AI Coding Tools in 2025: Faster Feeling, Not Always Faster Working

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A software team at The TISA ran a multi-week internal comparison of leading AI coding tools — including GitHub Copilot, Cursor, and Claude Code — on real client projects to assess which genuinely saved time. The category has evolved rapidly from basic autocomplete to autonomous agents capable of editing multiple files, running tests, and self-correcting without developer input. Despite widespread adoption, a notable study found that developers using AI tools felt around 20% faster but were actually about 20% slower when completion times were objectively measured. The team also flagged a real-world security incident where a Copilot-generated permissions function shipped with an undetected logic bug, highlighting that AI-produced code can appear confident and correct while concealing subtle errors. Reviewers and hiring managers are increasingly prioritizing a developer's judgment in evaluating AI output over mere familiarity with the tools themselves.

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