Clients expect the speed of vibe coders and the quality of a professional software house. Tango Code, a global software house, was shipping quality work in 2-3 month engagements. Most of that time was process overhead: handoffs, review cycles, waiting for fixes.
McKinsey estimated $4.4 trillion in annual productivity potential from generative AI. GitHub reported developers completing tasks 55% faster with Copilot. The numbers were there. What was missing was someone willing to rewire the actual process, test it, validate it, and bring the whole team along.
The transformation happened in one week. I worked with the CEO and CAIO to define the vision, then ran sessions with every designer on the team.
It wasn't clean. The first real friction was decentralized AI: every designer had their own workflow, their own tools, their own prompting habits. Nothing was shared, nothing was consistent. We fixed that by standing up a Team Claude account with Company Skills: shared prompt templates, project context, and coding conventions baked in from day one.
The second friction was the terminal. Designers had never used it. Dropping them straight into Claude Code would have killed momentum. So we built a ramp: Figma Make first to show that code was just another output, then v0 for layout generation, then Claude UI for component work, and finally Claude Code with the full terminal workflow. Each step came paired with dev team sessions where engineers explained what was actually happening under the hood. By the end, designers weren't afraid of the terminal. They owned it.
| Activity | What it solved | Impact |
|---|---|---|
| Daily workshops | Some designers had never touched a terminal. | Full team onboarded to Claude Code within 5 days. |
| Skill library | Inconsistent prompting. Each person reinventing the wheel. | Standardized skill set via CLI. Predictable outputs. |
| Best practices | Fear of breaking things in real codebases. | Clear PR workflow, branch naming, commit guidelines. |
| 1-on-1 pairing | Individual blockers with Git or CSS architecture. | Personalized support. Nobody left behind. |
The first project built entirely under the new process was a brand monitoring platform for AI models. The client needed to track how ChatGPT, Claude, Gemini, and Perplexity mention and recommend brands. Estimated at 2-3 months. Shipped in one. Half the cost. I worked alongside Giovanna Souza, who co-designed the product screens using the same AI-first workflow.
These are live components from the production codebase. Each illustration showcases a specific design decision made possible by the AI-first workflow.
Which AI models to track?
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Speed without reliability is just chaos. Vibe coding produces demos that collapse in production. We were building real software for a paying client. Every shortcut had to be earned through testing, review, and validation.