First of All, Why (and How!) I’m Writing This
43% of people use Gen AI tools. Daily.
In the workplace, that number rises to 70%.
Stats like these aren’t news to me, because I see it happen IRL.
I work in the tech world, both as a practitioner and as a part of teams that build, test, secure, and deploy software for real users. Over the last few years, AI tools have quietly moved from being ‘nice to try’ experiments to becoming part of our daily workflow.
But I’ll be honest, not all AI tools deliver what they claim. Far from it, most of them are not even good. In the past year or so, I’ve tried more than 50 AI-powered tools for designing, development, testing, security and even cloud operations. Most didn’t live up to the hype. But some definitely did and these are the tools that are now a permanent part of my tech stack.
So below, I am sharing what actually worked and what didn’t. Not based on what their marketing team claims, but based on 1000+ hours of using these AI tools in real world environments.
PS: This list is NOT sponsored. I am not getting paid for listing these tools here, it is all my personal opinion.
1. AI Tools for Web Design
I think of myself as a very creative person. But that creativity is limited to my thoughts and I do have a hard time expressing my creativity. So, in projects where I didn’t have a dedicated designer, AI tools helped me really move fast while iterating in real time. Design is also one of the first areas where I started using AI tools for mockups, landing page designs and layout inspirations. I’ve tried tools like Figma, Uizard, Galileo AI, Framer AI, and Canva AI
My Top 3
- Figma AI: Figma was already part of our workflow, so adding AI felt natural. The AI features helped generate layouts, improve spacing, and speed up repetitive design tasks. It didn’t replace designers, but it removed friction.
- Framer AI: Framer AI stood out for turning prompts into surprisingly clean, responsive web pages. For early-stage ideas or marketing pages, this saved us days of work.
- Galileo AI: Great for UI inspiration. I mostly use it when I know what I want to build but need visual direction.
2. AI Tools for Web Development (Low-Code / No-Code)
Low-code and no-code tools have improved a lot. While they didn’t replace the need to have full-stack developers, they did prove to be extremely useful for internal tools, MVPs, and admin dashboards. I’ve used these tools when speed mattered more than full control.
My Top 3
- Retool: Retool is excellent for building internal tools quickly. With AI-assisted queries and UI generation, non-front-end developers on our team were able to contribute meaningfully.
- Webflow AI: Webflow’s AI features made building production-ready websites faster, especially when combined with CMS content. It’s not fully no-code, but it strikes a good balance.
- Bubble: Bubble is powerful but I’ll be upfront, it has a learning curve. However, once you master it, it can support complex logic and workflows without writing traditional code.
3. AI Tools for QA and Testing
Testing is often under-prioritized because it’s time-consuming. AI tools helped us catch bugs earlier and reduce repetitive manual testing. My main focus when I tried AI-powered QA and testing tools was to see which ones integrated easily into existing workflows.
My Top 3
- QA Wolf: QA Wolf impressed me with how quickly it generated and maintained end-to-end tests. For teams without dedicated QA engineers, this is a strong option.
- Testim: Testim’s AI-powered test stabilization reduced flaky tests significantly. That alone saved us hours of debugging.
- Postman AI: If you already use Postman, the AI features are a solid upgrade. It makes sense to use AI in a tool that you are familiar with and using. Generating test cases and validating APIs became much faster with it.
4. AI Tools for Security
Security is an area where AI can add real value, especially in identifying patterns humans might miss. That said, trust matters a lot here, so I’d recommend not fulling relying on AI security tools, but they are definitely good for getting started and keeping things a little more secure than before.
My Top 3
- Snyk: Snyk integrated well into our CI/CD pipeline and gave actionable feedback on vulnerabilities. It’s not perfect, but it’s reliable.
- GitHub Advanced Security: If your code already lives on GitHub, this is an easy win. Code scanning and secret detection worked well for us.
- DeepCode: Useful for catching issues early during development, especially for junior developers.
Special Mention: ZeroThreat.ai
I haven’t used this one for long, to be honest, but in whatever little exploration that I did, it was really helpful for automated pentesting. For starters, it is free (at least for now!) and then the generated report also stood out. What I liked most was how it prioritized fixes logically, high-impact issues first, not minor ones at the top. That saved time and made remediation more practical.
5. AI Tools for Deployment & Cloud Management
Managing infrastructure can drain a lot of engineering time. At least that’s what we were facing in our workflows. And while we weren’t short on manpower, it certainly made sense for us to try out AI deployment tools for monitoring, optimization, and faster incident response.
My Top 3
- Vercel AI: For frontend-heavy projects, Vercel’s AI-powered insights made deployments smoother and performance issues easier to understand.
- AWS DevOps Guru: This tool helped surface anomalies we might have missed. It’s especially useful for teams already deep into AWS.
- Harness: Harness improved deployment confidence by predicting risks and suggesting rollback points. It wasn’t the easiest tool out there, but the effort involved was worth it.
Final Thoughts
Remember: AI tools won’t magically fix broken processes or replace good engineering judgment. But if you use them thoughtfully, they can remove friction, save time, and help teams focus on higher-impact work.
My biggest takeaway after 1000+ hours of using AI tools is this: the best AI tools are the ones that ‘quietly’ fit into your workflow. You don’t need ‘disruptive tools’. You need tools you can trust without having to re-engineering everything that you already have.
Have you tried AI tools for your workflow? Tell me your favorites in the comments below and let’s make lives easier for everyone! Waiting to see your suggestions in the comments.
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