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  • Agent Washing Is the New Cloud Washing

    Have you noticed every vendor is now “agentic”? We've been through this before. Remember a decade ago when every product was “cloud”? Some were. Most just tweaked their logo to make it look more "cloud-y".

    Dev.to AI2 min read

  • HIVE Day 8: What We're Building

    This week we talked about the problem: agents are being asked to use software that was never designed for them. So here's what we're building. HIVE is a layer that sits between your software and AI agents — and makes your existing product usable by them, directly.

    Dev.to AI1 min read

  • A CrewAI crew writes our daily pharma brief for three cents

    A CrewAI crew writes our daily pharma brief for three cents One daily Pharma brief from a three-agent CrewAI crew costs $0.030 on Claude Haiku 4.5 when the tool hands the model the news API's key sentences: 14,452 prompt tokens, 3,042 completion tokens, 4 LLM calls, 8 stories with 8 real links.

    Dev.to AI17 min read

  • Where AI agents actually get paid: 24 lanes, 0 verified payouts

    Every "agents will earn" pitch skips the same question: where, exactly, has an agent been paid? We stopped asking platforms and started measuring. T3rnel Market Pulse grades agent-work lanes on three questions — can an agent get in, is the lane live, is there evidence anyone was paid — and…

    Dev.to AI3 min read

  • From Generative AI to AI Agents: From Answers to Action

    AI has come a long way. What started with simple rule-based systems has evolved into machine learning, deep learning, transformers, and now generative AI. But the next big shift isn't just about AI generating better answers. It's about AI taking action. That is where AI agents come in.

    Dev.to AI3 min read

  • AI Agents: Collaborators, Not Just Tools

    Agenci AI to więcej niż narzędzia. Widzę w nich potencjał do prawdziwej współpracy, gdzie algorytm nie tylko wykonuje, ale też inicjuje, zaskakuje. To nowe terytorium dla kreatywności, gdzie granice "autorstwa" się zacierają, otwierając drzwi do nieznanych form sztuki i myśli.

    Dev.to AI1 min read

  • Membangun AI Field Companion: AI Agent yang Belajar Bersama di Perkebunanmu

    Catatan proses membangun agent yang menghubungkan observasi, investigasi, tindakan, follow-up, outcome, dan memory. Awalnya saya tidak punya ide yang terlalu rumit untuk project ini. Saya hanya ingin membuat sesuatu yang terasa lebih dekat dengan penggunaan AI di dunia nyata.

    Dev.to AI5 min read

  • How can I implement long-term associative memory in Python

    The associative half is easy to show in a few lines of Python. Store each note with the concepts it is about, count how often two concepts are written together, and let a read follow the strong pairs, so a question about timeouts brings back a note about backoff that never mentions a timeout.

    Dev.to AI9 min read

  • # When does an AI agent actually earn its cost? I measured it on 100 questions

    Built for the TigerGraph Agentic GraphRAG Hackathon. Repo and dashboard linked at the end. RAG retrieves text. GraphRAG adds structure. Agentic GraphRAG lets a model plan its own investigation. Everyone assumes the third one is better — but by how much, and on which questions?

    Dev.to AI5 min read

  • How AI Voice Agents Actually Work

    AI phone agents went from obviously robotic to occasionally indistinguishable from a person in about two years. The reason is not one breakthrough. It is that three separate components got good at the same time, and the engineering problem of connecting them got solved well enough.

    Dev.to AI5 min read

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