"Software engineering does not feel like one of those roles that will disappear."

Eno Reyes, Co-founder and CTO of Factory AI, is leading a new era of software development -  one where AI doesn’t replace engineers but multiplies them. In our conversation for Inside the Silicon Mind, we explored why the “AI will replace engineers” narrative misses the point, how the software development lifecycle (SDLC) is evolving, and what the future of work looks like when humans and AI truly collaborate.

The dominant narrative says AI tools will replace engineers. Reyes disagrees. At Factory, his team builds “droids” - agentic systems that take on repetitive engineering tasks. But rather than eliminating human roles, they’re redefining them.

“The transition we’ll see is from humans doing what we currently think of as coding, toward delegation where a human defines the problem, sets constraints, and directs AI systems to execute.”

In this new paradigm, engineers evolve from coders to architects of delegation. They will design, guide, and validate - not type. The skill shifts from syntax memorization to systems thinking: breaking down big problems into smaller parallelizable tasks that AI can run, and then reviewing, refining, and orchestrating outcomes.

The best engineers, Eno says, are already doing this. They’ve moved from serial work to parallel work, deploying multiple agents at once and spending most of their time on code review, validation, and system-level thinking.

It’s a profound workflow shift - one that multiplies the impact of a single developer tenfold.

Reyes predicts that AI will dissolve the boundaries between disciplines. The next generation of engineers will be generalists - individuals who blend engineering, design, and product management skills to define what to build and how it should behave.

“There’s no longer really a reason to be just an infrastructure engineer or just a PM. You can now work across all aspects of building a product.”

This convergence rewards clear communicators and deep thinkers. The best will be those who can articulate intent precisely to AI systems - an entirely new literacy. “Learn how to use AI” has become the new “learn to code.”

It’s not about prompts; it’s about clarity, structure, and judgment - speaking to machines as if they were competent collaborators who can execute at scale.

So what is Factory AI actually building?

At its core, Factory is an autonomous development platform that unifies fragmented data across an enterprise - the documentation, codebases, tickets, and system context engineers need and gives AI agents the shared memory to act on it.

The result? A true assembly line for software creation.

Reyes shared one striking use case: a company with a massive legacy codebase written in Italian by contractors who were no longer around. Factory’s platform mapped the codebase, created a migration plan, generated Jira tickets with dependencies, and had 20 autonomous code “droids” execute in parallel.

“What would have taken twelve engineers three months, we can now do in a week with two people.”

That’s not automation - that’s amplification. Factory isn’t removing the engineer; it’s industrializing their productivity.

Building AI systems that write and manage code raises an obvious question: How do you keep them safe?

Factory was designed with security as a first principle - not an afterthought. The company holds SOC 2, ISO 27001, and other privacy certifications, but Reyes emphasizes something deeper: defining what it means to build safe autonomy.

“There are no real examples yet of agents at enterprise scale. We’ve had to set the standards - technically, ethically, and operationally.”

Their approach is “secure by design.” Every decision from data integration to model control prioritizes safety, identity management, and responsible autonomy. Reyes’s team even collaborates with OpenAI and Anthropic on safety standards for organizational agents.

It’s an early glimpse into what responsible AI infrastructure will look like across industries.

Like many great companies, Factory’s road to PMF was paved with rewrites. The team rebuilt the product multiple times, even shifting the entire codebase from Python to TypeScript. Along the way, they discovered that early adopters loved the concept but the broader market wasn’t ready yet.

“We honed in too much on a very forward-thinking persona. When we went broader, we realized it was too early. Now, the world’s caught up.”

For Reyes, product-market fit isn’t a single event. It’s a cycle of iteration, validation, and conviction. Every few weeks, founders should either be scrapping ideas or doubling down with certainty.

“If every three or four weeks you haven’t decided something is wrong or gained conviction it’s right - you’re not iterating fast enough.”

That’s the Factory way: relentless refinement until conviction compounds into traction.

Despite operating at the bleeding edge of AI infrastructure, Reyes keeps a level head about the founder journey. He’s candid about the chaos of startup life - balancing investors, customers, and a fast-evolving product and the importance of building personal systems.

“You’ll work a lot. That’s the gig. But if you truly enjoy what you’re building, you’ll find peace in it.”

It’s the same principle his platform is built on - balance between human intuition and machine precision.

The company’s name is no accident. Reyes drew inspiration from the factory method in software design and the original industrial revolution.

“Henry Ford didn’t invent the factory, but he perfected it. We’re doing the same for software.”

Just as assembly lines revolutionized manufacturing, Factory AI is building the infrastructure to industrialize software creation. Not to replace artisans but to give every company, big or small, the ability to scale creative output with precision and speed.

●     Engineers evolve, they don’t vanish. The future of coding is delegation, not elimination.

●     Clarity is the new code. Learn to communicate precisely with AI systems.

●     Iterate relentlessly. PMF is discovered through conviction earned in short cycles.

●     Security is a moat. Safe autonomy will be the next enterprise standard.

●     Culture compounds. Building fast is easy; building responsibly is hard.

Factory’s story is more than a technical milestone - it’s a playbook for what product-market fit looks like in the age of AI. It’s not about replacing humans but elevating them. It’s not about speed alone but safe scalability. And it’s not about code - it’s about clarity, context, and conviction.

The companies that win this next era won’t be the ones shouting “AI replaces humans.” They’ll be the ones quietly building the infrastructure that lets humans do superhuman work.

Until next time,

Firas Sozan
Your Cloud, Data & AI Search & Venture Partner

Find me on Linkedin: https://www.linkedin.com/in/firassozan/
Personal website: https://firassozan.com/
Company website: https://www.harrisonclarke.com/
Venture capital fund: https://harrisonclarkeventures.com/
‘Inside the Silicon Mind’ podcast: https://insidethesiliconmind.com/