alecko

#it #thewinterishere #cook

[Anthropic @AnthropicAI]

We’ve received notice that the Department of Commerce has lifted export controls on Claude Fable 5 and Mythos 5.

We'll begin restoring access tomorrow, and will share an update soon.

We’re grateful to our users for their patience, and to everyone who worked with us on redeploying the models.

[Movez @0xMovez]

Anthropic engineers just showed how to build agentic systems that run for days using "loops."

"At Anthropic, >30% of our code is already written by loops - that's how we ship so fast.

in this 40-minute workshop, they reveal the whole stack:

agent loop + harness + memory + sub-agents.

Worth more than any $500 vibe-coding course.

Watch workshop today, then read article below.

[alecko @alecko]

🤔 so, we pray

[Anthropic @AnthropicAI]

Our internal data shows Claude is accelerating AI development—a possible path to recursive self-improvement, or AI autonomously building a more capable successor.

It’s happening faster than we thought, and the implications deserve greater attention. https://t.co/OVVPJO7VQx

[Kirk Borne @KirkDBorne]

Evaluating AI Agents — Bootcamp on June 27 hosted by @PacktPublishing @PacktDataML — register with my discount code 'KIRK50' at this link to save: https://t.co/2iGClh49hG

Participants will be guided through the fundamentals of Evaluating AI Agents, covering:

🟠Why modern agents fail across tool usage, planning, execution trajectories, outputs, and adversarial inputs.
🟧How to build component-level evaluations to assess tool selection, argument quality, and planning effectiveness.
🔶Methods for defining and measuring trajectory-level metrics such as step count, cost, recovery behavior, and loop detection.
🟠Techniques for creating outcome-level evaluators using multidimensional rubrics and LLM-as-a-judge approaches, and calibrating them against human evaluations.
🟧Common adversarial failure modes unique to agentic systems, with a focus on indirect prompt injection through tool outputs.
🔶Frameworks for determining which evaluation layer is most relevant based on specific use cases and team maturity levels.

[LangChain @LangChain]

Deep Agents v0.6 makes harness profiles a first-class abstraction.

Now, you can get production-grade performance from models like @Kimi_Moonshot, @Alibaba_Qwen, and @DeepSeek_ai at 20x+ lower cost than closed frontier APIs.

More on tuning:
https://t.co/6sU4M8qjRV

[alecko @alecko]

@OpenAI LOL

[SONIA @S0N_IA]

🚨 Anthropic está regalando una certificación por la que Deloitte está formando a 15.000 empleados.

0 $
Sí, gratis.
Solo necesitas un portátil. Nada más.

Se lanzó hace solo 10 días.
Casi nadie la tiene todavía.

Se llama “Claude Certified Architect”.

Piénsalo así: es como las certificaciones de AWS… pero en inteligencia artificial.
Y si viviste el boom de AWS, sabes lo que viene:
pasaron de “interesante tener” a “imprescindible para trabajar” en pocos años.

Esto va a ir MUCHO más rápido.

Mira quién ya está apostando fuerte:

- Accenture → 30.000 personas formándose en Claude
- Cognizant → 350.000 empleados ya dentro
- Deloitte → 470.000 con acceso
- Infosys → socio principal

No estamos hablando de startups probando cosas.
Son gigantes reestructurando su fuerza laboral alrededor de la IA.

Y tú puedes sacarte la misma certificación desde casa.

Pero ojo… no es un curso fácil para coleccionar insignias.

Es exigente:

- 60 preguntas en 2 horas
- Supervisado (cámara encendida)
- Sin pausas, sin Google

Te ponen en situaciones reales:
diseñar agentes de soporte, integrar IA en pipelines CI/CD…
Y las respuestas trampa están diseñadas como errores reales de producción.

Para aprobar necesitas 720/1000.

Los que ya lo han hecho dicen lo mismo:
—> arquitectura de agentes y sistemas multiagente = nivel duro

Porque esto no va de “hacer prompts bonitos”.
Va de construir sistemas de IA que funcionen en el mundo real.

Lo mejor:

- 13 cursos oficiales GRATIS (Anthropic Academy)
- Certificación gratis para los primeros 5.000
- Luego: 99$ por intento

Cómo empezar:

1. Únete gratis → https://t.co/fe0i7IJAl8
2. Empieza los cursos → https://t.co/qXJXRnY5zq
3. Regístrate al examen → https://t.co/EvVZJln5Cg
4. Haz el test de práctica
5. Preséntate cuando estés listo

Y ahí está la oportunidad.

