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A higher AI pass rate can still hide a bad release.
In the fictional worked example inside my AI QA Regression Kit:
• Baseline: 92% case pass rate
• Candidate: 94%
• Three new regressions
• One critical unauthorised tool action
The dashboard stays on HOLD.
That is the point of comparing the same cases before and after a change: you need to know what broke, not only whether the average improved.
The kit includes 50 starter cases, Excel and Google Sheets import files, repeat-run tracking and an editable client report. Run your workflow separately, then record reviewed outcomes.
Solo/consultant licence: $99.
https://contra.com/products/yjiAwm2y-ai-qa-regression-kit-prompt-model-and-workflow-testing
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Connect with clients, get discovered, and run your business 100% commission-free
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Why just browse a portfolio when you can interview it?
I added an AI assistant to my website. Ask about my experience, projects, technical stack, or availability—and get an instant answer based on my actual work.
Try it: AISaaSwithMustafa.com
What would you ask first?
#AI #Groq #SaaS #FullStackDevelopment #WebDevelopment #Angular #ReactJS #NodeJS #AIAssistant
You can now build tools to solve your problems in few yours.
I needed a tool to help me create & plan my content for X/LinkedIn.
It should help me generate ideas and preview my week/month to see how much content I have planned. I built it in few hours, then remembered that Liutauras Liucvaikis shares a lot of valuable knowledge for designers on how to get clients.
I adapted the tool to work around the strategies he shares online.
I don’t plan on making it public as it’s tailored to my needs & personal, but it’s a good reminder that now you can just build things for yourself 😉
Standardize, Automate, Outsource. In that order.
Every workflow I touch gets the same three questions. Is it written down? If not, that's the work: one format, one path, one place it lives. Only then, what kind of automation does it need? Deterministic code where the answer has to be exact (payroll math), AI where the input is messy (an emailed PO full of raw part strings). Whatever is left needs hands or judgment, so it gets outsourced, and it's cheap to outsource because step 1 already defined "done".
The mistake I see most is automating first because a demo looked good. You don't remove the mess, you bake it into code, and an agent will happily invent the steps nobody wrote down.
AI shows up in all three steps, not just the middle one. It drafts the standard from a pile of emails, runs the automation, and writes the brief for the person you hand the rest to.
Which step are most of your workflows actually at? My guess is step 1.
Full write-up with the IMS and OneHub examples: https://contra.com/p/eROlAXrO-sao-standardize-automate-outsource-how-i-decide-what-ships
