Training Long-Context, Multi-Turn Software Engineering Agents with Reinforcement Learning
AGENTS
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Building Efficient Agents While Reducing Costs
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Efficient Agents Building Effective Agents While Reducing Cost
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Karpathy’s Practical Roadmap to AI Agent Control and Validation
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8/ Karpathy’s roadmap is harder—but real. He lays out how to: • Structure validation loops
• Control agent sprawl
• Constrain generation for checkability It’s not sexy. It’s buildable. -
Outdated AI Models Undermining Complex Agent Performance
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6/ Worst part? They included GPT-3.5 Turbo and Mistral Small in their framework. These are outdated models. And they expect them to power complex agents? No wonder enterprise AI projects fail.
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DataRobot Agentic AI Transforms SAP Planning Workflows
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Planning in @SAP doesn’t need to be rigid. With SAP Endorsed Apps from DataRobot, bring agentic AI into your SAP workflows to forecast faster, optimize operations, and make better decisions without disruption. https://
bit.ly/4llKrzt #AI #agenticAI #SAP #enterpriseAI -
100+ Free Open Source AI Agents and RAG Tutorials
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Stay tuned for more such interesting posts → @Saboo_Shubham_ I have created 100+ AI Agents and RAG tutorials, 100% free and opensource. P.S: Don't forget to star the repo to show your support
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100+ Free Step-by-Step AI Agents and RAG Systems Tutorials
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100+ free step-by-step tutorials with code covering: AI Agents RAG Systems Voice AI Agents MCP AI Agents Multi-agent Teams Autonomous Game Playing Agents P.S: Don't forget to subscribe for FREE to access future tutorials.
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Nested World Models: Recursive Simulation Architecture
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A world model inside a world model 🌏 https://t.co/XQCFzy2pjc
— hardmaru (@hardmaru) 7 août 2025A world model inside a world model
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Connecting MCPs to GPTs with Custom Actions Guide
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Connecting MCPs to GPTs with custom actions is much harder than it needs to be, we wrote up a guide here for it:
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Agent steering improved with better message scheduling
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It’s now easier to steer the agent while it’s running. Sending a new message will schedule at the ideal time, usually after a tool call, versus queuing and waiting until the agent finishes. pic.twitter.com/NOfjlYlSSC
— Cursor (@cursor_ai) 6 août 2025It’s now easier to steer the agent while it’s running. Sending a new message will schedule at the ideal time, usually after a tool call, versus queuing and waiting until the agent finishes.