💬 AI

Aider, MCP, Claude, Sonnet, LLMs, local llms,

Composing and Decomposing AI Functions (Tutorial with Python Examples)
lightcapai.medium.com·14h·
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LazyLLM, Easiest and laziest way for building multi-agent LLMs applications
github.com·7h·
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Accumulating Context Changes the Beliefs of Language Models
lm-belief-change.github.io·11m·
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I Use AI
ben.stolovitz.com·1d·
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Show HN: Kumi – a portable, declarative, functional core for business logic
kumi-play-web.fly.dev·11h·
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The Complexity Cliff: Why Reasoning Models Work Right Up Until They Don't
rewire.it·7h·
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Can LLMs subtract numbers?
arxiv.org·1d·
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Show HN: Notifikai – Set and get reminders through simple text messages
notifikai.com·1d·
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Continuous Autoregressive Language Models
shaochenze.github.io·1d·
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Show HN: Arcitext, an AI assisted writing app to battle AI generated text
arcitext.com·10h·
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AI Agent Orchestration Frameworks
blog.n8n.io·21h·
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The Ghost in the Machine Is Finally Allowed to See: A Beginner's Guide to MCP
danielkliewer.com·15h·
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Text to SQL: Local, Secure, and Smarter
exasol.com·20h·
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Choosing the best AI coding agent for Bitrise
bitrise.io·1d·
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The AI ick
stackoverflow.blog·14h·
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Lessons from Implementing RAG in 2025
truestate.io·22h·
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Planning > Agents: Getting Reliable Code from LLMs
repoprompt.com·1d·
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Show HN: Refusal-Aware Logical Framework for LLMs
github.com·1d·
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AI Function Calling: Composing and Decomposing Functions for Complex Tasks
lightcapai.medium.com·1d·
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Run LLMs Locally
ikangai.com·13h·
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