Whether we’re building a logistics platform with on-device vision models or a SaaS dashboard with microservices and LLMs, our dev flow is powered by real tools that make our teams faster, cleaner, and more reliable.
Here’s what our AI-enabled development flow actually looks like, with the tools and examples we use across live projects 👇
🧩 1. Breaking Down Specs with ChatGPT
We start many projects with vague, high-level feature requests.
Instead of manually translating that into tickets, we feed context into ChatGPT:
Prompt:
"We're building a driver app. The user should be able to upload a photo of a package and log a delivery issue. Create detailed user stories, acceptance criteria, and edge cases."
✅ Output:
- 4 clean user stories
- Acceptance criteria for happy + unhappy paths
- Edge cases (e.g. photo too blurry, GPS mismatch)
We drop that straight into Jira or Linear. It turns planning from a 2-hour sync into a 10-minute async task.
💻 2. Shipping Code with GitHub Copilot
Copilot is always on in our editors. But we don’t just let it auto-complete—we prompt it intentionally.
In backend code, we use it for:
- Express.js route scaffolding
- Mongoose model creation
- Writing unit test stubs with Jest or Vitest
For repetitive tasks like validations, data formatting, or JSON transforms—it’s 5x faster.
🧠 3. Using Cursor to Refactor + Understand Legacy Code
One of our logistics clients had a legacy codebase with poor documentation.
Using Cursor, we could highlight entire files and ask:
“What does this component do?”
“Extract this logic into a separate service”
“Rewrite using React hooks”
“Find all places where this function is called”
This saved us hours navigating unfamiliar code, especially during onboarding.
🧪 4. Generating QA Test Scenarios with ChatGPT
Our QA engineers use ChatGPT to go from specs to test cases instantly.
Example prompt:
"Create test cases for a package delivery form. Fields: recipient name, photo, notes, GPS, timestamp. Include edge cases and negative tests."
🔍 Output:
- Valid/invalid inputs
- Missing GPS
- Upload fails
- Signature not detected
We pair this with Playwright or Cypress to automate coverage.
🔁 5. PR Reviews + Code Insights with Agents
On several projects, we’ve built internal agents using LangChain that:
- Review PRs for risky logic
- Summarize daily PR activity for the PM
- Flag inconsistencies (e.g., missing tests, changes to auth logic)
We also use GitHub bots to auto-summarize commits using OpenAI models—saving tech leads valuable time.
🧾 6. Auto-Generating Documentation
Nobody likes writing docs—but AI makes it easy.
Use cases:
- Use ChatGPT to explain complex modules in human-readable language
- Generate README.md files for new microservices
- Auto-document REST or GraphQL endpoints based on handler functions
Example prompt:
“Explain this Node.js Express route as if to a junior dev.”
→ Outputs method, params, edge cases, and error handling
⚙️ 7. Ops, DevEx, and Agent Coordination
In larger platforms, we’ve used AutoGen or LangGraph to create:
- Delivery planners (multi-agent logic that optimizes delivery sequences)
- QA & triage agents that analyze bugs and suggest root causes
- Slack bots that summarize deployment results and flag anomalies
For one logistics platform, we deployed a system where:
- The driver app sends a delivery photo
- On-device AI flags it as damaged
- An LLM agent notifies the dispatcher in Slack with suggested next steps
It runs in real time, and it was all orchestrated by our team.
📈 The Impact We See
Every project is different—but the benefits are consistent:
- 🚀 Faster sprint velocity (less time blocked, more time shipping)
- 🧠 Devs spend more time thinking, less time doing grunt work
- 🐛 Better coverage, fewer regressions
- 💰 Lower delivery costs thanks to fewer hours spent on manual steps
💬 Final Thoughts
This isn’t just “using AI”. It’s building a modern development culture—and we’re doing it every day with our clients across the US.
If your team is still stuck in 2022 workflows, we can help bring you into this new reality—with a fully AI-enabled nearshore team that plugs right into your product.
Nearshoring made simple. AI made practical.
📬 Ready to build faster, smarter, and with less overhead? Let’s talk.
