Building AI-First: How We Ship New Features in Days, Not Months

Key Takeaways

• AI-first development lets you ship new features in days, not months.
• Automating repetitive tasks and leveraging AI copilots accelerates every stage of the product cycle.
• Use a conversational command center to eliminate context switching and keep teams focused.
• The right tool stack (see our list below) is critical for rapid iteration.
• Real-world example: We shipped a customer-requested feature in 72 hours using this approach.
• Download our AI-assisted development template to get started.
• SimpleDirect’s WorkOS is built for teams who want to move at AI speed.
• Avoid common pitfalls: over-automation, tool overload, and lack of human review.
• US-based SaaS teams using AI-first methods report up to 40% faster release cycles.

The New Speed Standard for Product Teams

Shipping fast isn’t just a competitive advantage—it’s survival. In 2024, technical founders and product managers are under pressure to deliver new features at breakneck speed. But most teams are still stuck in old cycles: endless meetings, context switching, and slow handoffs.

At SimpleDirect, we’ve built our entire WorkOS around an AI-first development philosophy. The result? We routinely ship new features in days, not months.

In this article, we’ll break down our exact workflow, the tools we use, and a real example of how we delivered a customer-requested feature in just 72 hours. If you want to build faster, smarter, and with less friction, read on.

Why “AI-First” Changes the Game

Traditional product development is slow because it’s manual and fragmented. Teams juggle 5-10 tools, lose time in handoffs, and spend hours on repetitive tasks. AI-first development flips this script:

• Automated code generation: AI copilots write boilerplate, tests, and documentation.
• Conversational interfaces: Teams issue commands and get updates in one place—no more app switching.
• Instant feedback loops: AI-powered analytics surface bugs and user feedback in real time.

Key stat: According to a 2024 Stack Overflow survey, teams using AI copilots report a 40% reduction in development time.

Pro Tip: The biggest win isn’t just speed—it’s focus. By letting AI handle the grunt work, your team can spend more time on high-impact decisions.

The Problem with Old-School Development

Let’s be honest: most teams are still running on processes built for 2014, not 2024. Here’s what that looks like:

• Spec writing: 1-2 days of back-and-forth in Google Docs.
• Prototyping: 2-3 days of manual coding, often starting from scratch.
• Testing: 2 days of writing and running tests, often by hand.
• Deployment: 1 day of manual steps, with risk of human error.
• Feedback: 1 week to collect, analyze, and act on user feedback.

That’s 7-10 days for a simple feature—if everything goes right.

The AI-First Difference

With AI-first, you can:

• Draft specs in minutes with AI assistance.
• Generate code and tests automatically.
• Deploy with a single command.
• Get real-time feedback and analytics.

The result? Features ship in days, not months. Your team stays focused, and your customers get what they want—fast.

Our AI-Driven Development Workflow (Step-by-Step)

Here’s how we ship new features in days, not months. This is our real, battle-tested process at SimpleDirect.

1. Feature Request Intake

• All requests flow into SimpleDirect Chat (our command center).
• AI triages, tags, and summarizes requests for the product team.
• No more lost tickets or endless email threads.

2. Spec Generation

• Product manager drafts a spec in Chat.
• AI assistant auto-generates user stories, acceptance criteria, and edge cases.
• Team reviews and approves in under an hour.

3. Rapid Prototyping

• Engineers use AI code copilots (GitHub Copilot, Cody) to scaffold code.
• AI suggests test cases and documentation as code is written.
• UI/UX mockups generated in Figma with AI plugins.

4. Automated Testing & QA

• AI bots run unit, integration, and regression tests.
• Failures are flagged instantly in Chat, with suggested fixes.
• Test coverage reports generated automatically.

5. Deployment & Feedback

• One-click deploy from Chat.
• AI monitors usage, collects feedback, and suggests improvements.
• Customer support (SimpleDirect Desk) is looped in automatically.

Workflow Table

Total time saved: Up to 80% per feature.

Tools & Templates We Actually Use

Here’s our real stack for AI-first shipping. We’ve tested dozens of tools—these are the ones that actually work for US-based SaaS teams.

