A clerk seen from behind, the back of the head showing, sits at a counting desk weighing small bundles of finished work on a brass scale, while three small robots queue with more bundles and an open account book lies beside a gate where a second figure, also seen from behind, holds the latch, the whole scene drawn with wide empty margins on every side.

Agoda Engineering & Design

Key Takeaways from Agoda’s AI Developer Report 2026

Agoda Engineering · 29 September 2026

Company story · agents · roles · Human approval

Takeaway

Agoda, the online travel company, surveyed developers in Southeast Asia and India: 53 percent use AI agents widely, and 79 percent require a person to approve production deployments.

Summary

Agoda, the online travel booking company, surveys software developers and engineering leaders in India and six Southeast Asian countries each year. Its second report finds that 53 percent have AI agents in production or broad use. Only 38 percent call their code ready for an agent that works fully on its own, and the post does not say how many people answered.

Key points

Developers named cost as the main barrier to wider use of agents. The report finds that most of the cost lies in designing, reviewing and checking the agents' work, not in the AI model itself.
Developers grant agents freedom by risk: 43 percent let agents handle documentation alone, while 79 percent require a person to approve a production deployment.
When an agent causes a problem, 42 percent hold the individual developer responsible and 2 percent blame the AI vendor.
Of junior developers, 49 percent expect agents to make their jobs less secure, against 17 percent of chief technology officers and vice presidents of engineering.

Implication

The report advises engineering teams to measure what agents cost per piece of finished, checked work, instead of counting tokens and licences. The survey is Agoda's own, the post does not give its sample size, and it also promotes Agoda's own tools for code review and coding agents.

Suggested actions

Engineering

Report AI agent spending by team per piece of finished, reviewed work, so the cost of reviewing agent output counts, not only the AI model's bill.

Engineering

Set an AI agent's freedom by the risk of the task: let it work alone on documentation, and require a person's approval before any production deployment.

Derived by Working Surface from the article. Source line: Measure cost per unit of finished, verified work, make usage visible by feature or team, and choose the model as a configuration decision from the start.

Source issue

29 September 2026: when AI tools do the making, a team has to keep some of the old steps on purpose.