You only need about seven core building blocks to solve almost any business problem with AI. 1. Intelligence (LLM)
2. Memory
3. Tools
4. Validation
5. Control
6. Recovery
7. Feedback
AGENTS
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Seven Core Building Blocks to Solve Business Problems
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Strategic LLM Integration Over Full Automation Frameworks
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They're mostly deterministic software with strategic LLM calls placed exactly where they add value. The problem is that most frameworks push the "give an LLM some tools and let it figure everything out" approach.
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Simple Custom AI Blocks Beat Agent Frameworks
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Most successful AI applications I've seen are built with simple, custom building blocks, not agent frameworks. This is because most effective "AI agents" aren't actually that agentic at all.
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Building Cost-Effective AI Agents Without Expensive LLM Calls
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Making an LLM API call is the most expensive and most dangerous operation in modern software development. While incredibly powerful, you want to avoid it at all costs and only use it when absolutely necessary. Here's how to build AI agents that actually work:
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New AI Automation Module with n8n Agents Launches 17 Lessons
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C’est le jour J ! Je vais être clair : c’est le meilleur contenu que j’ai jamais produit et c'est VOUS qui allez en bénéficier. Le module automatisation-agents IA / n8n est officiellement en ligne. 17 nouvelles leçons (qui viennent s'ajouter aux 90 précédentes sur l'IA),
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Testing AI Models Through LMArena: Summit Model Access
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This is through LMArena, where you are given random models to test. You will likely get a chance to use "Summit" fairly often (it came up three times in my six attempts):
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GenAI Strategy: Shaping Your Future or Derailing It?
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Will Your Gen AI Strategy Shape Your Future or Derail It? https://
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FSw
… #hbr #RAG #AgenticAI #AIagentInnovation #AIAgents #LLMs #LLM #GenerativeAI #GenAI #technology #TechRevolution #tech #Engineering #ArtificialIntelligence #AutonomousIntelligence #AI @sonu_monika
