Although feedback cannot increase the channel capacity of memoryless channels, it can enhance the error rate performance and/or shorten the codeword length for the target performance. This work is based on an early work by Viterbi in 1965 that utilizes instantaneous feedback for reliable uncoded communications. We build on this work by incorporating convolutional codes as a new variable-symbol-length digital communication scheme using instantaneous feedback. In the proposed system, called Opportunistic Symbol Length Adaptation (OSLA), the symbol length opportunistically adapts to the noise realization observed within a sub-symbol interval to minimize the packet/codeword error rate. It is shown that the proposed OSLA scheme combined with tail-biting convolutional codes or turbo codes outperforms state-of-the-art non-feedback codes as well as a deep learning-based feedback scheme with up to 1.5 dB gain in noiseless and noisy feedback channels.