A Team

Inspiration

What it does

How we built it

Challenges we ran into

Accomplishments that we're proud of

What we learned

What's next for A Team

Inspiration I was listening to My First Million with Sam Parr and Shaan Puri when they started talking about a “Fiverr for AI.” At that moment, it clicked. I had already spent nine months waiting on a development shop in India to build DEX an AI tool that solves a small piece of the sales cycle. Watching them riff made me realize that instead of tackling a single pain point like DEX, I could create a platform that lets me go to any service-based business and solve whatever workflow headache they have through automations. By the end of that episode, I decided to build A Team and did it in two days.

What I Learned Speed Trumps Perfection Waiting nine months for DEX taught me the pain of slow development. With Bolt, I saw that I could validate ideas almost instantly. That sense of momentum is invaluable when you’re trying to solve problems for real users.

Pain Points Vary Widely Working with general contractors, law firms, and medical facilities revealed a spectrum of administrative drudgery everything from chasing down client info to manually generating estimates or patient intake forms. I learned that once you build a flexible automation engine, you can repurpose it to address countless needs across industries.

User-Centric Design Matters DEX focused on one slice of the sales process. A Team needed to be broad enough that a non-technical office manager at a clinic could set it up, but also powerful enough that a partner at a law firm could customize it. Striking that balance reinforced how critical it is to keep the end user front and center.

How I Built It Listing Universal Problems I mapped out common “pain points” across several verticals:

General Contractors: Converting job details into accurate estimates, tracking change orders, automating follow-up emails.

Law Firms: Organizing case files, auto-filling standard motions, sending court deadline reminders.

Medical Clinics: Streamlining patient intake, verifying insurance details, automating billing codes.

Leveraging Bolt for Rapid Prototyping Bolt’s no-code interface let me drag in API calls, set up AI prompts, and define data flows in hours, not months. I created templates for each vertical and built a small component library things like form inputs, email senders, and PDF generators.

Building the Marketplace Frontend I spun up a lightweight React app connected to Supabase. It displays a directory of vertical-specific automations. Service businesses can browse, preview demos, and click “Install” to deploy a workflow into their account. Bolt handles authentication, API keys, and runs the automation behind the scenes.

Balancing Flexibility vs. Simplicity Early testers wanted deep control over AI prompt variables tone, formatting, output structure. But giving non-technical users too many knobs can be overwhelming. I settled on a tiered configuration: a simple toggle interface for most users, with optional advanced settings for power users.

Managing API Costs Running AI models for every workflow invocation gets expensive fast. I experimented with caching common prompt outputs and batching small requests. I also built a usage dashboard where clients can monitor token consumption and adjust accordingly.

Explaining Value to Non-Technical Stakeholders Selling based on both simple transactional what this agent does (ie. automate communication with your clients) as well as on value (selling them on % of time saved or money).

What’s Next I’m already doing cold outreach on LinkedIn and hopping on calls with prospects to demo A Team. From here, I’ll:

Gather Real Feedback After every call, I’ll note the exact pain points—whether it’s contractors needing quicker estimates or clinics struggling with patient intake. Those insights will guide tweaks to each workflow template.

Build a Simple Onboarding Flow I’ll record a 3–4 minute screencast showing how to install and configure a workflow. That way, new users can get up and running without my hand-holding optimizing for self service.

Built With

• chatgpt
• github
• operator