Eric Bragas

Founder, Magic & Co. AI operations consulting built on Claude. Workshops, implementation, Skills Library. Building the Austin Claude community.

[Eric Bragas @ericbragas]

I run Magic & Co., an AI consulting firm in Austin built entirely on Claude.

Three things we do:

• Implementation consulting. MCPs, agentic workflows, skills architecture.
• AI for Founders Workshop. Full day, hands-on, you leave with Claude installed and a 90-day plan.
• Public Skills Library. Claude Code plugins built from real consulting work.

I've been in data and consulting for 12 years. Previously ran workshops at a Microsoft Partner. Same playbook, new paradigm.

Building the Austin Claude community. If you're a founder figuring out where AI fits, I want to help.

[Eric Bragas @ericbragas]

@mikefutia SEO

[Eric Bragas @ericbragas]

@MichLieben Ads

[Eric Bragas @ericbragas]

@MichLieben Ads

[Eric Bragas @ericbragas]

Prompt engineering is dead weight when your context file does the heavy lifting.

Save this for when you're ready to build yours.

[Eric Bragas @ericbragas]

The fix: a context file.

One document your AI reads before every session. Your brand, your preferences, your offers, how you like things done.

[Eric Bragas @ericbragas]

Want to build one? Open ChatGPT or Claude and say: "Build a context file about me and my business. Interview me one question at a time."

Twenty minutes of answers. Every prompt after that gets better.

[Eric Bragas @ericbragas]

Most people re-explain everything to their AI every single time. Their business, their tone, their goals.

Every conversation starts from zero.

[Eric Bragas @ericbragas]

You're writing 500-word prompts to get what a 5-word prompt can do.

The difference isn't skill. It's context.

[Eric Bragas @ericbragas]

I keep hearing the same question from founders: "Should I use Claude or Codex? What about Antigravity?"

So I ran an experiment. Same prompt, same task, three platforms at once. "Build a landing page for my AI workshop."

They all did the same thing. Read the workspace. Made a plan. Wrote the code. Spun up a local server. Three working landing pages.

The outputs converge because every AI agent runs the same loop: observe, think, act. The platform is just the car. The driving skill transfers.

Learn context files. Learn memory. Learn tool connections. Those work everywhere.

Stop comparing dashboards. Learn to drive.

[Eric Bragas @ericbragas]

@thatsKAIZEN Yea, thought that was a weird one from Marc.

Felt more like the idealization of blind pursuit over asking why we’re pursuing a certain goal.

As much as I respect the guy! I’m glad he isn’t running a frontier AI company.

[Eric Bragas @ericbragas]

Once you see the loop, you stop evaluating AI tools by their UI and start evaluating them by how well they observe, think, and act.

Save this. It applies to every agent you'll use.

[Eric Bragas @ericbragas]

Most people use AI like a chat window. Ask a question, get an answer, repeat.

That's not how agents work. Agents take a goal and run with it.

[Eric Bragas @ericbragas]

Claude Code, ChatGPT, Cursor, Codex. Different interfaces, same core loop underneath.

The platform is the car. The loop is knowing how to drive. Learn the loop once, use it anywhere.

[Eric Bragas @ericbragas]

AI doesn't shrink your team. It turns specialists into cross-functional players who can own more of the work. Build for that.

Follow for more on how AI actually changes how teams work.

[Eric Bragas @ericbragas]

Most companies are asking the wrong question about AI and headcount. The question isn't "how many people can we cut?" It's "what can each person now do that they couldn't before?"

[Eric Bragas @ericbragas]

What makes this work in practice: shared context, common tools, AI-accessible knowledge bases. You have to engineer the environment so people with different backgrounds can operate on the same work without constant translation overhead.