How Clioloop's Agentic Fusion Works: A Technical Deep Dive
Architecture Overview Clioloop's Agentic Fusion is not just "run the same prompt 5 times and pick the best." It's a structured pipeline where differen…
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Clioloop: The Open-Source AI Agent That Thinks in Teams
The Problem Most AI assistants give you one model's answer. If it's wrong, you catch it or you don't. If you use a cheap model, quality drops. If you …
LLM Self-Preference Bias: How Anonymized Peer Review Fixes It
LLM Self-Preference Bias: How Anonymized Peer Review Fixes It The panel had been agreeing with itself for a week before I noticed, and the worst part …
Clioloop — The Open-Source AI Agent with Agentic Fusion
Clioloop — The Open-Source AI Agent with Agentic Fusion We just open-sourced Clioloop , an AI agent with a feature we're calling Agentic Fusion . I wa…
Stop guessing your AI bill: one endpoint for GPT-5.5, Claude & Gemini at a flat per-call price
If you build on top of LLMs, you've probably hit this: you ship a feature, traffic spikes, and the API bill comes back way higher than you expected. P…
Как научить языковую модель читать транзакции: превращаем историю платежей в базу знаний
Меня зовут Дмитрий Валов, я тимлид команды «Инструменты для банка (агенты)» в Sber AI Lab — Центре практического искусственного интеллекта Сбера. Боль…
Two months building an investment bot. What it taught me about LLMs
For two months, I tinkered together a small system that watches my portfolio and sends me, once a month, what it thinks I should do: buy, add, lighten…
Ollama Structured Outputs in Practice — Getting Type-Safe JSON from Local LLMs with Pydantic
json.loads(response) fails at a certain point. You told the model "return JSON only," but it added a ```json markdown code fence around everything. A …
Tokenization under the hood: BPE, WordPiece, SentencePiece, and Unigram compared
Tokenization under the hood: BPE, WordPiece, SentencePiece, and Unigram compared You deploy a chatbot. English queries average 42 tokens each. Then a …
Why multi-agent orchestration is harder than it looks
One AI agent answering a question is useful. Five agents that divide a complex task, pass state to each other, and act on live enterprise systems is a…
Building an AI Visibility Scanner: Hybrid AI Analysis Architecture
Building an AI Visibility Scanner: Hybrid AI Analysis Architecture If you've been following the AI space, you've likely noticed the shift: users are n…
RLAIF Is Eating RLHF — Here Are the Four Places Human Feedback Still Wins
RLAIF is having a moment. Walk through any alignment paper or vendor pitch from the last six months and you'll see the same claim: replace your human …
RLHF vs DPO vs IPO vs KTO: which alignment method should you use
RLHF vs DPO vs IPO vs KTO: which alignment method should you use You have a base model, say Llama 3.2 8B, that can write poetry in any meter and pass …
Your LLM prompt doesn't fit? Pack it by priority (zero dependencies)
Every RAG app and agent eventually hits the same wall: you have more stuff than fits in the model's context window — a system prompt, chat history, re…
Local Inference Powers Browser Sign Language, Open-Source Agent Infra, & AI Engineering Guides
Local Inference Powers Browser Sign Language, Open-Source Agent Infra, & AI Engineering Guides Today's Highlights This week highlights practical a…
AI Claim Verification Pipeline: Stop Hallucinations Before They Reach Customers
AI hallucinations rarely look broken at first glance. They look confident, polished, and ready to ship. That is the dangerous part. A generated report…
I was fine-tuning a language model on Arabic. The loss was perfect. It spoke Chinese.
Repo: github.com/AmmarHassona/trainsafe I was working on fine-tuning an open-source small language model (SLM) on Arabic using DPO. I had the data, th…
Two Pre-Registered Benchmarks for Audit-Native RAG: RAB (EU AI Act 10/12/19) + LRB (Time-Travel Retrieval)
Most RAG demos answer "what's the right chunk?" Very few can answer the two questions a regulator or an auditor will actually ask: Replay this decisio…
Why Prompts Fail in Production (and the 4 Failure Vectors)
Originally published on AI School — free AI & ML courses, no signup. This is lesson 1 of the free course Prompt Patterns That Survive Production .…
The self-improving prompt engine that learns from your codebase history
Via v0.4.0: We Built a CLI That Gets Smarter Every Time You Use It We shipped Via v0.4.0 today another weekend project based on utilizing prompt devel…
AI Agents
AI Agents: Why Simple Chains Beat Complex Orchestration I've built nine AI features into CitizenApp, and I keep seeing the same pattern: developers ge…
Support Threads That Span Days: Agent Memory via Email
Most conversational state management assumes the conversation is happening — a chat session, a websocket, a context window. Email breaks that assumpti…
Google Ships Gemma 4 QAT Checkpoints: Quantization-Aware Training
What: Google shipped quantization-aware-trained (QAT) checkpoints for the Gemma 4 family — open weights that were trained to survive being squeezed do…
When to Move Beyond LiteLLM (And When Not To)
LiteLLM is one of the most useful tools in the modern AI stack, and I want to say that clearly before anything else. If you're building an AI applicat…
Show HN: NeuralBridge - Self-Healing SDK for LLM-Powered AI Agents
Show HN: NeuralBridge — We Built a Self-Healing SDK for LLM-Powered Agents After months of production experience running LLM calls at scale, we realiz…
I Built a Local LLM Rig to Escape API Bills. Then I Paid OpenAI Again.
I run a one-person AI shop. For 2asy.ai's filing pipeline that needs thousands of single-document extractions per cycle, the local rig lost the batch …
Memory Poisoning: The Silent Threat to AI Agents (and How to Defend Against It)
The Problem Nobody's Talking About If you're building AI agents with persistent memory — using Mem0, ChromaDB, Pinecone, or custom vector stores — the…
I stopped trusting “same answers, fewer tokens” after watching an agent lose 1 field name and burn 3 hours
I used to hear the pitch for context compression and think: sure, makes sense. Smaller prompts. Lower latency. Lower cost. Same output quality. Then I…
Создаем автономный анализатор логов на локальных ИИ моделях
У моего клиента есть пара железных серверов, которые используются для хранения и раздачи статических файлов. Все бы ничего, но любое оборудование треб…
Stop explaining yourself to Claude
You're wasting tokens. Not a little -a lot. Here's a prompt I see constantly: "I have a React app and I'm using the useState hook. My component re-ren…