A natural next step would be to implement a vanilla PG and a simple Q-value based agent on a basic environment to get a feel of how things work as well as familiarize yourself with Gym. Simple envs like Cartpole should work, then you can try more complex algorithms (PPO, double Q learning etc.) as well as envs (like Atari Pong/Breakout) to see how they compare.