The cost of building software has collapsed. What used to require a venture-backed team and a multi-million dollar seed round now requires one operator, a clear thesis, and a well-designed system. The bottleneck is no longer the code—it is the judgment required to architect the system and the discipline to operate it.
I am currently building Inky, an AI storytelling app. It is a core property within the Total Ventures portfolio. This is not a project meant for a quick exit; it is a digital product built to keep. Inky represents a shift in how we approach software: moving away from human-heavy development toward agentic engineering.
The Shift in Software Production
When building an AI story app today, you are not just writing functions. You are designing an environment where agents can execute work. In the old model, a developer wrote every logic gate. In the new model, I architect the operating system, and the AI workforce executes the production.
This shift changes the stakes. If you bolt AI onto an old organizational shape, you will be out-shipped by smaller teams with better systems. At Total Ventures, the goal is to maintain a portfolio of real products with zero employees. The machine is the moat.
Moving Beyond the Wrapper
Most people think building an AI story app is about finding the right prompt. I learned the hard way that a single prompt is a fragile foundation. If your product is just a thin layer over a large language model, you do not own a business—you own a feature that will eventually be absorbed by the platform providers.
To build for permanent equity, you must move beyond the wrapper. You need an orchestration layer that manages state, handles non-deterministic outputs, and ensures a consistent user experience.
The Orchestration Layer
Inky relies on a multi-stage agentic pipeline. Instead of asking a model to "write a story," the system breaks the process into discrete, manageable tasks:
- World Building: An agent defines the constraints, tone, and setting.
- Character Architecture: A separate agent develops character arcs and motivations.
- Narrative Synthesis: The engine weaves these elements into a coherent structure.
- Validation: A final agent checks for logical inconsistencies or tone shifts.
This is agentic engineering in practice. By decoupling these steps, I can swap out models or refine specific parts of the process without breaking the entire application. It allows for a level of precision that a single prompt can never achieve.
Agentic Engineering: The New Workforce
Working in public means being honest about how the work gets done. I do not spend my days writing every line of CSS. I spend my days directing the agents that do.
My edge is pattern recognition across domains. Music has grammar, code has syntax, and storytelling has a structural feedback loop. When building an AI story app, I apply these same principles. I look for the underlying system.
In the Total Ventures monorepo, the agents are the workforce. They handle the research, the initial drafting, and the monitoring of the deployment. This allows me to work on the business, not in it. I allocate capital and attention; the machine executes the technical requirements.
Learned the Hard Way: The Reality of Non-Deterministic Systems
Building with AI is not like building traditional CRUD apps. In a traditional app, if you input A, you get B. In an AI-native product, if you input A, you might get B, C, or a hallucination.
I learned the hard way that you cannot rely on the model to maintain state over long sessions. For Inky, this meant building a robust managed data layer that tracks every narrative decision. The agents do not "remember" the story; they query the database to understand the current state of the world.
Latency is another enemy. Users will not wait thirty seconds for a story to generate. Solving this required moving from a synchronous request-response model to an asynchronous, event-driven architecture. The user sees the story unfold in real-time as the agents complete their tasks. It is more complex to build, but it is the only way to create a product that people actually use.
Built to Keep: The Permanent Equity Framework
Total Ventures is a permanent-equity company. We build, keep, and operate. This philosophy dictates every technical decision I make while building an AI story app.
I am not building toward an acquisition. I am building for durable free cash flow. This means prioritizing craft and stability over rapid, unmanaged scale. It means choosing a tech stack that is maintainable for the long haul—a relational database for structured data, a reliable orchestration layer for the agents, and a clean frontend framework for the user interface.
When you build to keep, you care about the margins. You care about the cost per generation and the lifetime value of a user. You don't chase trends; you build systems that compound.
Shipping Today
There is no substitute for shipping. You can theorize about agentic engineering for months, but the real lessons are found in the logs of a production environment.
Inky is a demonstration of what is possible when one person uses an AI workforce to build a high-quality digital product. It is not a side project. It is a cash-flowing asset that proves the Total Ventures model works.
If you are an operator looking to redesign how you work around this shift, the first step is to stop thinking like a developer and start thinking like an owner. Build the system, not just the code.
Always forge ahead.
Justin Tsugranes Founder, Total Ventures
Next Step: If you are ready to build your own AI-native products, the free Studio Launch Checklist covers the exact framework I use to move from concept to shipped artifact.
Download the Checklist — totalventures.io/resources/launch-checklist
Studio Notes
How I’m building the studio.
The operator’s log — systems, decisions, and what’s working.
Written by
Founder, Total Ventures
Solo-founder building a multi-brand product studio with AI agents. Writing about building, operating, and shipping.
