Rise of the Software Factory | Tereza Tizkova

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Tereza Tizkova<br>San FranciscoSometimes Prague

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Back to blogI gave this talk at AI Engineer World Fair in San Francisco, June 2026.

This is the full day-one livestream; my talk starts at roughly 2:10:00 (jump straight to it).

This is a loose write-up of my talk, not an exact transcript. Tell me what you think, and if you disagree, even better.

Everyone is suddenly talking about software factories, but very few have actually built one and fewer still are willing to show the process. So I want to start with the obvious questions of why this is happening now and what a software factory actually means.

No one knows what software factory means

Everyone is launching software factories. Enterprises share their transformations, LinkedIn is full of thought leadership, and this conference even has a dedicated track for them. What is much harder to find is honest evidence that any of it works in production, or a clear answer about the conditions it needs and how autonomous software really is today. Those are the questions people actually ask when the marketing fades: what a software factory is, whether they should build their own and how, what genuinely works in production, and at what cost.

I define a software factory as the whole cycle of developing software that runs autonomously, which means far more than writing code: it covers the spec, the build, the validation, the deploy, and the learning that comes back afterward. The better mental image is not a chatbot that codes but a factory floor, with parallel lines each handling a different task at a different level of autonomy, where you set policy and priorities at the top and the floor reports back up to you.

That is why the rest of the talk is about three properties that make this floor trustworthy: agnostic, autonomous, and always-improving.

The software factory was not possible two years ago

Karpathy's "Software 2.0" essay in 2017 was the intellectual precursor, and then each layer arrived in turn: Copilot in 2021 for autocomplete, ChatGPT in 2022 for conversation, GPT-4 and bigger context windows in 2023 for real code generation, better reasoning in 2024 for multi-step tasks, and persistent environments with long-running missions in 2025 for genuine autonomy. Every one of those layers had to exist before the factory could.

The length of task an agent can handle doubles roughly every seven months, and for years the AI was a brain with no body, able to plan, retry, and narrate but never actually execute across a full cycle.

The idea itself is not new, since AutoGPT and BabyAGI were already looping and iterating on software back in 2023, they just did not work yet. The models hallucinated, context windows were too small, reasoning was too weak, and there were no good isolated environments where an agent could actually run, so every one of those problems had to be fixed before the factory became real.

The way I like to define it is by what it goes beyond. A software factory is much more than a coding agent, or even a swarm of thousands of coding agents, because generating code is the easy part. Engineers spend most of their time not on writing code but on everything that surrounds it, and that surrounding work is exactly what a factory has to handle. The right mental model is building a real team of people, because with that many agents testing, validating, and iterating, the whole thing turns into chaos unless you design it deliberately.

The firms that rewire their organization around AI, rather than bolting it onto their existing process, pull steadily ahead of the ones that only adopt it, and the gap between leaders and laggards keeps widening because readiness is what compounds over time. A software factory is something you build and own, not a consultancy you hire.

Accenture's valuation multiple peaked near 30x in early 2025 and has come down to about 10x. The market is pricing the difference between advising on AI and actually shipping it.

Electrification is the useful analogy here. When factories first got electricity, they bolted a motor onto the old steam-era layout and saw almost no gains, and the real jump only came once they redesigned the whole factory around electricity. AI works the same way, so bolting agents onto today's process just leaves you with the old factory and a new motor, while redesigning the process around them is what actually produces a software factory.

That factory should stay independent instead of locking you into one platform, work with the models and tools you already use, be trusted enough to run genuinely autonomously, and carry context so that it learns with use.

Do not lock yourself into one environment or subscription, because the same agent should be able to run in the cloud, locally, in CI, and in your IDE, and once it can, that portability becomes real leverage and keeps you clear of vendor lock-in.

Resources for this section:

Karpathy,...