👋 Welcome to Tami’s Technical Enablement newsletter. Your weekly guide to scaling AI, software engineering, and tech talent.

In this week’s newsletter, we’ll cover:

Before we dive in, you can help your developers adopt vibe coding and learn prompt engineering more quickly with Tami. Get a demo to learn more.

Have you read the recent Wall Street Journal article "Vibe Coding Has Arrived for Businesses?”

The headline isn’t just trendy, it’s a real transformation happening at enterprise companies. Vibe coding is no longer just for startups. It’s quietly becoming the new standard in how software is created, iterated, and scaled.

This shift isn’t just about AI generating code. It's also about AI augmenting human capabilities. It’s an entirely new approach to software development, where developers can collaborate with models through natural language, or “prompt engineering”.

This is vibe coding. We’re entering an era where success in engineering won’t be defined solely by how well someone can write code. It will be defined by how well they can shape ideas into clear, strategic prompts and how quickly they can iterate based on what the model returns.

Vibe coding unlocks productivity, but only if your teams know how to steer the AI.

Vibe coding shifts from writing code to describing intent, letting AI generate code.

It's iterative: suggestions, responses, improvements, corrections, and adaptations, making it collaborative design rather than autocomplete.

Engineers specify goals like 'build a real-time leaderboard' or 'refactor auth flow.' The AI acts, guided by the engineer.

Expertise isn't obsolete; better understanding improves guidance.

The key is to frame intent clearly and debug outcomes through language, not just keystrokes.

Jason Lemkin has been vibe coding in public on X and sharing his insights:

If you think this is just a developer's curiosity, think again. The WSJ article mentioned a wave of companies embracing vibe coding as part of their development workflows. And this isn't experimental. These are live systems shipping value daily.

Generally, we’re seeing three major forms of adoption:

1. Paired prompting: Developers using tools like GitHub Copilot or GPT-4 to scaffold boilerplate, generate tests, or plan architecture.
2. Internal copilots: Custom LLM agents built on company-specific context (codebase, services, documentation) to accelerate onboarding and reduce cognitive load.
3. AI-native workflows: Entire features being prototyped and deployed through AI-assisted iteration. Not as shortcuts, but as process accelerants. These aren’t isolated hacks.

They’re becoming institutionalized. AI-enhanced development is emerging in planning meetings, sprint rituals, and post-mortems. And it’s only going to accelerate.

This movement is growing fast, and so is the ecosystem. Here are a few standout tools that are defining the next wave of AI-powered development platforms:

GitHub Copilot: The most widely adopted code completion assistant, integrated directly into editors like VS Code. Great for scaffolding, commenting, and real-time suggestion.

ChatGPT (OpenAI): Often used in conjunction with code editors for architecture planning, debugging, and writing boilerplate across languages. Claude (Anthropic): Especially strong at understanding longer context windows—great for working with full files or larger codebases.

Claude Code: A specialized AI coding environment from Anthropic, designed for secure and efficient multi-file generation and debugging workflows. Ideal for teams building complex systems through prompting.

Cursor: An IDE purpose-built for LLM integration. Designed around prompting and iteration.

Lovable: A new AI development platform that just raised $200M in Series A funding at a $2B valuation. Lovable says less than 1% of the global population can code. Their mission is to empower the remaining 99% to build, iterate, and launch production-grade software by just talking to AI.

Replit Ghostwriter: Offers AI-assisted coding directly in the browser, great for fast prototyping and education.

Windsurf: Recently acquired, Windsurf is a rapidly growing entrant in the AI-native IDE space. They’ve been making headlines for enabling full-stack development through prompt-driven workflows, with deep integration into modern toolchains.

Each tool varies in UX and integration but share a common trait: making coding conversational.

The article misses something really important: vibe coding only works if your people know how to prompt.

Otherwise, it’s just fancy autocomplete that frustrates more than it helps.

Prompt engineering isn’t just about asking better questions. It’s about understanding how to:

In many ways, this is the new programming language. And like any language, it’s a skill that requires both practice and structure.

Currently, there’s a significant gap between teams that view prompt engineering as a serious skill and those that dabble. The serious teams get velocity.

What is Vibe Coding?

A workflow where you describe what you want in natural language, and the AI generates code, tests, comments, or designs to match your "vibe."

How To Start Vibe Coding:

This is where most organizations hit a wall. They want to use Copilot or GPT at scale, but usage is uneven.

Some engineers soar. Others tap out after a few bad experiences.

That’s why we built Tami to help teams build prompt engineering fluency.

Not over weeks or months, but over days.

Teams that train with Tami report faster development, more consistent AI output, and better collaboration across roles.

Request a demo to see how Tami can help your organization join the vibe coding revolution and learn prompt engineering now.

Thank you for reading!