Consíguela ahora… antes de que pase a ser el nuevo estándar.

[Dhairya @dkare1009]

Google just dropped a FREE AI Agents course.

And almost no one is talking about it.

10+ code samples, whitepapers, hands-on projects... all in one place.

Here’s the full breakdown (5 days):

Day 1: Foundations of AI Agents
Learn how agents actually work:
• Architecture
• Capabilities
• How they differ from LLMs

→ Build systems that can perceive, plan, act

Whitepaper: https://t.co/LGGc7UDLX2

Code: https://t.co/8XFiroXqKz

Day 2: Tools & MCP (Model Context Protocol)
Agents don’t work alone.

Learn:
• Tool usage & APIs
• MCP architecture
• Human-in-the-loop workflows

Whitepaper: https://t.co/YklFh27OX9

Code: https://t.co/iMMpPsEgox

Day 3: Context Engineering (Memory)
This is where agents become powerful.

• Sessions → short-term memory
• Persistent memory → long-term learning

Whitepaper: https://t.co/KWAOnwjXaz

Code: https://t.co/ctlpTBNUdU

Day 4: Agent Quality
Production-ready systems need reliability.

Learn:
• Logs, traces, metrics
• Evaluation frameworks
• LLM-as-a-judge

Whitepaper: https://t.co/kSaz3DK8Q3

Code: https://t.co/96DYJj4trU

Day 5: From Prototype → Production
Where most people fail.

• Deployment strategies
• Scaling agents
• Agent-to-Agent communication
• Vertex AI ecosystem

Whitepaper: https://t.co/rYub7sP1aP

Code: https://t.co/xtU4CTP3Ek

This is basically a complete roadmap to building AI agents in 2026.

And it’s 100% free.

Save this. You’ll need it later 💾

Like 👍 • Repost ♻️

Follow for no-BS AI insights 🚀

[LangChain @LangChain]

💫 New LangChain Academy Course: Building Reliable Agents 💫

Shipping agents to production is hard. Traditional software is deterministic – when something breaks, you check the logs and fix the code. But agents rely on non-deterministic models.

Add multi-step reasoning, tool use, and real user traffic, and building reliable agents becomes far more complex than traditional system design.

The goal of this course is to teach you how to take an agent from first run to production-ready system through iterative cycles of improvement.

You’ll learn how to do this with LangSmith, our agent engineering platform for observing, evaluating, and deploying agents.

Enroll for free ➡️ https://t.co/fok9ahXyX8

[PyCharm, a JetBrains IDE @pycharm]

#LangChain, explained properly 🧠🐍

Our complete 2026 guide walks you through building real AI agents with tools, middleware, guardrails, testing, and dynamic models – not just basic chatbots.

You can debug them all inside PyCharm, too!

Read the complete tutorial by Cheuk Ting Ho: 👉 https://t.co/xxMSTIqt1V

[alecko @alecko]

@Carlidairivero @LuisAng17345676 @IaanRL_ @midudev la sección Understanding humans toda una joya

https://t.co/le36zNcBoI

[alecko @alecko]

@MyLordBebo open-potatoes season

[alecko @alecko]

@yourtechgirl24 ALL

[Your Tech Girl @yourtechgirl24]

Stop paying for expensive courses.

I’m giving away 20+ premium courses 100% FREE — worth hundreds of dollars.

1. Artificial Intelligence
2. Machine Learning
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4. Ethical Hacking
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To get it, just:

1. Like & Retweet
2. Comment "ALL"
3. MUST be Following (so that I can dm)

[alecko @alecko]

@JulianGoldieSEO n8n

[LangChain @LangChain]

LangChain x TrueLens

TruLens is an opensource package that provides instrumentation and evaluation tools for large language model (LLM) based applications.

Thanks to @josh_reini for adding documentation on how to connect TrueLens to LangChain!

https://t.co/8h1Igcuoav

[alecko @alecko]

@calcsam Book

[alecko @alecko]

@bradsmith Tool

[Krishna Agrawal @Krishnasagrawal]

🚀 The Complete Guide to Building AI Agents, From Zero to Production

AI Agents are the next big leap in automation, they can think, plan, and execute tasks just like humans 🤖

This guide takes you from basics to building real, production-ready AI Agents — step by step!

To get your copy 👇
Like & Repost
Comment “AI”
Follow (so I can DM you the guide)

[alecko @alecko]

@Krishnasagrawal AI