BiggB

Every Story has 3 sides: mine, yours, and the truth

[BiggB @bigbindian]

@BBCWorld Bbc🤣🤣🤣🤣

[BiggB @bigbindian]

@SrBachchan Sir, Jis din sochna band kar diya samjlo jina band kar diya. Aur apto Jindadili ka dusra naam ho. Sirf ye tweet count karna chhod do T5803 ho ya T9999 kya farq padta hai

[BiggB @bigbindian]

@VarahaWarrior No nautaki hai

[BiggB @bigbindian]

@GuavaKisan India should take the honour to recognize the republic of Balochistan

[freeCodeCamp.org @freeCodeCamp]

One LLM prompt can get messy when it has to plan, write, and review all at once.

In this tutorial, Darsh shows how to build your first multi-agent AI system in Python and LangGraph.

You'll use Ollama, Qwen, focused agent prompts, shared state, nodes, and edges to build a local study guide generator.

https://t.co/5ZJWP4cRlB

[Khairallah AL-Awady @eng_khairallah1]

Claude Code team just dropped a free course on loop engineering with Fable 5:

00:00 - how Claude Code works under the hood
05:01 - the agentic loop explained
16:21 - building agents with Fable 5
19:01 - why voice beats typing
32:34 - how to deploy agents with Fable 5
58:39 - Fable 5 for non-code work

this 30-minute watch will replace 10 paid courses about prompting Claude.

Bookmark this and read the article below.

[BiggB @bigbindian]

@TomTSEC Who know how these 125M will be used

[BiggB @bigbindian]

@iihtishamm Iran loves to cross res lines 🤣🤣🤣

[BiggB @bigbindian]

@ryangerritsen Wow must be golden eggs and silver chicken - enjoy Canadians hard earn money

[BiggB @bigbindian]

@Chicago_Goofies Any asian looking guy is Indian if something is bad - 🤣🤣🤣

[ollama @ollama]

You can use OpenCode Desktop with Ollama!

Try it with the top open models!

[Dhanian 🗯️ @e_opore]

API Design Mindmap

Grab the API Design Ebook: https://t.co/khMNSzhLw0

[Brij Pandey @LearnWithBrij]

AGENTIC AI
│
├── 01. AI Foundations
│ ├── LLMs
│ ├── Tokens
│ ├── Context Window
│ ├── Embeddings
│ ├── Prompt Engineering
│ └── Function Calling
│
├── 02. RAG Systems
│ ├── Chunking
│ ├── Vector Databases
│ ├── Embedding Models
│ ├── Retrieval
│ ├── Re-ranking
│ └── Hybrid Search
│
├── 03. Agent Fundamentals
│ ├── Planning
│ ├── Reasoning
│ ├── Tool Calling
│ ├── Memory
│ ├── Reflection
│ └── Self-Correction
│
├── 04. MCP (Model Context Protocol)
│ ├── MCP Servers
│ ├── MCP Clients
│ ├── Resources
│ ├── Prompts
│ ├── Tools
│ └── Transport Layer
│
├── 05. AI Memory
│ ├── Short-Term Memory
│ ├── Long-Term Memory
│ ├── Semantic Memory
│ ├── Episodic Memory
│ ├── Memory Retrieval
│ └── Memory Optimization
│
├── 06. Agent Frameworks
│ ├── LangGraph
│ ├── OpenAI Agents SDK
│ ├── CrewAI
│ ├── AutoGen
│ ├── Mastra
│ └── LlamaIndex
│
├── 07. Tool Integration
│ ├── APIs
│ ├── Databases
│ ├── Browser Automation
│ ├── Code Execution
│ ├── Search
│ └── External Services
│
├── 08. Multi-Agent Systems
│ ├── Planner Agent
│ ├── Research Agent
│ ├── Coding Agent
│ ├── Reviewer Agent
│ ├── Coordinator
│ └── Human-in-the-Loop
│
├── 09. Deployment
│ ├── FastAPI
│ ├── Docker
│ ├── Kubernetes
│ ├── Serverless
│ ├── Monitoring
│ └── Scaling
│
├── 10. Production AI
│ ├── Guardrails
│ ├── Evaluations
│ ├── Observability
│ ├── Caching
│ ├── Cost Optimization
│ └── Security
│
└── 11. Future of AI
├── Voice Agents
├── Computer Use
├── AI Employees
├── Autonomous Businesses
└── Physical AI

[Movez @0xMovez]

