The Google I/O pieces that actually matter

• Gemini 3.5 Flash: positioned as the agent optimized model, which usually means faster, cheaper, and better at task chaining than flashy benchmark flexing

• Gemini Spark: an always on assistant with Gmail integration, which is basically Google saying “let the agent live in your inbox, not just your browser”

• Antigravity 2.0 and AI Ultra: pricing for the agent era, where usage becomes a serious product design constraint instead of an afterthought

• AI Studio and Android CLI: the part I find most interesting, because this is where agentic AI becomes something developers can actually ship with, not just admire in keynote videos

A hands on way to think about the new workflow

If I were building a tiny Android app with these tools, I would not start by asking AI to “build me an app.” That is how you get demo slop. I’d break it into boring, real steps.

For example:

1. Use AI Studio to scaffold the app shell and basic screens

2. Let the Android CLI handle repeatable build and test tasks

3. Keep the agent on a short leash with narrow permissions and clear output contracts

4. Review generated code like you would review a junior engineer’s PR, because that is basically what it is

5. Only then connect anything sensitive like Gmail or personal data

That last step matters a lot. Everyone wants the magic. Nobody wants to talk about the footguns. But agents with access to accounts and background actions are a different class of risk.

The real technical shift: orchestration, not prompts

People still talk about prompts like they are the main event. They are not. Prompts are just the keyboard. The real work is orchestration.

Agentic systems need memory, tool use, retries, fallbacks, observability, and hard limits. Otherwise they become that one overconfident coworker who says yes to everything and silently creates chaos.

Here is what changes under the hood:

• Latency matters more because the agent may take several steps, not one completion

• Memory becomes a product decision, not just a model feature

• Tool calling needs guardrails, because autonomous actions can wreck trust fast

• Cost control becomes real engineering work, especially for always on agents

If you have ever built background jobs, queues, or workflow engines, this is familiar territory. Agentic AI is basically workflow software wearing a very expensive sci fi jacket.

The part nobody wants to admit

I think a lot of teams are going to underestimate how much trust this requires. If an agent can read your mail, monitor topics, or act on your behalf, then consent becomes product design. Logging becomes product design. Rollback becomes product design.

You cannot just slap a chat bubble on top and call it innovation.

The companies that win here will be the ones that make autonomy feel safe, visible, and reversible. The rest will ship impressive demos and burn user trust in record time.

What I would watch next

If this trend keeps moving the way it looks now, I think we’ll see three big changes:

• Apps will become less screen centric and more action centric

• Search and inboxes will turn into agent surfaces instead of passive containers

• Developer tooling will shift toward workflows where AI writes, tests, and ships with humans supervising the important parts

And yeah, that means some old traffic patterns will get wrecked. If agents start doing the clicking, then a lot of the web’s current attention economy gets weird real fast. But that also opens the door for better interfaces, less friction, and software that feels way more alive.

My take

I am genuinely excited about this, but not because I want AI to replace thinking. I want it to remove the sludge around thinking. The setup work, the repetitive tasks, the boring glue code, the endless tab switching. Give me that back and I can spend more energy on design, product, and the weird creative leaps that actually matter.

That is the promise here. Not just faster coding. A different relationship with software.

If agents become the new developer platform, the people who win will not be the ones who ask the fanciest questions. They will be the ones who design the best systems, set the sharpest boundaries, and build tools that let autonomy scale without turning into chaos.

That feels like the beginning of a bigger shift, honestly. One where software stops being a pile of screens and starts becoming a crew of capable little machines working alongside us. And if we get that right, the next decade could be ridiculously powerful.