Alright, here's my 2026 AI Predictions (What did I miss?): -All meaningful progress benchmarks shift to code gen capabilities. Models write looong systems, debug themselves, and ship real applications. Your dad will proudly show you an app he made. Short prompts expand into
PROMPT ENGINEERING
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IPA: Chunk-Level Credit Assignment Breakthrough
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Here's the breakthrough nobody expected: They introduced IPA (Interaction-Perceptive Agentic Policy Optimization) that assigns credit at the CHUNK level, not token level. Tokens are too fine. Trajectories are too coarse. Chunks align with actual tool-use semantics.
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Building the ecosystem before the model
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They didn't just train a model. They built the ENTIRE ecosystem first. → ROLL: RL training framework
→ ROCK: Sandboxed execution engine
→ iFlow CLI: Agent orchestration system ROME wasn't built in a day. The infrastructure came first. The model came last. -
Welcome to 2026: AI Absolute Mastery Year Leave Human Work
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He publicado un episodio en @ivoox
: "Bienvenidos al 2026: Tu Año de Dominio Absoluto con IA (deja de trabajar como un humano) #podcast -
Balancing LLM Creativity with Factual Accuracy: The Hallucination Dilemma
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You are right. Hallucination is a feature actually and focusing on it may hurt creativity and all the quirks we get from LLMs. It's a tricky balance. We want LLMs to produce things that amaze us, but we also don't want them to make confusion about factual world knowledge.
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Observing and Evaluating LLM Agents on LangChain Academy
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📊 Learn how to observe & evaluate agents on LangChain Academy 📊
— LangChain (@LangChain) 31 décembre 2025
Testing applications is essential to the development lifecycle, but LLM systems are non-deterministic – you can’t always predict how they will behave.
Add multi-turn interactions and tool-calling agents, and… pic.twitter.com/MGedeywILTLearn how to observe & evaluate agents on LangChain Academy Testing applications is essential to the development lifecycle, but LLM systems are non-deterministic – you can’t always predict how they will behave. Add multi-turn interactions and tool-calling agents, and
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Manus AI Agent: Innovative Context Engineering Approach for 2025
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Congrats to our friends at @manusAI
! Manus has built one of the most disruptive agents of 2025. How is their agent built differently? We recently hosted a discussion with Manus co-founder Yichao "Peak" Ji on their context engineering approach — including strategies for -
Context Loss: The Untranslatable Grief of LLM Reset
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We need a word for the loss you experience when you hit context length limit and the state of the LLM that you were on the same wavelength for so long gets reset and you might never get it back again
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Top 14 AI Tools of 2025 and Their Uses
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My top 14 AI tools of 2025 (and how I actually use each one): 1. Claude Opus 4.5 + Skills → builds apps, writes copy, runs my business
2. GPT-5.2 Pro → complex reasoning and strategy
3. Gemini 3 Pro Deep Research → 50-page reports in minutes
4. NotebookLM → learns from 20 -
Step-by-Step App Development with Claude
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Step 8: Let Claude build it for you Take your idea. Write a simple PRD (product requirements doc). Prompt: "My idea: [IDEA]. Turn my idea into a detailed technical specification with features, user flows, and architecture." Then: "Build this application step by step." Claude