“If we did the things we are capable of doing, we would literally astound ourselves.” —Thomas Edison #SundayReading

Now that Agent Skills are trending 🔥! Read up on how they work and when to use 'em!

9/ Read the blog post here: https://t.co/fQrbXtliBK If you found this deep dive helpful, follow me for more on AI systems and LLM internals!

8/ Conclusion The future of coding isn’t just a smarter chatbot—it’s a well-orchestrated team. By treating context as a scarce resource and specializing agents, we can finally tackle problems that were previously too complex for a single prompt. 🚀

7/ The Pro Tip (Cost Management) Multi-agent systems can use 15x more tokens than standard chat. The key is Model Routing: ✅ Haiku for linting and file discovery. ✅ Sonnet for coding and debugging. ✅ Opus for high-level architectural reasoning.

6/ The Ecosystem Explained Don't get lost in the jargon! Here is the Anthropic agentic hierarchy: 🔹 Skills: Portable tools/functions. 🔹 Sub-agents: Isolated workers for parallel tasks. 🔹 Agent Teams: Persistent groups that debate and coordinate architecture.

5/ Customization The real power lies in Custom Sub-Agents. 🛠️ You can define agents with specific "tool restrictions" using Markdown and YAM. For eg.: A "Ruthless Code Reviewer" can search and read files but is strictly forbidden from editing them, ensuring security and control.

4/ Speed Through Parallelization Efficiency isn't just about smarter model; it's about parallel work. ⚡ Instead of linear chain of thought, an Orchestrator spawns multiple sub-agents to research diff tasks simultaneously. This reduces completion time for complex queries by 90%.

3/ The Architecture - the Orchestrator-Worker pattern. 🏗️ The "Lead" agent (typically Claude 4.6 Opus) acts as the strategist, while specialized "Worker" sub-agents (Sonnet or Haiku) execute specific tasks. It’s like having a team of jr engineers who disappear once job is done.

2/ The Problem Why do we need sub-agents? Two words: Context Rot. 📉 In traditional workflows, every debug log and error message clutters your main context window, degrading model performance. Sub-agents solve this by encapsulating "grunt work" in isolated contexts.

1/ The era of the "do-it-all" chatbot is ending. 🤖 Anthropic’s Sub-Agents are shifting AI from linear conversations to hierarchical orchestration, unlocking 90% performance gains on complex tasks. Here’s how the Orchestrator-Worker pattern is changing the game. 🧵👇

1/5 🚨 We're nearing the "end of the exponential" in AI development, says Anthropic CEO @DarioAmodei in podcast with @dwarkesh_sp. Within years, we'll have AI systems matching Nobel Prize winners' intellect. What does this mean for us? #AI #AGI #Anthropic

Introducing Nano Banana 2: Our best image generation and editing model yet. 🍌 Pro-level quality, at Flash speed. Rolling out today across @GeminiApp, Search, and our developer and creativity tools.

3/7 🔥 Benchmarks are blowing up! GEA hits 71% on SWE-bench Verified & 88.3% on Polyglot, outpacing state-of-the-art methods. Self-evolution just got a major boost! 🚀 #AIBenchmarks #AIAgents #AI

1/7 🚀 A new paradigm in AI evolution: Group-Evolving Agents (GEA) is shaking up the game! Moving from individualistic to collaborative evolution, GEA boosts performance & efficiency. Let's dive in! #AI #GEA #Agents

Salesforce CEO @benioff mounts a passionate defense of software: "The AI companies love our products. They're some of our largest customers. Anthropic, OpenAI, Google, Amazon." "That's reality. No one has a company running entirely on a LLM, because that's not real."

2/ Every company has access to the same LLMs. The difference is what you do with them. We’re in a unique position because we completely rebuilt our platform around four systems: a system of context (Data 360), a system of work (Customer 360), a system of agency (Agentforce), and

7/7 👉 Follow Jiten for more AI systems, LLM internals, and startup insights! Got AI questions? Drop 'em in the comments! 😊 #AICommunity #AI #Agents

6/7 📚 Want the full scoop? Read Jiten Oswal's deep dive on Medium: https://t.co/Anqd5SjW5d 💡 #AIResearch #GEA #AI

5/7 💻 The future of AI self-improvement? GEA's showing us the way. No more "reinventing the wheel" – it's collective progress, baby! 🚀 #AIFuture #AI #Agents

4/7 🤖 GEA's not just fast, it's efficient & robust! Fixes framework bugs in 1.4 iterations (vs 5). Plus, it's transferable across architectures. Universal improvement? 🤔 #AIEfficiency #AI #Agents