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Most Claude Code sessions die in the middle — not because the model is weak, but because the brief was vague and the scope kept growing.
Here's the six-step loop I use so a feature lands as a reviewable PR instead of a sprawling rewrite:
01 BRIEF — write the win condition, in-scope files, and what must not change
02 MAP — explore the call graph; confirm the plan before any edit
03 SLICE — one vertical cut that proves the behavior; defer refactors
04 PROVE — failing test first, then implement until green
05 GUARD — diff the change against the original brief; reject drive-bys
06 LAND — conventional commit + risk note; human still owns merge
If scope drifts, return to MAP. Never keep editing blind.
#Claude #ClaudeCode #AIAutomation
"Write what must not change" is the step most people skip. Without it the agent happily refactors half the repo to fix one button. Do you keep the brief in the repo, or paste it in fresh each session?
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Two concepts. Two different first impressions.
Exploring two visual directions for a finance and AI platform.
Option A | Fundely
Warm gradients, soft curves, and a clean layout. Designed to make finance feel simple, approachable, and easy to trust.
Option B | Proxyma
Bold typography, a structured grid, and a striking 3D visual. Designed to make AI feel confident, modern, and forward-thinking.
Both share the same goal: create a strong first impression through design.
But which direction communicates better?
A or B? I'd love to hear your perspective.
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Shopify Abandoned Cart Recovery Automation 🛒
Ever wondered how many potential orders an online store could miss when customers add products to their cart but leave without completing checkout?
I built an abandoned cart automation workflow using Activepieces, Shopify, Google Gemini, Gmail, and WhatsApp Business.
⚙️ How It Works
🛒 Cart Trigger: Detects an abandoned checkout event from Shopify.
🔀 Conditional Routing: Routes the workflow based on configured conditions.
🤖 AI-Powered Messaging: Gemini generates a personalized reminder message.
💬 WhatsApp Reminder: Sends a cart reminder through WhatsApp Business.
📧 Email Reminder: Sends a follow-up email to encourage the customer to complete checkout.
💡 How It Can Help E-commerce Businesses
Remind customers about products left in their carts.
Reduce repetitive manual follow-up work.
Make customer communication more consistent.
Create an opportunity to recover potentially lost sales.
Tools Used: Activepieces | Shopify | Google Gemini | Gmail | WhatsApp Business
Project Type: Personal Automation Project
I built this workflow to demonstrate how automation can support abandoned cart recovery for Shopify and D2C businesses.
Interested in automating your store's customer follow-ups? Let's connect.
The 30–60 minute delay then 24-hour follow-up is a sensible cadence. The part I would harden next is the stop conditions: once the cart converts or the customer replies, every channel should cancel, and WhatsApp especially needs a clear opt-in trail before the first send....
Your Logistics Team Shouldn't Have to Chase Every Shipment Manually. 🚢
A shipment is delayed. Your customer wants an update. Your operations team is checking carrier portals, copying tracking numbers into spreadsheets, and sending the same status emails repeatedly.
By the time everyone has the right information, the next shipment needs attention.
The problem isn't a lack of effort. It's disconnected logistics operations.
Common challenges:
Shipment updates scattered across multiple carrier systems.
Delayed shipments discovered too late.
Manual customer status emails.
Tracking spreadsheets that quickly become outdated.
Repetitive follow-ups between operations and customer service.
Limited visibility into shipment exceptions.
The solution: An automated logistics operations workflow built with n8n.
I can design an automation that connects carrier tracking APIs, your shipment database, and customer communication channels.
Instead of manually checking every shipment, your team receives structured updates when something actually needs attention.
What the automation handles:
📦 Shipment Tracking — Retrieve updates from supported carrier APIs.
🚨 Exception Detection — Identify delays, customs holds, and missed milestones.
🤖 AI-Assisted Updates — Convert complex tracking events into clear, customer-friendly messages.
📧 Customer Notifications — Send relevant shipment updates automatically.
📊 Operations Visibility — Maintain synchronized shipment records and exception histories.
🔁 Escalation Management — Notify the responsible team when an exception requires action.
The goal: Less repetitive tracking work, faster exception awareness, and more consistent customer communication.
Two ways we can work together:
Option 1: Already have carrier APIs, a TMS, or a defined tracking workflow? Share your requirements, and I'll help design the integration.
Option 2: Not sure which logistics tasks should be automated? We can map your shipment lifecycle and identify the highest-value starting point.
Make your logistics operations easier to manage as shipment volume grows.
Workflow architecture
Scheduled Trigger → Carrier API Request → Normalize Tracking Events → Match Shipment Records → Detect Status Changes → Route Exceptions → AI Summary → Customer Email / Operations Alert → Database Update
Implementation: Authenticate carrier integrations, normalize differing event codes, compare timestamps and event IDs, prevent duplicate alerts, route exceptions by severity, and log delivery failures for retry.
Benefits: Reduced manual tracking, clearer exception ownership, more timely customer updates, and an auditable shipment history.
Result: A centralized shipment monitoring workflow that allows operations teams to focus on resolving exceptions instead of repeatedly checking tracking portals.
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The customs-hold exception is the one I'd find hardest to route, since it needs a different owner than a plain delay. Do you map each exception type to its own team in the escalation step, or is it one shared alert queue?