AI has made writing code significantly cheaper, shifting the engineer's role from a hands-on coder to a higher-level systems designer and architect. The future of engineering will involve managing AI agents, setting system-level guardrails, and focusing on strategic architectural decisions rather than line-by-line implementation.
AI tooling has led to massive productivity gains, with over 50% of Lagora's code being AI-generated. This extends beyond engineering, with Product Managers using AI for rapid prototyping and internal teams building custom AI-powered tools for HR and talent acquisition.
Lagora's CTO admits to consistently underestimating growth, having to scale the engineering team from a projected 20 to 80 and now planning for 270. This has forced a new philosophy of building all systems to handle 100x their current scale and being more aggressive with hiring.
The state-of-the-art in AI models is incredibly fluid, with the 'best' model for a task changing almost bi-weekly. Lagora utilizes around 10 different models, routing tasks based on specific needs. The speaker also notes the importance of a competitive open-source ecosystem to prevent a duopoly among model providers.
A new, critical role is emerging within enterprises: the internal AI systems or enablement team. This function evolves from traditional IT or DevEx to focus on building custom internal tools, setting guardrails for AI agents, and maximizing the effectiveness of AI across the company.
Keep pulling the thread on Jacob Lorentzon.