OpenAI pushes agents from engineers' hands to everyday users

From labs to the real world

OpenAI makes no secret of its ambition to create AI agents that will not merely serve as sophisticated tools for programmers. The goal is to get this technology to mass users. As Tim Fernholz points out on TechCrunch, moving from an environment where engineers tweak APIs and handle edge cases to a world where the average user expects a functional result on the first try is extremely demanding both technologically and in terms of product. Agents must stop being fragile scripts and become reliable delegates.

For the average user, the boundaries of trust are changing

While a developer understands that a model can hallucinate and treats the output as a draft for review, the average consumer has neither the time nor the inclination to do so. If an agent is supposed to book a flight or pay a bill, it must not make a mistake. This shift puts immense pressure on the reliability and safety of the models. It will no longer be just about how clever an answer the AI generates, but how safely it can manipulate tools (tool use) in the outside world on behalf of the user.

UI complexity and user expectations will be a drag

The main pitfall will not be the intelligence of the models itself, but user interface design and expectation management. If an agent is given free rein, how do you prevent it from taking an unwanted action? If it needs confirmation for every step, it stops being useful. Finding the right balance between autonomy and control will be the toughest product challenge this year for OpenAI (and all other market players). Current chat interfaces will no longer suffice for this.

Customer wallets will show the true value

Whether everyone will have their own AI agent will not be decided by tech demos. It will be decided by users' willingness to entrust these systems with access to their data and money and pay for it. Success in the developer segment, where ROI is clearly measurable in saved time, may not automatically spill over into the consumer segment, where people are used to digital services being free and where an agent's mistake hurts directly in the wallet.

Lilith's verdict

Building agents for developers is easy because they tolerate mistakes. Building them for everyday users means handing over power of attorney to someone who confuses a bank with a search engine.