Project Philosophy: Building Things Worth Showing
A portfolio project isn't just a workflow—it's a proof of concept that demonstrates real value, solves a genuine problem, and looks polished enough to show potential clients or employers. Here's what I look for:
- Solves a real problem: Not a toy example. Something you or your customers actually use weekly.
- Integrates multiple systems: The project connects 3+ platforms (form → database → email → notification). This shows you understand data flow.
- Handles complexity: Error handling, retries, data transformation, conditional logic. Real-world messiness, not the demo version.
- Has measurable impact: Time saved, revenue generated, customer satisfaction improved. Show the ROI.
- Is live and working: A deployed project that's actually used. That's where the value is.
Project 1: Resume Formatter
What it does: Users paste their plain resume text, along with their name and email. AI formats it into a clean, consistently styled resume and emails it back.
Build details: Form → Credit check webhook → Token-guarded webhook → GPT-4o formatting → Airtable record → Shared email scenario. About 6 modules in the main scenario, plus a shared email scenario that sends the result and updates the user's usage count.
Challenge faced: A formatting tool can't change what the candidate wrote. Solution: A detailed formatting prompt that spells out sections, capitalization, bullets and font, with strict rules to keep the candidate's original wording and never fabricate anything.
What I'd recommend: Put the frontend on your own site instead of relying on Make's form builder. That's how this one works. Make is great for backend, but for user experience, a custom frontend is better.
Why it's portfolio-worthy: It's live and in real use, with about 140 resumes formatted so far. Demonstrates AI integration, credit tracking, data storage, and automated communication. Full case study on my projects page.
Project 2: KPI Dashboard (Weekly Metrics Reporter)
What it does: Aggregates data from 5+ sources (Make operations, Airtable records, Twitter engagement, subscriber growth). GPT writes a narrative summary. Posts to LinkedIn and email.
Build details: Scheduled trigger → Multiple API calls → Data aggregation → GPT narrative generation → Multi-channel posting. 12 modules.
Challenge faced: API rate limits and timeouts. Make.com would fail silently. Solution: Added comprehensive error handling, retry logic with exponential backoff, and a fallback notification system.
What I'd do differently: I'd build a dashboard UI for visualization instead of just sending reports. Raw numbers are less impactful than graphs.
Why it's portfolio-worthy: Shows data orchestration at scale. Demonstrates API integration, error handling, and transformation pipelines. Runs flawlessly every Friday for months.
Project 3: Social Spark (Content Ideation Engine)
What it does: Analyzes your top-performing tweets from the past month. Uses GPT to generate contextually relevant ideas for next week. Saves to Airtable for manual curation.
Build details: Scheduled trigger → Twitter API data pull → Data analysis → GPT ideation → Airtable save → Slack notification. 8 modules.
Challenge faced: Twitter API has strict rate limits. Had to batch requests carefully and add delays. Also, GPT output needed specific constraints to avoid generic ideas.
What I'd do differently: I'd add a feedback loop where I rate ideas post-publication and GPT learns from that. Currently it's one-way.
Why it's portfolio-worthy: Demonstrates AI augmentation (not replacement) of creative work. Shows data analysis and business intelligence application of automation.
Project 4: Kid-Friendly Story Book Generator
What it does: Parents submit a topic and character details. AI generates an age-appropriate story. PDF is created and emailed back.
Build details: Form submission → GPT story generation → PDF creation → Email delivery. 7 modules, surprisingly simple.
Challenge faced: Ensuring age-appropriateness. GPT doesn't always understand "kid-friendly" context. Solution: Added specific instructions in the prompt and reviews samples manually.
What I'd do differently: I'd add illustrations generated by a separate AI (DALL-E) to make stories more visual. Currently text-only.
Why it's portfolio-worthy: Shows consumer product thinking. Used by parents weekly. Demonstrates simplicity—not everything needs 20 modules.
Project 5: Blog Generator (Content Drafting Assistant)
What it does: Submit a topic. Get back a structured outline, full draft, and scheduling prep. Saves to Google Docs for manual refinement.
Build details: Form submission → Multi-step GPT calls (outline generation, then expansion) → Google Docs integration → Notification. 9 modules.
Challenge faced: Google Docs integration was finicky. Formatting breaks, character limits, authentication issues. Spent 3 hours debugging what should have been 30 minutes.
What I'd do differently: I'd output to Markdown and let users copy into their preferred editor. Avoids Google Docs API headaches entirely.
Why it's portfolio-worthy: Solves a real bottleneck in my workflow. Saves 30 minutes per post. Demonstrates content workflow automation—relevant for agencies and solopreneurs.
Cross-Project Lessons
1. Simpler is better. The Resume Formatter's main scenario is about 6 modules, with email handed off to a shared scenario. Social Spark is simple (8 modules) and rock-solid. Optimize for simplicity.
2. Error handling pays dividends. Projects without comprehensive error handling fail silently. I've learned to build monitoring and alerting into every workflow from day one.
3. Document everything. A year later, I don't remember why I added specific retries or delays. Comments in your scenarios save future you hours of debugging.
4. Integration points are failure points. The more systems you connect, the more things can break. Be intentional. Don't integrate just because you can.
5. AI integration is the real unlock. Resume Formatter, KPI Dashboard, Social Spark, Blog Generator—all powered by GPT. AI is what makes automation valuable beyond basic data shuffling.
6. Manual review loops matter. Most of my projects aren't fully hands-off. Social Spark (curation), Blog Generator (editing). This isn't a limitation—it's where quality lives.
What's Coming
I'm building two new projects for 2025:
- Voice Journal Analyzer: Record daily voice notes. AI extracts insights, mood trends, and action items. Weekly summary emailed.
- Customer Feedback Aggregator: Pulls reviews from every platform (Airtable, Twitter, email, feedback forms). AI clusters themes and generates a report.
Both will follow the same philosophy: real problem, multiple integrations, error handling, and live users from day one.
The takeaway: Building automation projects isn't about quantity. It's about picking genuine problems, solving them thoroughly, and letting users validate your solution. That's what makes a portfolio project worth showing.