What makes Claude Code so damn good

So, what great new products or startups have these amazing coding agents helped create so far (and not on the AI supply side).

Anywhere to check?

It doesn't use RAG is the most obvious way, like taking whole text/code and generating embeddings and performing vector search on it.

the "context" is the short term memory equivalent of LLM.

Long term memory is its training data.

You really should not check that... I saw some dude on reddit saying that you can build your own saas in 20 days and launch and sell it. I checked out some of his; Claude Code can do that in a few hours. So can I without AI as I have a batteries included framework ready that has all the plumbing done. But Claude can do those from scratch in hours. So 1 day with me doing some testing and fixing. That is not a product or a startup: it's a grift. But glory to him for getting it done anyway. Not many people launch and then actually make a few bucks.

I am curious if any good existing solution exist for this tool:

`Tool name: WebFetch Tool description: - Fetches content from a specified URL and processes it using an AI model - Takes a URL and a prompt as input - Fetches the URL content, converts HTML to markdown - Processes the content with the prompt using a small, fast model - Returns the model's response about the content - Use this tool when you need to retrieve and analyze web content`

I came up with this one:

`import asyncio from playwright.async_api import async_playwright from readability import Document from markdownify import markdownify as md

async def web_fetch_robust(url: str, prompt: str) -> str: """ Fetches content from a URL using a headless browser to handle JS-heavy sites, processes it, and returns a summary. """ try: async with async_playwright() as p: # Launch a headless browser (Chromium is a good default) browser = await p.chromium.launch() page = await browser.new_page()

            # --- Avoiding Blocks ---
            # Set a realistic User-Agent to mimic a real browser
            await page.set_extra_http_headers({
                'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36'
            })

            # Navigate to the URL
            await page.goto(url, wait_until='networkidle', timeout=15000) # wait_until='networkidle' is key

            # --- Extracting Content ---
            # Get the fully rendered HTML content
            html_content = await page.content()
            await browser.close()

            # --- Processing for Token Minimization ---
            # 1. Extract main content using Readability.js
            doc = Document(html_content)
            main_content_html = doc.summary()

            # 2. Convert to clean Markdown
            markdown_content = md(main_content_html, strip=['a', 'img']) # Strip links/images to save tokens

            # 3. Use the small, fast model to process the clean content
            # summary = small_model.process(prompt, markdown_content) # Placeholder for your model call

            # For demonstration, we'll just return a message
            summary = f"A summary of the JS-rendered content from {url} would be generated here."

            return summary

    except Exception as e:
        return f"Error fetching or processing URL with headless browser: {e}"

# To run this async function # result = asyncio.run(web_fetch_robust("https://example.com", "Summarize this.")) # print(result) `