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All digests tagged Agentic Workflows
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Learn how to build a fully autonomous 'Software Factory' using agent loops and feedback loops. Discover how to achieve 75% PR merge rates without human intervention, while maintaining cost control and model agnosticism.
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Contour Asset Management shares how they measure AI ROI by running live A/B tests on analyst workflows. They focus on 'cost per useful insight' and integrating disparate data sources like AlphaSense and Yipit into unified platforms.
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Modal addresses the challenge of AI workloads, which are bursty and non-rectangular. The solution involves aggregating global GPU capacity into a serverless compute platform, making compute more flexible and efficient than traditional three-year capacity commitments.
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The panel discusses securing AI software factories, arguing that agents must be treated as unpredictable actors. Key controls include enforcing boundaries, never letting agents hold credentials, and securing the dynamic supply chain.
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Is the agent harness dead? Jediah Katz explains that while models are absorbing coding skills via the data flywheel, the harness remains critical for infrastructure, security, and unlocking new, non-coding frontiers.
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Trusting AI agents requires more than just code. WorkOS demonstrates how to build robust verification loops using CLI health checks, browser snapshots, and LLM judges. Learn to make your agents self-correct and prove their work is done.
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Learn how to cut massive AI inference costs at scale. Eugene Cheah outlines four moves: Measure, Right-size, Buy Capacity Well, and Check Processes to optimize your tokenomics.
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Nemotron 3.5 Super VL is a multimodal open model built for autonomous agents. Learn how its 120B parameter architecture, optimized with NVFP4 and trained via distillation and mid-training, enables superior performance in agentic and vision-language tasks.
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The session covered the shift to agentic AI, local model deployment on consumer hardware (RTX Spark), and the open-source revolution in robotics with the MicroDuck. Key focus areas include open weights and physical AI pipelines.
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NASDAQ is adapting its infrastructure and software offerings to meet the demands of high-performance compute and agentic capabilities. The key is building a trusted 'intelligence layer' over existing financial systems.
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The video summarizes the 'Road to GTC Berlin' build series, focusing on advanced AI agents, open models, and physical AI. Key themes include agent safety, sovereign edge deployment, and multimodal interaction.
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The workshop details the shift from traditional software security to AI-native defenses, covering topics like Prompt Injection, AI Bomb inventory, and integrating security hooks into CI/CD pipelines for agentic workflows.
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Learn how to scale custom AI agents from local development to autonomous CI pipelines. Discover agentic workflows, marketplaces, and cross-repo automation using GitHub Copilot.
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Building AI-native apps requires a unified data layer. We explore how ClickHouse handles vector search, real-time event ingestion, and complex agentic workflows, making it a single platform from first feature to complex agent.
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CTO Jacob Lauritzen details how Legora scales with AI agents, discussing custom orchestration tools, agentic bug-fix loops, and why measuring AI adoption by tokens is a flawed metric.
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To manage AI spend, tag every resource and move beyond total cost. Focus on efficiency metrics like 'cost per thought,' 'reasoning ratio,' and 'cache hit rate' to truly understand AI ROI.
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The Gemini Interactions API and Managed Agents enable robust, stateful agentic workflows. Key features include persistent context via `interaction ID` and secure, remote sandboxes using `environment ID` for complex, multi-modal pipelines.
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Rowan Christmas demonstrates how coding agents can leak sensitive PII from host machines. He introduces Docker Sandboxes (sbx), a microVM solution that provides 'security by design' through kernel isolation and default-deny networking.
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Learn how to manage the exploding costs of AI agents. Experts discuss cache-aware routing, open-weight models, and why only $18 of every $100 spent on AI actually ships to users.
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The Defender's Window highlights the urgent need for a 'Defense Factory' to close the gap between advanced AI capabilities and cyber defenses. Learn how GPT-6 Astra and CodeX automate vulnerability remediation.
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