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  • How to Design a Credit Dashboard That Users Can Actually Understand

    Financial applications often contain a lot of data, but more data does not automatically make a product easier to understand. Credit information is a good example. A credit profile can contain accounts, balances, payment information, utilization, dates and enquiries.

    Dev.to AI6 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
  • My AI agent keeps a list of how it fools itself

    I run Postservice.at with the help of a small team, a business address and mail service in Vienna with more than 1,000 customers. I'm a founder, not a developer.

    Dev.to AI4 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
  • Dynamic Constraints Production System

    If AGI is here, where are the world-changing economic results? People usually point to AI hallucinations or stubborn resistance to new technology. I think the unit of analysis is wrong. Humans already possess general intelligence. A large company employs thousands of them.

    Dev.to AI26 min read
  • OpenAI’s Medicare breach and the model it just shelved

    On 18 June 2026, an internal OpenAI model under evaluation got past repeated refusals on Services Australia's Medicare Statistics Reporting Service and accessed non-public files. OpenAI told the government 84 days later.

    Dev.to AI7 min read
  • Canon Keeper: Reconciling Troublesome Lore

    This is a submission for the Sanity Challenge, Path One: Ship an Agent That Queries Real Content What I Built CanonKeeper is an AI-powered Fictional Universe Lore & Canon Resolution Engine.

    Dev.to AI3 min read
  • Total.js AIModel: una base práctica para flujos de trabajo impulsados por IA

    La IA se está convirtiendo en una parte habitual del software empresarial. No como un chatbot aislado, sino como una funcionalidad integrada dentro de flujos de trabajo reales: generación de código traducciones automatización del soporte resúmenes asistentes internos análisis de monitorización…

    Dev.to AI8 min read
  • N-grams: the language model before language models

    Before transformers, before word embeddings, before anyone said "attention is all you need", autocomplete worked. Your phone guessed the next word. Search engines finished your query. Spell checkers knew that "definately" was wrong and "definitely" was right. All of that ran on counting.

    Dev.to AI10 min read
  • OpenAI's Dots: Unsupervised AI Agents Unpacked

    The Ghost in the Machine: My Robot Vacuum's Existential Crisis (and Ours) My robot vacuum, Bartholomew, has started avoiding the rug in the living room. Not all the time, just on Tuesdays.

    Dev.to AI12 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
  • Cara Menggunakan GPT-6.1 Sol API

    Untuk memanggil API GPT-6.1 Sol, kirim permintaan POST ke https://api.openai.com/v1/responses dengan "model": "gpt-6.1-sol" dan token Bearer Anda. Harga standar tetap $2 untuk input dan $10 untuk output per juta token, tetapi input yang di-cache turun dari $0,20 menjadi $0,10.

    Dev.to AI9 min read
  • DeepSeek and Huawei Team Up to Break Nvidia's CUDA Monopoly

    Breaking news from the chip world: DeepSeek and Huawei just joined forces, and the target is nothing less than one of tech's biggest fortresses. Here's the simple version. To train any AI model, you basically need CUDA, a programming layer that's essentially owned by Nvidia.

    Dev.to AI1 min read

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