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40+ live apps, open data APIs, MCP servers, and 200+ guides - more than anyone wants to click through. Point your AI here and it reads the whole map and does the work: finds the tool, pulls the data, runs the analysis, and hands you the links.

Here for the open-source code? Your agent finds the right repo for you - and can even clone and deploy it.

Prefer to explore on your own? Go right ahead.

Paste this to Claude Code, Codex, or any AI agent:
Go to tigzig.com and read tigzig.com/llms.txt. It is a practitioner toolkit - 40+ analytics apps, open no-auth data APIs, MCP servers, open-source repos (github.com/amararun), and 200+ build guides. Help me [your task]. Surface the exact links; where there is an API or MCP, call it directly; and if I want to self-host, find the repo and help me deploy it.

The Google Machine continues to roll. Will it do to AI what it did to search?

Published: November 18, 2025

Google AI Tools

A month ago, I posted that Google was back in the AI race. Earlier in the year, I wrote about the shift in their LLM quality.

Sanya Ojha's analysis this week confirms it from the strategy side. I'm seeing it from the execution side.

Google is shipping at a rate I haven't seen in years. Around 20% of my workflow now runs on Gemini. In January 2025, that was 0%.

Here's what I am using for my client projects

At the rate they're going - straddling the whole food chain from LLMs to hardware, to builder tools & enterprise integrations - there's a fair chance in a few years they'll do to AI what they did to search.

➜ But one big gap remains: Top tier LLM and AI coding. For high-intelligence work, Claude Sonnet 4.5 is still the leader, followed by OpenAI. Google sits at #3. They've won the workhorse tier - fast, cheap, reliable bulk work. They haven't won the frontier tier yet

Will they get there? Based on the way it is gaining grounds, odds are in favor of Google.

Read Sanya's full analysis

My original post from last month: Google - the old edge is back source: migrated)

Google AI Analysis