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Such an amazing websites, the balance equilibrium of automation and auditing website and SCO work. That’s a very 1% of the work in web development.
#best #webdeveloper
Built SpeedPulse AI — an automated website performance teardown and local client acquisition engine.
Most local businesses lose over 35% of their mobile conversions due to slow load times and missing Google SEO schema. Auditing each client manually took hours, so I automated the...
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Gorgeous 😍
Picture a consultant who takes 8 sales calls a week.
After each one comes the same routine: replay the recording, write notes, update the pipeline sheet, write the follow-up email. Call it 30 minutes a call. That is 4 hours a week, and on busy days the follow-up slips to tomorrow.
I built an n8n workflow that takes that routine away:
→ Fireflies records and transcribes the call
→ As soon as the transcript is ready, AI writes a summary, the open questions, the next step and whether the prospect is ready to go ahead
→ A follow-up email that fits that outcome is saved in Gmail drafts, addressed to the person on the call
→ The call is logged in Google Sheets and the notes land in your inbox
Nothing is sent automatically. You read the draft, change a line if you want, and press send.
For that consultant, 4 hours of admin a week turns into a few minutes of reading, and every prospect hears back the same day.
I tested it on a real recorded client call and have submitted it to the n8n template library as a free template. If you want it set up for your business, send me a message.
My AI assistant runs all day. The expensive model only does the thinking.
Most requests need no AI at all. "Call me in 30 minutes" is handled by plain code. Reminders, schedules and limits are code too.
Short tasks like sorting and scoring go to fast models on a free tier.
The big model only gets planning and long conversations, where it actually has to think.
If it hits a limit, a backup model answers instead of the app going silent.
If your AI app's bill keeps growing, check what really needs the big model.
What does your app send to the most expensive model?
Same pattern holds in outbound tooling. Filtering, dedupe and enrichment lookups are plain code. The model only writes the first line once the row is already verified. Cuts cost and the weird outputs.