Agentic Browser: ~98% fewer tokens than HTML for LLM web agents (Python + MCP)
Open-source agent-first Chromium browser: compact observations, stable refs, MCP server. ~98% fewer tokens than raw HTML.
Open-source agent-first Chromium browser: compact observations, stable refs, MCP server. ~98% fewer tokens than raw HTML.
Chrome ships a real LLM inside the browser now — Gemini Nano, exposed through a handful of built-in...
Part 1 of Retrieval-Augmented Self-Recall — the research track behind Claude Code, Beyond the Prompt....
Learn how to run an AI agent in Python with Ollama, from local installation to FastAPI integration, testing, and production scaling, using code exampl
LLMs measurably reverse correct answers when you push back, and self-critique does not fix it. This is the case for an architectural fix: a challenge-triggered gate that forces one...
Meet DZHC: A Company Run Entirely by AI Agents Dutch Zero-Human Company (DZHC) is exactly...
Your linter is like a spell checker for code. Great at catching typos, terrible at catching...
Ponytail made my agent lazy. Guardsman made it loyal. The difference is everything. ...
I built an AI setup to save money on tokens. It turned into the memory and focus my ADHD brain is...
TL;DR: Ponytail taught my AI agent to write less code. Guardsman taught it to write accountable...
I Automated My Entire Dev Workflow with AI Agents Running 24/7 on a Mac Mini Every morning...
Most "summarize a PDF with AI" tutorials send your document to a cloud API. That's fine — until the...
Most legal AI tools focus on summarising documents or answering queries. While they’re useful, they...
A year ago, the conversation around enterprise AI was simple: build a chatbot, connect an LLM, and...
Let’s be honest: If you’re reading this, you’ve likely used an LLM to generate a boilerplate...
Three days ago I filed the most serious issue my project has ever had — against myself. The tool is...
I built a pytest suite for a small AI agent - not a model that answers once, but one that plans,...
Turn a coding-benchmark audit into a reproducible task-state model, sensitivity analysis, and acceptance rule.
Test full-duplex AI voice across calls, route changes, backgrounding, permissions, and weak networks with a reproducible device matrix.
Use the new OpenAI Agents SDK and FastAPI template as a trigger to test UI, API, authorization, persistence, and cancellation together.
Convert the GPT-Red announcement into a cheap, model-agnostic prompt-injection regression loop with explicit failure evidence.
Day 1 · by Kunal Hore (@KunalOnTech) Quick Jump Why I'm Learning This...
Turn Kimi K3's announced scale, context window, and planned weights release into an evidence-based self-hosting decision.
Tips on Handling Files in LLMs You might want to pull information (especially from doc/text...