After a full year of using AI tools (primarily Claude and ChatGPT) as a daily working tool, here is an honest synthesis of what actually changed — and what did not.
What Changed
Writing speed doubled for drafts. The first draft of any document — report, email, proposal, article — can now be produced in a fraction of the time it previously took, because the resistance to starting (blank page problem) has been almost eliminated. The AI produces a starting structure that I then edit, which is much faster than producing a starting structure myself. Code for personal automation (scripts, data processing, API integrations) that I previously did not have the time or skill to build can now be built in hours — AI handles the implementation details, I handle the specification. Research breadth increased: a question that previously required an hour of searching can be answered in minutes, with better coverage of adjacent angles I might have missed.
What Did Not Change
Decision quality. AI can lay out options, analyse trade-offs, and surface considerations I had not thought of — but the final judgment on complex decisions remains mine and requires my domain knowledge, my values, and my stake in the outcome. Creative originality. The genuinely original ideas — the unexpected connection, the contrarian argument, the insight that surprises — still come from extended human thinking, not from AI prompting. Relationship management and political navigation. Understanding people, reading social dynamics, and managing stakeholders are entirely unaffected by AI tools. These are the things that matter most in most organisations, and they remain human skills.
The Unexpected Effects
My tolerance for low-quality information decreased. Having access to fast, well-organised summaries made me impatient with long-winded sources that take 2,000 words to make a 200-word point. This is a mixed effect — some things worth understanding require the 2,000 words, and impatience for complexity is a cognitive cost worth watching. My trust in AI output is calibrated, not eliminated. I verify facts that matter (specific numbers, dates, technical specifications), accept structural outputs without verification (outlines, formats, draft frameworks), and have learned to catch the characteristic failure modes (confident wrongness about niche topics, hallucinated citations). Prompt quality matters more than most people realise: a thoughtfully constructed prompt produces qualitatively different output from a casual one.
The Net Assessment
AI tools are the most significant productivity lever I have found in 15 years of trying productivity tools. They do not eliminate the hardest parts of knowledge work — judgment, creativity, relationships — but they dramatically reduce the cost of the supporting work that surrounds those hard parts. The people who benefit most are those who are already strong at the core skills (writing, thinking, domain expertise) and use AI to remove the friction around them. AI does not substitute for those skills; it amplifies them.
