Techreviewer

Hey IH community 👋

My team at Techreviewer just wrapped up a survey of software development teams about their AI workflows. Since most of us here are building solo or with tiny teams, I thought you'd find the data useful – especially the gap between "AI saves time" and "AI verification takes longer."​

The headline numbers

• 84% use ChatGPT (Claude at 64%, Copilot 56%, Cursor 53%). If you're not using AI yet, you're in the 2% minority.​

• 85% report higher productivity, and 78% are satisfied with their tools. On paper, AI works.​

• But here's the twist: 64% say verifying AI code takes longer than writing from scratch. Only 36% actually save time end-to-end.​

Where AI actually delivers ROI

The survey broke down task-by-task efficiency (time saved ÷ usage frequency):​

Biggest wins:

• Code generation/completion (0.9+ efficiency score)​

• Documentation writing (0.9+ efficiency)​

• Bug fixing/debugging (0.79 efficiency)​

• Writing tests (0.7+ efficiency)​

Poor ROI:

• API integration (0.37 efficiency – used often, saves little time)​

• Database queries (0.58 efficiency)​

• System architecture (0.62 efficiency)​

The trust problem

Only 18% are "very confident" in AI accuracy. Nearly everyone treats AI output as a draft requiring manual review.​

62% find logic errors in AI code (it runs but does the wrong thing), and 47% hit security issues. Syntax errors? Only 31% – AI passes the compiler but fails real-world context.​

What indie hackers should do differently

Based on 64% of respondents being senior devs with 8+ years experience:​

1. Use AI for docs and tests first
These have the highest efficiency scores. If you're time-constrained (we all are), automate the boring stuff that actually saves hours.​

2. Skip AI for DB queries and API work
The data shows poor ROI here. Faster to write it yourself than debug hallucinated endpoints.​

3. Always verify, but budget for it
The 64% who spend extra time on verification aren't wrong. Build review into your workflow; don't assume AI = instant shipping.​

4. Ethics matter more than you think
80% have faced ethical dilemmas (IP concerns, data privacy, bias), and 85% worry about copyrighted training data. Only 2% disclose AI use to clients frequently. If you're building for B2B, expect questions.​

My take

AI won't replace you, but it shifts where you spend time: less on boilerplate, more on verification and context. For solo founders, that's a net win if you stick to high-ROI tasks (docs, tests, code completion) and avoid the traps (architecture, integrations).​

The hype says "10x developer." The data says "2x developer who spends 1.5x time checking work." Still worth it – but manage expectations.

What's your experience? Are you in the 36% who save time, or the 64% who verify longer? Drop your workflow below, curious what's working for other indie hackers.

Full research here if you want the deep dive: https://techreviewer.co/blog/how-ai-reshaping-development-workflows-in-2025