A lot of people assume that there are more objective answers out there than there actually are. I don't think sycophancy is a huge issue in math, but you want advice? Feedback on writing? Help with an idea or project? Lots of areas where current mode default to too nice.
AGENTS
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AGI Alpha: Ascending Together with Artificial General Intelligence
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[ α‑AGI Ascension ] “We Choose to Ascend with AGI” https://
agialphaagent.com Together, we choose not merely to witness the dawn of #AGI, but to ascend with it. #AGIALPHA #AscendWithAGI -
DeepAgent Successfully Replicates Notion Clone in Single Attempt
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Deepagent one shots a notion clone
— Abacus.AI (@abacusai) 6 juillet 2025
We are working on multi-turn optimization next pic.twitter.com/K0jTYrNv8eDeepagent one shots a notion clone We are working on multi-turn optimization next
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Deep Research Agents: Comprehensive Survey of LLM-Powered Systems
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6. Deep Research Agents Provides the most comprehensive survey to date of Deep Research (DR) agents, LLM-powered systems built for autonomous, multi-step informational research.
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Evaluating LLM-Based Agents: Key Metrics and Methods
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7. Survey on Evaluation of LLM-based Agents Overview of how to evaluate LLM-based agents, which differ significantly from traditional LLMs by maintaining memory, planning over multiple steps, using tools, and interacting with dynamic environments.
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Comprehensive Threat Model for LLM-Powered AI Agent Ecosystems
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5. Threats in LLM-Powered AI Agents Workflows This work presents the first comprehensive, end-to-end threat model for LLM-powered agent ecosystems.
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Top AI Papers of the Week: Agents and LLM Research
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Top AI Papers of The Week (June 30 – July 6): – xLSTMAD
– AI4Research
– Deep Research Agents
– SLMs are the Future of Agentic AI
– Chain-of-Thought Is Not Explainability
– Survey on Evaluation of LLM-based Agents Read on for more: -
Small Language Models: Superior Future of Agentic AI
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1. Small Language Models are the Future of Agentic AI This position paper argues that small language models (SLMs), defined as those runnable on consumer-grade hardware, are not only sufficient but superior for many agentic AI applications.
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LEGO Assembly Benchmark for Robot Speed and Precision
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Is there already a "build this lego model as fast as you can" benchmark for robots?
— fofr (@fofrAI) 6 juillet 2025
– follow instructions precisely and correctly
– find the pieces needed for each instruction (starting with an unsorted pile)
– put them in the right place
– complete the model in fastest time https://t.co/Joa2dLZQNPIs there already a "build this lego model as fast as you can" benchmark for robots? – follow instructions precisely and correctly
– find the pieces needed for each instruction (starting with an unsorted pile)
– put them in the right place
– complete the model in fastest time -
Current AI Agents Complete Only 30% of Complex Tasks
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Current agents only do 30% of complex real company tasks in this paper. Though note benchmarks are a floor, not a ceiling, if:
1) More recent models show improvement in the benchmark, suggesting future models may do it
2) Better prompting/tools would make the AI perform better.