I Replaced 10 Hours of Weekly Work With AI. Here's How.

I've been using AI tools extensively in my daily work for over two years now. Not experimentally — as core parts of my workflow. Here's a concrete breakdown of what I've automated and augmented, and the actual time savings.

The Workflows

Code Review Assistance (~3 hours/week saved)

As a technical lead, I review a lot of code. I now use AI to:

First-pass review: AI scans PRs for common issues — security concerns, performance problems, inconsistent patterns. I still do the final review, but I'm starting from a pre-filtered view.
Context gathering: When reviewing code in unfamiliar areas, AI summarises the relevant history and related files in seconds instead of me spending 15 minutes reading through git blame.
Suggested comments: AI drafts review comments that I edit and refine. The drafts are about 80% there — I'm adding nuance, not writing from scratch.

Documentation (~2 hours/week saved)

Nobody loves writing docs. AI makes it tolerable:

API documentation: I describe the endpoint and AI generates the OpenAPI spec and human-readable docs. I verify and adjust.
Architecture Decision Records: I explain the decision verbally (or in rough notes) and AI structures it into a proper ADR.
Onboarding guides: AI analyses the codebase and generates getting-started documentation that I refine with institutional knowledge.

Data Analysis and Reporting (~2 hours/week saved)

Log analysis: Instead of manually grepping through logs, I describe what I'm looking for and AI writes the queries.
Incident summaries: After resolving an issue, AI drafts the post-mortem from the timeline and chat transcripts.
Stakeholder updates: AI transforms technical updates into business-friendly summaries for non-technical stakeholders.

Development (~3 hours/week saved)

Boilerplate generation: Infrastructure code, test scaffolding, configuration files — AI generates the 80% that's mechanical.
Debugging assistance: Describing a bug to AI and having it analyse the relevant code catches issues I might spend an hour tracking down.
Learning acceleration: When working with unfamiliar APIs or libraries, AI provides targeted explanations and working examples faster than documentation.

What I Don't Use AI For

Critical architectural decisions: AI can inform these, but the judgment calls are mine.
Performance-sensitive code: I write this myself and have AI review it, not the other way around.
Anything involving secrets or sensitive data: AI tools see nothing that shouldn't be in a public repo.

The Tools

I won't name specific tools because they change fast, but the categories that matter:

Coding assistant (in-editor AI) — the single biggest time saver
Chat-based AI — for analysis, writing, and brainstorming
Custom scripts — small AI-powered utilities I've built for specific repetitive tasks

The Honest Truth

AI doesn't replace thinking. It replaces the mechanical parts of work so you can spend more time on the parts that require human judgment. The 10 hours I've saved don't just disappear — they go into the higher-value work that actually moves projects forward.

That's the opportunity for every business: not replacing people, but giving them back the hours currently spent on work that doesn't require human intelligence.