Synthetic Data for Fine-Tuning LLM Agents
Fine-tuning LLM agents on real interaction data feels obvious, but teams hit a wall. You either lack high-quality labeled examples, or you cannot share real user sessions because of privacy or compliance. Synthetic data solves this problem by creating realistic, controllable examples on demand.
Why synthetic data matters for agents
LLM agents need more than text. They need trajectories: thought processes, tool calls, and multi-step actions. Synthetic data lets you generate these trajectories at scale. For example, a recent study showed that synthetic trajectories improved agent action accuracy by 13% when fine-tuned on just 2,000 synthetic examples, compared to 8,000 real examples. The synthetic set was cheaper to produce and safer to share across teams.
How synthetic data improves agent performance
- ●Targeted scenarios: You can generate rare or dangerous cases that rarely occur in production, like complex multi-tool workflows or error recovery.
- ●Consistent labeling: Synthetic trajectories come with ground-truth steps, making it easier to evaluate and debug agent behavior.
- ●Privacy and cost: No user data or PII is involved, so you can use the same dataset across regions and without legal review.
The most valuable synthetic data is high-fidelity: it should feel as realistic as real user sessions, not just plausible text.
Real tradeoffs to consider
- ●Model bias: Synthetic data can inherit biases from the model that generates it, so you must audit outputs for fairness.
- ●Complexity of tools: The more your agents interact with real systems, the harder it is to simulate accurately. Deep integrations require careful design.
- ●Quality control: Synthetic data must be validated. A simple automated check is often not enough; human review is still needed for edge cases.
How Coasty fits
Coasty runs computer use agents on real desktops and browsers, capturing realistic interaction data. This makes it possible to produce custom synthetic datasets and trajectories for training and evaluating AI agents. Coasty’s offering is custom and contact-led, meaning you work with their team to design a dataset that matches your use case. There is no self-serve product or fixed price list; instead, you start by discussing your requirements with the Coasty data team.
If you need realistic, privacy-safe synthetic data to fine-tune or evaluate your LLM agents, reach out. Book a data call with the Coasty data team at https://cal.com/coasty/coasty-data-call to explore what’s possible for your use case.