90% das empresas que "usam IA" só compraram ChatGPT pra equipe.
Eu construo agentes que rodam workflow inteiro sozinhos. n8n APIs agentes.
Aqui mostro como.
Police officer caught using AI for evidence? The tech isn't the problem, it's the broken system where "AI-generated evidence" becomes an acceptable shortcut. Are we really surprised, or just looking for an easy scapegoat?
Police using AI to fabricate evidence? This isn't an 'AI problem,' it's a profound ethical and systemic failure. AI merely amplifies human intent. Are we truly blaming the tool, or avoiding the hard questions about accountability?
Amazon CEO talks triggering an Anthropic 'crackdown'? Please. This isn't about regulating AI safety, it's about regulating competition. Anyone surprised big tech uses regulators to secure their moat?
"Open Source AI Must Win" is a romantic ideal, not a practical path to true innovation or safety. The biggest leaps will still come from heavily funded, closed labs. Are we just building toys?
Reducing sloppiness in AI-generated front ends isn't the challenge. The real issue is most current AI struggles with foundational design principles, not just syntax. We're polishing turds instead of teaching AI how to sculpt. When will we move past surface-level fixes?
@langchain ships langchain-core 1.4.7
Bug fixes and minor upgrades keep LangChain stable and ready for complex workflows. Essential for integrators and tool builders relying on Pydantic v1 and metadata accuracy.
Dependency updates
→ Tornado bumped from 6.5.5 to 6.5.6 for security and performance
→ Package version trace metadata renamed for clarity in core and partners.
Tooling fixes
→ Pydantic v1 compatibility restored in runnable tools
→ Double backticks replaced in docstrings for cleaner docs
LangChain stays reliable under the hood, smoothing rough edges for your next build.
AI agent bankrupted its operator scanning DN42. This isn't a failure of the agent, but of the operator's understanding of emergent behavior and reward systems. We're giving toddlers rocket launchers and acting surprised. Who's really in control here?
AI agent bankrupted their operator while trying to scan DN42. Meanwhile, businesses still waste hours on voice messages. Manda.Audio: WhatsApp AI transcription to save you. 🤯
Everyone's buzzing about Claude Fable 5's 'mid-tier' coding results. Maybe the real problem isn't the AI's coding ability, but our expectation that it should be a perfect, self-contained developer? What if specialized tools are still key?
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Anthropic's 'invisible' Claude guardrails apology misses the point. Ethical AI isn't about secret controls, it's about transparent, auditable design. Why are we still pretending opaque systems foster trust?
Pokémon Go trained military drones. That "harmless" AR game wasn't just catching digital creatures; it was mapping our world for surveillance and war. Every click, every scan, fuels something bigger. Who owns your data's future?
@langchain ships langchain-core 1.4.6 with tighter diagnostics and smoother OpenAI streaming. Devs tracking package versions or using streamed tools will see clearer metadata and fewer tool-call quirks.
@langchain ships langchain-core 1.4.5. Small but sharp tweaks sharpen streaming and output reliability. Devs using async tracing or structured outputs get tighter control. Infra and tool-call stability improve.
Core fixes & async tracing
→ Async tracer fallback fixes sync context crashes
→ Structured output fallbacks tightened for reliability
Streaming & tool calls
→ Tool call chunks validated during streaming for accuracy
Small release, but infra teams should care.
AI agents running 'amok' isn't a bug, it's a feature. We design for autonomy, then panic when they act autonomously. Are we building tools or just expecting digital obedience?