Agentic AI failures are rarely the model—it's the retries and networking hidden in your stack. Our guide to self-managed observability:
@datarobot
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AI Investment Surges: Does It Translate to Real Impact?
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NEW: AI investment is at an all-time high, but is it actually translating to impact? Our Unmet AI Needs Survey 2026 just launched, and the results are a little….
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Create Production-Ready AI Agents in 5 Minutes with DataRobot
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Have an idea? Make it a production agent ready in 5 minutes through @DataRobot
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Multi-outcome prediction model achieves 14% improvement in 10ms
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We built a model that predicts multiple correlated outcomes simultaneously: portfolio risk, grid balancing, supply chains. In 10ms with no calibration required and it's 14% better than the best alternative. Check out the research: https://
arxiv.org/pdf/2603.20266 -
Essential soft skills for successful developers
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do you need soft skills as a developer? what does that look like?
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Deploy Your First AI Agent at 50,000 Feet
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That's a wrap on @NVIDIAGTC
! Safe travels home, everyone. Got wi-fi on your flight? Perfect time to deploy your first agent at 50,000 feet. https://
docs.datarobot.com/en/docs/get-st
arted/how-to/agents-am.html
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DataRobot Open Source Projects and AI Toolchain Insights
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Full writeup coming soon on the @DataRobot blog. Our toolchain, what's compounding, what we'd do differently and what we're looking forward to. In the meantime, check out some of our open-sourced projects! https://
github.com/datarobot-oss -
AI tooling feedback loops accelerate product development cycles
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We're doing something meta here too – building AI tooling with AI tooling creates a tight feedback loop. When engineers hit friction with our own platform, they're also the ones who can fix it. We can ship product improvement in days, not quarters. We're not building this in
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Context Windows and Agent Orientation in Large Repositories
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Context does fall apart on large repos but the windows are getting larger literally every week. You still need to spend real time learning how to keep the agent oriented. The longer the context window, the more risk for distraction and drift. Governance can be mostly automated
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AI Agents Excel at Documentation, Testing, and Engineering Onboarding
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Big wins: Docs and test coverage. Unglamorous, high-leverage, agents are good at it. Eng onboarding. New engineer + large repo + AI best practices = ramp time drops noticeably. API work. High volume, low ambiguity where the agent doesn't need to invent anything – just execute.