Core Tools

• SimpleDirect Chat: Command center for all requests, updates, and deployments.
• GitHub Copilot / Cody: AI code generation and review.
• TestGPT: Automated test writing and execution.
• Linear: Lightweight issue tracking, integrated with Chat.
• Figma + AI plugins: Instant UI mockups and handoff.
• SimpleDirect Desk: AI-powered customer support for instant feedback.

Optional Add-Ons

• Retool: For quick internal dashboards.
• Amplitude: Product analytics, integrated with SimpleDirect.
• Zapier: For connecting legacy tools.

Our AI-Assisted Development Template

We use a simple, repeatable template for every new feature:

1. Feature Name & Description
2. User Stories (auto-generated)
3. Acceptance Criteria (AI-suggested)
4. Edge Cases (AI-suggested)
5. Test Cases (auto-generated)
6. Deployment Checklist
7. Feedback Loop Plan

Pro Tip: Don’t overload your stack. The fewer tools, the less context switching—and the faster you ship.

Real-World Example: Shipping a Feature in 72 Hours

Let’s get specific. Here’s how we shipped a customer-requested feature in just three days.

Scenario

A SaaS customer requested a new “bulk email scheduling” feature on Monday morning.

Day 1: Intake & Spec

• Request logged in SimpleDirect Chat.
• AI summarized and generated a spec.
• Product manager reviewed and approved in 30 minutes.

Day 1 (Afternoon): Prototyping

• Engineer used Copilot to scaffold backend and UI.
• AI generated test cases and documentation.
• Figma plugin created UI mockups in 20 minutes.

Day 2: Testing & QA

• Automated tests ran overnight.
• Bugs flagged and fixed by noon.
• Test coverage report generated and reviewed.

Day 3: Deployment & Feedback

• Feature deployed with one click from Chat.
• Customer notified via SimpleDirect Desk.
• AI monitored usage and collected feedback.

Results

• Total time: 72 hours (Monday morning to Thursday morning)
• Meetings required: 1 (15 minutes)
• Customer satisfaction: 9.8/10 (post-launch survey)
• Cycle time improvement: Down from 14+ days in 2022 to 3.2 days in 2024

Key stat: Our average feature cycle time is now 3.2 days (down from 14+ days in 2022).

Actionable Tips: How to Build AI-First in Your Team

Ready to move faster? Here’s how to get started with AI-first development in your own team.

1. Start with One Workflow

Pick a high-friction process (like bug triage or spec writing) and automate it with AI. Don’t try to “AI-ify” everything at once.

2. Centralize Communication

Use a command center (like SimpleDirect Chat) to keep everyone aligned. No more Slack, email, and Jira all at once.

3. Automate Specs and Tests

Let AI generate user stories, acceptance criteria, and test cases. Review and edit as needed, but don’t start from scratch.

4. Limit Your Tool Stack

Fewer tools = less context switching = faster shipping. Integrate only what you need.

5. Measure Everything

Track cycle time, bug rates, and customer feedback in real time. Use dashboards to spot bottlenecks.

6. Iterate Fast

Ship small, get feedback, and improve—AI makes this loop faster than ever.

Quick Reference Table

Common Pitfalls and How to Avoid Them

AI-first development is powerful, but it’s not magic. Here are the most common mistakes we see—and how to avoid them.

1. Over-Automation

Problem: Automating everything, including tasks that require human judgment.

Solution: Use AI for repetitive, well-defined tasks. Keep humans in the loop for product decisions and edge cases.

2. Tool Overload

Problem: Adding too many tools, which increases context switching.

Solution: Stick to a core stack. Integrate only what’s essential.

3. Lack of Human Review

Problem: Trusting AI-generated code or specs without review.

Solution: Always review AI output. Use AI as an assistant, not a replacement.

4. Ignoring Feedback Loops

Problem: Shipping features without real-time feedback.

Solution: Use AI-powered analytics and customer support to close the loop.

5. Not Training Your Team

Problem: Expecting everyone to “just get” AI tools.

Solution: Run short training sessions. Share best practices and templates.

Conclusion: Start Shipping Faster with SimpleDirect

AI-first isn’t a buzzword—it’s a proven way to build and ship features at startup speed.

By automating the busywork and centralizing your workflow, you can deliver what your customers want in days, not months.

Ready to move faster? Download our AI-assisted development template and try SimpleDirect WorkOS for your next feature sprint. Stop switching between 10 apps—start building in one conversation.