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You can now add @huggingface to @cursor_ai to find models, datasets, papers, apps,... Vibe coding a website is cool but imagine if the new AI powered code editors would turn everyone into an AI builder able to train AI themselves? How cool would that be?

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𝗧𝗵𝗲 𝗰𝘂𝗿𝗿𝗲𝗻𝘁𝗹𝘆 𝗳𝗮𝘀𝗵𝗶𝗼𝗻𝗮𝗯𝗹𝗲 𝗶𝗱𝗲𝗮 𝘁𝗵𝗮𝘁 𝘄𝗲 𝗵𝗮𝘃𝗲 𝗮𝗹𝗿𝗲𝗮𝗱𝘆 𝗮𝗰𝗵𝗶𝗲𝘃𝗲𝗱 𝗔𝗚𝗜 𝗼𝗿 𝗮𝗿𝗲 𝗮𝗹𝗿𝗲𝗮𝗱𝘆 𝗲𝘅𝘁𝗿𝗲𝗺𝗲𝗹𝘆 𝗰𝗹𝗼𝘀𝗲 𝗶𝘀 𝗮𝗯𝘀𝘂𝗿𝗱. 𝗛𝗲𝗿𝗲 𝗶𝘀 𝘄𝗵𝘆: 1. True AGI [Artificial General Intelligence] ought to be

Which of these patterns matches YOUR current AI challenges? Read the full breakdown with implementation details: https://t.co/1SFkORPJ8o Discover how the AI-First Development Framework makes these patterns work together seamlessly.

According to Gartner, "At least 30% of GenAI projects will be abandoned after proof of concept by 2025." The cause? Poor structure. These 5 patterns transform uncertainty into intentional design. Stop guessing, start building systems that LAST.

Pattern 5: Human-in-the-Loop Orchestration Critical for high-stakes domains. Design explicit checkpoints where: • Low-confidence predictions get human review • Humans approve critical actions • Users correct & guide the system Balancing automation with necessary judgment.

Pattern 4: Stratified AI Systems Layer specialized intelligence on your foundation models: • Foundation: Large models (GPT-4, Claude) • Application: Task-specific logic, prompts & context Leverage general capabilities for specific domains without constant fine-tuning.

Pattern 3: Agentic Feedback Loop AI systems need to learn from their outputs. Design feedback channels where: • Successful prompt/output pairs are stored • User ratings fine-tune the system • AI analyzes its own errors Systems that improve without constant intervention.

Pattern 2: Decoupled Context Pipeline As complexity grows, separate your context handling: • Context ingestion • Processing (embeddings, summaries) • Storage (vector DBs) • Serving to AI models This is where a Living Context Framework truly shines.

Pattern 1: Context-Aware Monolith Perfect for simpler AI projects & MVPs. Instead of complex microservices, integrate context management DIRECTLY within your application. Your AI needs memory to be smart - this pattern gives it a dedicated "brain" without overengineering.

That magical feeling when AI generates code in seconds quickly turns into a nightmare of technical debt. Why? Because we're GUESSING our way through AI development. Here are 5 battle-tested architecture patterns that ACTUALLY prevent AI project failure: 🧵👇 #AIdev #Architecture

Nice catch, but it has the same problem that all these IDES. They are doing with AI the same job, the key is redefine the product development process.

Great product, but. it needs what we are doing to be sick :)

The hidden crisis destroying AI development teams right now: context loss. After 2+ years building AI systems, I've discovered why your AI-generated code becomes unmaintainable technical debt within weeks. A thread on what nobody's telling you 🧵 #AIdev

Is your team building on quicksand? How many hours did you waste last month deciphering AI-generated code that made perfect sense when written? The answers in the comments will reveal if you're ahead of the curve or falling behind. #SoftwareEngineering