and work with your coding agent to implement it. Many of the best developers already build this way. A spec lets you control large code changes with a few words, preserve context across agent sessions, and stay in control as your project grows in complexity. Skills you'll gain: - Write a detailed specification to define your mission, tech stack, and roadmap, giving your agent the context it needs from the start - Plan, implement, and validate features in iterative loops using a spec as your agent's guide - Apply the same repeatable workflow to both new and legacy codebases - Package your workflow into a portable agent skill that works across agents and IDEs Join and write specs that keep your coding agent on track!

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.Aaron Levie says AI agents may take years to diffuse from engineering into the rest of knowledge work. "The models are really good at code, and the work is verifiable." "You have 5 or 10 things that make agents work in an enterprise context for engineering." "The users are less technical, the data is much more fragmented, the systems are much more legacy." "That's why it's going to be a number of years for this diffusion to roll from what we're seeing in Silicon Valley, into the rest of knowledge work."

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Mark Zuckerberg says the future of coding is closer than we think: AI agents inside Meta are being built not as generic developer tools, but to push Llama research forward — fully integrated into their workflow. He predicts that within 12–18 months, most of the code for these efforts could be written by AI itself — not simple autocomplete, but systems that take goals, run tests, fix bugs, improve performance, and even write higher-quality code than many skilled engineers. The real takeaway? This is only one part of a massive AI landscape, and no single company will dominate it all. Meta is building its own internal agents designed specifically to advance Llama research — deeply connected to their toolchain rather than built for enterprise customers. He expects that within the next year to year-and-a-half, AI will be writing most of the code in these projects, going far beyond autocomplete — understanding goals, running experiments, finding issues, and continuously improving systems. And according to him, this shift will become a core driver of how AI itself evolves. Meta is investing heavily in coding and research agents deeply integrated into their own systems, focused on advancing Llama rather than building broad enterprise tools. He expects AI will soon move beyond autocomplete to fully goal-driven coding — testing, debugging, improving, and producing high-quality results. But in his view, the AI revolution is too big for any single winner — multiple players and approaches will shape the future.

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2:12

We’re thrilled to share that Outset has raised $17M in Series A funding, led by 8VC to help companies better understand their customers. When michael hess and I founded Outset, we set out to solve a critical problem: truly understanding your customer is painfully slow, expensive, and at times, impossible. It shouldn’t be. We believed AI could change this by focusing on the human side of AI. So we built the world’s first AI-interviewer. An AI agent that asked questions, listened, and learned from real humans. By removing the barriers of traditional research and allowing companies to have deeper conversations with more customers more quickly, we could help teams infuse their products with genuine human understanding at a speed and scale previously impossible. So what was the moment we knew we were onto something? When WeightWatchers ran that first pilot back in early 2023. Participants shared incredible amounts of depth, all with the world’s first AI-interviewer. We got a call the next day from their head of research: "You built a thing. We want that thing. How do I pay you for it?" That validation has turned into explosive growth. We've doubled our revenue in just the last 4 months alone, with >50 enterprise customers like Nestlé, Microsoft, and WeightWatchers trusting us to unlock deeper customer insights. All of this built on the backs of a truly special early team with 0 employee turnover. This funding round was led by 8VC, with participation from an incredible group, including: Future Back Ventures by Bain & Company, Y Combinator / Garry Tan, Adverb Ventures /April Underwood / Jessica Verrilli ), Alt Capital / Jack Altman , Rebel Fund, Genius Ventures, Ritual Capital, and many more. So what's next? We're scaling our engineering and go-to-market teams to build the world's most powerful agentic customer research platform. All focused on one mission: helping companies better understand humans. To our customers, investors, and team - thank you for believing in this vision. Now check out the video to see Outset in action, testing the video itself with real people!

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Our approach to AI infra is simple: build the most fungible and flexible fleet to meet the real world's needs across inference and training as Scott Guthrie shared with Alex Kantrowitz. And we are already doing it at scale today, as we power the biggest AI workloads like Copilot and ChatGPT, APIs that power 3P products & enterprise workloads and high scale training.

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The U.S. Department of Defense is moving toward large-volume procurement of one-way attack drones, with requirements reaching up to 300,000 units over the coming years. This is a different level of scale for institutional procurement. At Ondas Capital, this is the operating model we are preparing for, working with companies already aligned with scalable production, supply chain resilience, and deployment readiness. Real capability comes from systems that can scale together, not from isolated solutions. If you are currently building for this level of production, scale, and deployment readiness, Ondas Capital is open to discussion: #OndasCapital Department of War CTO #JamesAcuna #DroneDominance #DefenseTechnology #UnmannedSystems

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16:32

Agentic AI is only as strong as the search foundation beneath it. At AWS re:Invent 2025, Nick Patience and Elastic’s GM of Search Solutions, Steve Kearns (Steve Kearns), break down how enterprises are moving from classic RAG to autonomous, production-grade agentic systems—and how Elasticsearch is enabling more autonomous, reliable enterprise workflows.

Six Five Media

223,766 Aufrufe • vor 6 Monaten