Matt Marshall
@mmarshall
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Founder, @VentureBeat
San Francisco
Joined April 2007
I went deep on this shift for @VentureBeat. Spoke with Val Bercovici about why this agentic swarm revolution has turned him from a skeptic about AGI into a believer, and @MarkRuddock about building a production-ready app on a transatlantic flight. We break down the 5
venturebeat.com
The era of "vibe coding" – the conversational, often exploratory practice of prompting an AI for code, coined by Andrej Karpathy – has given way to a more disciplined concept: agentic swarm coding.
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The conversation around AI coding is stuck on "vibe coding." There's a massive perception gap. The real story this summer is the shift to a new paradigm: agentic swarm coding. It's a move from passive prompting to disciplined orchestration, giving enterprise devs the control
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Recent events highlight a pattern: concerning online behavior often appears before real-world incidents. This isn't political—it's about protecting people and workplaces. Screen for patterns, not just history.
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‘Snitch-gate’ is already old. The real headline: give ANY agentic LLM a tool and you’ve just hired an unpredictable insider. 🛑 We unpack 6 controls to stop your bot from firing off the next “Dear FDA” email. 👇
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My latest deep dive on @VentureBeat about why Google’s bet is bold, risky—and maybe the only way to keep Search’s $200B product intact👇 🔗
venturebeat.com
Google doubles down on its ‘world-model’ vision, racing to build an AI operating layer to drive a universal personal assistant with Gemini. Even as Microsoft moves to capture the enterprise UI....
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Want to learn more about ethnic studies and the dangers of extremist ideology in K-12 schools? Make sure to subscribe to our biweekly newsletter by clicking the link in our bio.
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Google’s playing 4-D chess. Microsoft is pushing an enterprise UI for Copilot. But Sundar & team seem focused elsewhere: wiring a world-model under the hood, an AI operating layer that could reroute apps, ads, everything. If Gemini nails physics-level understanding first,
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📖 Full breakdown: How AlphaEvolve works, what it saved, and how enterprises can follow the recipe 🧠 @VentureBeat Story → https://t.co/sMf1R84CKu 🎥 Deep-dive podcast w/ @samwitteveen →
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AlphaEvolve shows what an AI agent can do when it runs on Google-level infrastructure. It clawed back 0.7% of global compute. Google published a paper on it. If you’re serious about agent deployment, it’s a great blueprint. And we explain how 👇
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Full analysis on what this means for enterprise AI, dev workflows, and the bigger picture in my @VentureBeat deep dive: https://t.co/3q6qY2f35X Original discussion w/ @Sam_Witteveen that sparked this analysis: https://t.co/wRvPlueohu Valuable context on AI's new open
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🔥 @OpenAI's $3B @windsurf_ai move: the real reason behind its enterprise AI code push. My take? It’s a high-stakes strategic play against fierce competition (think Google & Anthropic!) for AI's coding future & the crucial agentic "starting point." What's really driving this?
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Dive deeper into the Google vs OpenAI ecosystem comparison – cost advantages, agent strategies, model risks & enterprise fit post-o3: 📄 Read the full VB analysis: https://t.co/XchaaswaJ2📺 Watch the discussion with @SamWitteveen:
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Evidence: Benchmark-topping Gemini 2.5 Pro, hyper-efficient TPUs (OpenAI lacks them), real customer wins (Wayfair, Salesforce+), cohesive agent strategy & the MSFT/OpenAI 'frenemy' disadvantage. It's a compelling case for Google's AI ascendancy. Full @VentureBeat deep dive:
venturebeat.com
Google has surged ahead in the enterprise AI race after perceived stumbles. VentureBeat details the Gemini models, TPU advantage & agent ecosystem driving its turnaround.
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"Catch up, to catch us." ← Google's enterprise AI sentiment shift is real. My @VentureBeat analysis argues they've seized the lead. How? Deep integration competitors can't easily match (TPUs+Gemini+Stack). #EnterpriseAI #GoogleCloud #AI #GoogleVsMicrosoft More 👇🧵
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Their assistant, Fargo, now serves 20.1M users. No PII leaves the system. No humans touch the flow. Just a model (Google Flash 2.0) pulling intent from scrubbed input. Everything else — from retrieval to computation — stays internal. More than doubled growth targets, to 245M
venturebeat.com
Wells Fargo’s generative AI assistant, Fargo, surpassed 245 million interactions in 2024 using a model-agnostic architecture powered by Google’s Flash 2.0. The bank’s privacy-forward orchestration...
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245M+ AI interactions. 0 humans in the loop. 0 PII sent to the LLM. @WellsFargo has quietly shipped one of the boldest real-world AI deployments in banking — and it actually works. Huge credit to CIO Chintan Mehta for showing how smart orchestration > model hype.👇
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Dive deeper into this development and its implications for enterprise AI in our discussion with @samwitteveen: @VentureBeat article: https://t.co/RHfFKicOv0 Video: https://t.co/k5tHImgoRn
#AIagents
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🚨 The AI agent race just took an unexpected turn. Forget Google, Microsoft, and OpenAI. A startup with Chinese roots, @genspark_ai , has unveiled Super Agent -- an AI that plans your trips, books reservations via realistic voice calls, and leads the GAIA benchmark...⬇
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What Gemini 2.5 Pro means for enterprise AI👇 — New level of chain-of-thought clarity — 1M token context = full codebase reasoning — Handles images like an agent — Actually useful. Fast. Steerable. Trustable. More in my breakdown @VentureBeat ⬇️ https://t.co/4fX5WpQAVt And
venturebeat.com
Gemini 2.5 Pro marks a significant leap forward for Google in the foundational model race – not just in benchmarks, but in usability. Based on early experiments, benchmark data, and hands-on develo...
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🔥 Everyone slept on it… But Google just dropped the smartest LLM you’re not using. Gemini 2.5 Pro didn’t get the spotlight — OpenAI’s Ghibli avatars did. But here’s the thing 👇 This model thinks better than anything I’ve tested. And it shows its work. Step by step. Bullet by
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