Learn AI engineering from scratch with this repository: → 435 lessons
→ 320 hours of content
→ Python, TypeScript, Rust…
→ Prompts, skills, agents, and MCP servers Practical exercises in each lesson
100% open source
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@nicos_ai
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Learn AI Engineering: 435 Lessons, 320h, Python, Rust, MCP, Free
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Ultra-realistic photo of a glamorous woman in a crowded stadium
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Hecho con Seedance 2.0 en Pollo AI
— Nico (@nicos_ai) 1 juin 2026
Prompt:
"Foto ultrarrealista de retransmisión deportiva de una mujer glamurosa sentada entre el
público de un estadio de fútbol abarrotado durante un partido nocturno, con un top de satén sin
mangas de cuello alto en marrón oscuro y pendientes… pic.twitter.com/yR2fWosLGMMade with Seedance 2.0 on Pollo AI Prompt:
"Ultra-realistic sports broadcast photo of a glamorous woman sitting among the crowd of a packed football stadium during a night match, wearing a dark brown satin sleeveless turtleneck top and curls" -
Everything Claude Code: the most complete open source toolkit
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You are not using 100% of Claude Code.
Until you install this. It's called Everything Claude Code and it's the most complete open source toolkit I've seen. → 30 agents, 64 skills, 33 commands
→ Integrated AgentShield with 1,282 security tests
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Claude Code Acts as an AI Agent to Find Jobs on LinkedIn
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CLAUDE CODE CAN NOW FIND YOU A JOB (literally)
— Nico (@nicos_ai) 29 mai 2026
Built with ego lite, the browser your agent drives directly.
I gave Claude Code one prompt:
→ Search LinkedIn for AI engineering roles in San Francisco
→ Full-time, on-site, posted in the last month
→ Exclude Senior, Staff,… https://t.co/kZdNlLfNMR pic.twitter.com/4TeGRBBGpfCLAUDE CODE CAN NOW FIND YOU A JOB (literally) Built with ego lite, the browser your agent drives directly. I gave Claude Code one prompt: → Search LinkedIn for AI engineering roles in San Francisco
→ Full-time, on-site, posted in the last month
→ Exclude Senior, Staff, -
AI Tool Demonstrates Precise Object Color Change in Video Editing
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haven’t seen any video tool pull this off
— Nico (@nicos_ai) 29 mai 2026
i filmed a guy playing with a red ball and asked aleph 2.0 to make it green on @runwayml
only the ball changed color
his movement, the bounce and the background stayed exactly the same
this is where “regenerating everything” and… pic.twitter.com/4ZHHUtzdjbhaven’t seen any video tool pull this off i filmed a guy playing with a red ball and asked aleph 2.0 to make it green on @runwayml only the ball changed color
his movement, the bounce and the background stayed exactly the same this is where “regenerating everything” and -
Anthropic Releases Claude Opus 4.8: Faster, Cheaper, and Smarter
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ANTHROPIC ACABA DE LANZAR CLAUDE OPUS 4.8
— Nico (@nicos_ai) 28 mai 2026
Y puede que sea su mejor modelo hasta la fecha:
→ 2.5x más rápido y 3x más barato con modo /fast
→ Trabaja SOLO como un ingeniero senior, sin que lo supervises
→ Lanza cientos de subagentes en paralelo para completar tareas complejas… https://t.co/QSIQ1rvfpo pic.twitter.com/2cNoRMTRDgANTHROPIC JUST RELEASED CLAUDE OPUS 4.8 And it might just be their best model to date: → 2.5x faster and 3x cheaper with /fast mode
→ Works ONLY like a senior engineer, no supervision needed
→ Launches hundreds of subagents in parallel to handle complex tasks on its own And -
AI Agents Need to Learn from Executions, Not Just Complexity
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Exacto. Ese es el problema que nadie estaba atacando. Todos haciendo agentes más complejos pero ninguno que realmente aprenda de sus propias ejecuciones
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AI Self-Improving Agent Outperforms Karpathy’s Autoresearcher
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Esa gráfica es clave. Se ve claramente el momento en el que el self-improving agent se despega del autoresearcher de Karpathy y ya no baja
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AI Agents Need to Learn from Executions for Meaningful Functionality
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I've been waiting for something like this for a while. Agents that don't learn from their executions make no sense.
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General-Purpose AI Agent Surpasses Karpathy’s Auto-Researcher by Self-Improvement
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A GENERAL-PURPOSE AGENT SURPASSED KARPATHY'S AUTORESEARCHER It wasn't designed for research. It simply improved itself until it achieved it The framework behind it is called SIA by Hexo Labs and it's open source → The agent updates its own logic
→ Modifies its own weights