ZERO to RUNNING Software Factory In 16 Minutes (LIQUID Software)

Stop waiting for the next model. It will not save you. Neither will the next tool or harness. YOU are the bottleneck. 🔥 Every minute you spend prompting back and forth is a minute your agents sit idle waiting on you. The engineers pulling ahead right now are not chasing primitives. They are moving from in the loop to near the loop, where proactive AI agents work around the clock and only stop at decisions that actually need you. 😲 Get Your Tiny Software Factory https://agenticengineer.com/infinite-agentic-engineering?y=GRlcm3wmOqs 🚀 In this video, we take an empty template and turn it into a running software factory inside a real product codebase, live. One skill, one command, three steps: initialize, configure, specialize. We mount a Tiny Software Factory into Hues, a mock prompt-to-image app, then hand our in-loop agent a 150-line plan that configures it into an AI analytics agent that keeps working after you stop watching. 🏭 IndyDevDan here with Tiny Software Factories lesson two, part of Infinite Agentic Engineering. Lesson one built the foundation. Here we stack 14 new features on top of the empty factory: generic agentic tooling that has no purpose until you give it one. Great defaults plus full customization is a massive advantage, and you can redeploy it against any problem you face on repeat. 💧 The big idea: liquid software. With rising intelligence and falling token costs, a new class of software is emerging that takes the shape of the problem you're solving, and keeps changing shape as you learn more. The Tiny Software Factory is liquid software, designed from day one to be customized by you and by the agent living inside it. 🛠️ Key takeaways: In Loop vs Near the Loop: In the loop, you are the bottleneck. Near the loop, proactive agents run 24/7 and surface results only when a decision needs you. Init, Configure, Specialize: Mount the empty factory into any greenfield or brownfield codebase, then pass a detailed plan to the configure skill. Agents building agents. Tool Summaries: A lightweight model summarizes your agent's tool calls into sentences you can read at a glance. You can look away and pray, or you can engineer and measure. Specialized Subagents: One-off agents with their own model tier, system prompt, and tools, plus hard time and spend budgets. Every run is traced: prompt in, synthesis, output. Agentic Access Parity: Every button click and settings change, your agent can do too. One prompt retunes subagent defaults, enables cron pulse, builds a new theme, and rewires the nav bar. Specialization Wins: One super agent that does everything is not how you solve specialized problems on repeat. Specialization is your advantage. Moving near the loop multiplies it. 💡 Whether you run Claude Code, the Pi coding agent, or your own custom harness, the leverage is the same. Stop fixating on the next model and make the meta optimization in how you work. The scale of intelligence operating on your behalf directly drives the impact you can have with agentic engineering. 🌟 After every lesson, ask yourself: what problems can I repeatedly solve with a tiny software factory? Then build the system that builds the system, and get your butt out of the seat. Stay focused and keep building. IndyDevDan #agenticengineering #aiagents #softwarefactory