Browsing: context

When you analyze documents that span millions of characters, you hit the context window barrier and even the largest context windows fall short. Your model either…

Most AI models today are not designed for sustained, multi-step autonomous execution. Tasks like running hundreds of iterative code modifications, or chaining tool calls across hours…

Training large language models on long sequences has a well-known problem: attention is expensive. The scaled dot-product attention (SDPA) at the core of every transformer scales…

banner(“§12 CLAUDE.md”) sh(“repowise generate-claude-md”) md = TARGET / “CLAUDE.md” if md.exists(): print(md.read_text()[:4000]) banner(“§13 MCP tools via CLI”) base = [ (“get_dead_code”, “repowise dead-code –safe-only”), (“search_codebase”, ‘repowise…

class RoutedAgent: def __init__(self, server: MCPToolServer, router: HybridMCPRouter, model: str): self.server = server self.router = router self.model = model def discover_exposed_tools(self, exposed_tool_names: List[str]) -> List[Dict[str, Any]]:…

The mouse pointer has sat at the center of personal computing for more than half a century. It tracks cursor position. It registers clicks. Beyond that,…

OpenAI just announced that ChatGPT is getting a model upgrade to GPT-5.5. The company says the model will bring better results because of changes to how…

Deep Agents can plan, use tools, manage state, and handle long multi-step tasks. But their real performance depends on context engineering. Poor instructions, messy memory, or…

A deep neural network can be understood as a geometric system, where each layer reshapes the input space to form increasingly complex decision boundaries. For this…

import subprocess, sys subprocess.check_call( [sys.executable, “-m”, “pip”, “install”, “-qU”, “google-genai”], stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL, ) import getpass, json, textwrap, os, time from google import genai from google.genai import…