Gonzalo Gomez

Sr. Web Developer. I build custom software (Laravel/Nest/React/Twilio) and supercharge it with AI. You can find code content in

[Gonzalo Gomez @ggomezdev]

🚀 I help SaaS, startups & telcos build cloud communication platforms using Twilio + Laravel

✅ Twilio Flex setup & plugin development
✅ A2P 10DLC + SMS/WhatsApp
✅ AI voice agents + SaaS apps

🌍 LATAM-based, US client focus
📅 Book a call → https://t.co/lfU9dYpWQy

[Gonzalo Gomez @ggomezdev]

It works on my machine 😶‍🌫️

[ClaudeDevs @ClaudeDevs]

Usage limits are up, effective today we're:

1) Doubling Claude Code's 5-hour limits for Pro, Max, Team and seat-based Enterprise plans

2) Removing peak hours limit reduction on Claude Code for Pro and Max plans

3) Substantially raising our API rate limits for Opus models

[Gonzalo Gomez @ggomezdev]

@PovilasKorop When searching for jobs, you got to check the hiring rate and money spent. Not to mention the verified payment method.

When hiring, I noticed some freelancers hire themselves through different accounts and receive around 10-50 bucks on each job, but they do it to boost ratings

[Claude @claudeai]

Introducing Claude Opus 4.7, our most capable Opus model yet.

It handles long-running tasks with more rigor, follows instructions more precisely, and verifies its own outputs before reporting back.

You can hand off your hardest work with less supervision.

[Gonzalo Gomez @ggomezdev]

If you're evaluating WhatsApp infrastructure for an AI communication layer, the BSP decision is made before anything else. Reply "official" and I'll share a list of compliant providers that actually support AI integration at scale

[Gonzalo Gomez @ggomezdev]

1/ WhatsApp banning your bot is not a moderation glitch. It's your architecture failing at a predictable point.

[Gonzalo Gomez @ggomezdev]

The tradeoffs are real: per-conversation pricing, template approval for business-initiated messages, 24-hour session windows that require queue management. These are solvable at the architecture level. A permanently banned production number is not.

[Gonzalo Gomez @ggomezdev]

I’ve been spending more time thinking about these pipelines as infrastructure rather than “AI features”.

Curious how others are approaching this once things move past prototypes.

[Gonzalo Gomez @ggomezdev]

Most voice AI problems I see in production have nothing to do with the model.

They come from how the system is wired together.

[Gonzalo Gomez @ggomezdev]

Two teams can use very similar models and end up with completely different products.

One feels usable.

The other feels like a demo.

At that point, it’s no longer an AI problem.

It’s a systems design problem.

[Gonzalo Gomez @ggomezdev]

We all gotta start somewhere.

Can’t thank enough the ppl who found my content useful 💪🏻🙌🏻

[Gonzalo Gomez @ggomezdev]

This enables personalization across sessions.

The most common mistake I see:

Trying to use a single tool (often Sheets) for everything.

Prototypes might work like this.

Production systems usually need multiple memory layers.

If you're designing an AI agent, define the memory architecture first.

Then choose the technology.

[Gonzalo Gomez @ggomezdev]

Choosing the wrong memory for an AI agent can break the whole experience.

When people design AI assistants, many assume a spreadsheet will be enough.

In reality, AI agents use different types of memory.

Here are the 4 most common ones 🧵

[Gonzalo Gomez @ggomezdev]

4️⃣ Identity memory

Here the conversation history is associated with a specific user.

Examples:
• phone number
• email
• account ID