Before: Hire developers ($10K+), wait weeks, hope it works, pay separately for hosting, database, auth, etc. Now: Describe your idea, watch it build, deploy instantly, everything included – a ready-to-go app in less than 10 minutes
AGENTS
-
Using Mocha AI to build a full-stack application
By
–
Within just a few minutes, Mocha has built an entire application for me.
— God of Prompt (@godofprompt) 24 juillet 2025
Not only that, the app includes:
✅ Database
✅ Backend
✅ Domain and hosting
0 manual configuration needed. How cool is that? pic.twitter.com/u65Jej0PDMWithin just a few minutes, Mocha has built an entire application for me. Not only that, the app includes: Database
Backend
Domain and hosting 0 manual configuration needed. How cool is that? -
Using AI agents to build custom business management applications
By
–
Someone told Mocha, "I'm a restaurant owner and I want to build an app that tracks all my expenses, vendors, daily profit and loss, and growth projections."
— God of Prompt (@godofprompt) 24 juillet 2025
I simply entered this prompt and let Mocha work its magic: pic.twitter.com/AozGIYpWHpSomeone told Mocha, "I'm a restaurant owner and I want to build an app that tracks all my expenses, vendors, daily profit and loss, and growth projections." I simply entered this prompt and let Mocha work its magic:
-
From iOS Development to LLM Personality Design: Tech Evolution
By
–
Working in tech then: how to build good ios apps on 3G
Working in tech now: how to give LLMs personalities -
Manus AI: Context Engineering Over Model Development Strategy
By
–
Manus AI Manus AI chose to focus on context engineering rather than developing models. If you were to start an agentic company today, which would you invest in?
-
Managed MCP Servers: Secure LLM Agent Tools with Governance
By
–
Equipping LLM agents with tools shouldn’t mean losing governance or security. Model Context Protocol (MCP) has taken off in recent months, and we’re excited to introduce managed MCP servers with Mosaic AI and Unity Catalog integration. Now your your AI models can securely
-
Dynamic Few Shot Prompting to Prevent Agent Overfitting
By
–
3. Dynamic few shot prompting They cautioned against using traditional few shot prompting for agents. Seeing the same few examples repeatedly will cause the agent to overfit to these examples. Ex: if you ask the agent to process a batch of 20 resumes, and one example in the prompt visits the job description, the agent might visit the same job description 20 times for these 20 resumes. Their solution is to introduce small structured variations each time an example is used: different phrasing, minor noise in formatting, etc. [Translated from EN to English]
-
Tool Use in Agents: Managing Complexity and Forcing Tool Selection
By
–
2. Tool use Given how easy it is to add new tools (e.g., with MCP servers), the number of tools a user adds to an agent can explode. Too many tools make it easier for the agent to choose the wrong action, making them dumber. They caution against removing tools mid-iteration. Instead, you can force an agent to choose certain tools with response prefilling. Ex: starting your response with <|im_start|>assistant<tool_call>{"name": “browser_ forces the agent to choose a browser. Name your tools so that related tools have the same prefix. Eg: browser tools should start with `browser_`, and command line tools should start with `shell_`
-
Composite: A browser-native AI agent with clear utility
By
–
Composite might be the first browser-native agent that doesn’t feel like a gimmick. Just clear utility, fast execution, and zero fluff. Big fan of the no-cloud approach.