For many stochastic processes (but certainly not all) you can find such a function $X_t$. It turns out that it will be a finite variation process, called the bracket process, or quadratic variation process.
In this particular case, one can use the markov property in place of Ito's formula:
\begin{align} \Bbb E[ W_t^2 | \mathcal{F}_s]
&= \Bbb E\left[ (W_t-W_s)^2 + \left. 2W_sW_t - W_s^2 \ \right|\ \mathcal{F}_s\right] \\
&= \Bbb E[(W_t-W_s)^2 | \mathcal{F}_s] + 2W_s\Bbb E[W_t|\mathcal{F}_s] - W^2_s && \text{"taking out what is known"}\\
&= \Bbb E[(W_t-W_s)^2 | \mathcal{F}_s] + 2W^2_s - W_s^2 && W\text{ is a martingale}\\
&= \Bbb E[(W_t-W_s)^2] + W_s^2 &&\text{by independence from the past} \\
&= \Bbb EX_{t-s}^2 + W_s^2 && (\star)\\
&= (t-s) + W_s^2 &&(t>s)\end{align}
where in the line marked $(\star)$, $X_{t-s}$ is a Brownian Motion restarted at time $s$. This tells us that $W_t^2 - t$ is a martingale.