Anthropic just released a 4-hour course on building agentic systems from scratch:

• 00:00 - Building, running & monitoring agents
• 57:43 - Evals for Claude AI agents
• 01:58:12 - MCP, /hooks, Claude.md
• 02:57:28 - Shipping long-running agentic loops
• 03:44:46 - Building skills for Claude agents

This 4-hour series of webinars will replace 10 paid courses on agentic engineering

Watch it today, then learn how to build self-learning trading agents with Horizon in the post below

[sunick @Serantych]

Anthropic just released how they build agents on Opus 4.8 with Karpathy's loop method

same task, same harness - reliability jumped from 30% to 100%

→ drop the effort a level - 4.8 defaults high, the cost curve moved down.same output, less spend

→ cut your "summarize" prompt - it narrates its own progress now

→ change the rules mid-task with a system message - your cache holds, no 10x penalty

→ send a second agent to attack the first one's answer - keep only what survives

→ edit memory in one script, not twenty tool calls - and git-track it

bookmark this ↓

[Ruben Hassid @rubenhassid]

I made a 16-page PDF to get you Claude-certified.

The certificates are official by Anthropic & free...

And the playbook is free too, at https://t.co/psB7XxAv8w. Here's what's inside:

The Claude Certification Playbook.

→ 3 official certificates & the order to take them in.
→ Step from creating an account to downloading.
→ The fake detector (yes, people sell fake ones).
→ The LinkedIn format to showcase the certificates.
→ The copy-paste announcement post on LinkedIn.
→ What you can honestly say about it in interviews.

The certificates take 6 hours.
Getting the playbook takes 2 minutes:

1. Go to https://t.co/psB7XxAv8w. Subscribe for free.
2. Open the welcome email in your inbox.
3. Tap the Notion library link inside.
4. Download "The Claude Certification Playbook."
5. Start with page 4 (the fake detector).

Know someone job hunting? Send them this post. It's the favor.

[Codez @0xCodez]

Anthropic team just shared a “3-layer system” on how they use Claude internally at Sequoia Podcast:

step 1 → knowledge layer: skills, memory, MCP, context grounding.

give Claude the right information before it starts working

step 2 → execution layer: harness + managed infra + sandboxes.

let Claude actually do the work - edit files, call tools, run tasks

step 3 → coordination layer: strategies, token jobs, meta-harnesses.

one token advises, another executes, another grades the output

most people never get past step 1. Anthropic is already building at step 3.

"we have 5 token jobs internally. give this to the ecosystem - it becomes 100,000 combinations."

watch, then read the guide below ↓

[rari @0xwhrrari]

Anthropic dropped a free 59-minute Claude Code course

From autocomplete to real agents:

00:00 - From autocomplete to agents
04:50 - How the agentic loop works
14:07 - CLAUDE.md as project memory
26:53 - Why Plan Mode comes first
33:31 - Live task from brief to commit
54:46 - Skills vs CLAUDE.md

Most people still use Claude Code like a smarter autocomplete

This shows how Anthropic uses it to plan, call tools, test, and ship real work

Worth more than 99% of paid Claude Code tutorials

Bookmark and watch it later

[Annatar.md @AnnatarXBT]

TYPES OF LOOPS - FOUR WAYS TO STRUCTURE AGENTIC WORK WITH CLAUDE

loop engineering gets talked about like one thing -> it's really four structures, and picking the right one is the whole skill

every loop answers two questions: what starts a run, and what decides it's done. by hand you answer both yourself

each type moves more of that into the system

1) turn-based
> starts on your prompt
> Claude gathers context, acts, checks itself, replies - then you write the next one
best for: requirements still forming

2) goal-based
> starts with /goal + a limit ("Lighthouse 90, stop after 5 tries")
> when Claude tries to stop, an evaluator checks the goal and sends it back on a no
best for: measurable outcomes where the path isn't worth watching

3) time-based
> starts on a clock ("/loop every 5 min: check the PR, fix CI")
> /loop runs local, /schedule moves it to the cloud
best for: recurring work you can define ahead of time

4) proactive
> starts on an event, no human present
> /schedule watches a channel, spawns triage, fix, and a reviewer that judges the work before it closes
best for: standing duties where you can't predict what comes in

each type hands off one more job than the last. the more you hand off, the less you babysit

full breakdown on loop engineering in the article below 👇

[Zach Lloyd @zachlloydtweets]

https://t.co/GtnfNHmPOq