GPT-5 is coming: multimodal LLMs in real software work

After GPT-5 shipped, AGI chatter spiked again. As practitioners, we care about a different question: what real value do these models bring to software development?

Code generation: from Copilot to autonomous coding

First-gen tools like GitHub Copilot proved the value of AI-assisted coding. Code agents go further — understanding requirements, designing architecture, writing and debugging code.

UI design: screenshot to code

Multimodal models turn screenshots into frontend code. Not production-ready, but excellent for design review.

Bug hunting: a new log-analysis paradigm

Drop log screenshots and error output to a model and it locates root causes fast — extremely useful in practice.

Limit: not a replacement for engineers

Models fit repetitive, deterministic coding — unit tests, refactors, API docs. Architecture and technical decisions still belong to engineers.