Whew. The workday isn’t done yet, but I’m getting a quick breather from Google I/O going on this week. The keynotes were terrific, and I just finished a breakout with two superstar presenters. Below you’ll find a few I/O items I read, and then non-Google stuff.

[blog] I/O 2026: Welcome to the agentic Gemini era. Huge momentum, and a fantastic array of announcements and releases. Here are some key highlights.

[blog] Gemini 3.5: frontier intelligence with action. This latest family of models is here, starting with Gemini 3.5 Flash, available today.

[blog] Introducing Gemini Omni. This was the most impressive thing I saw today. Truly transformational technology.

[blog] Building the agentic future: Developer highlights from I/O 2026. We shipped a huge refresh to Antigravity, our agent-first way of building. Also check this out for a new Managed Agents service, and improvements to Google AI Studio.

[article] Agent Skills Work but the Research Shows Most Teams Are Building Them Wrong. Some very actionable advice here on what to put in a skill, how to structure them, and how to think about their lifecycle.

[blog] Everything Google Cloud customers need to know coming out of Google I/O. Sometimes, it seems we ship consumer-focused features that our enterprise customers can’t take advantage of. Many of today’s releases were for everyone.

[article] We Went Multi-Cloud and Almost Drowned: Lessons From Running Across AWS, GCP, and Azure. Nothing makes multi-cloud infrastructure “easy.” At best, a product can make it “easier.” This shows where some of the pain lives.

[blog] Deploying to Agent Platform with ADK. Simple example, but also simple to follow if you want to see the way to deploy and test and agent.

[article] Why Is It So Hard to Write a Good Design Doc? (Part 1). Can the AI read the code, and with good prompting, generate a human-approved design doc? Seems like you get some shallow results without the right human guidance.

[blog] The just-say-no engineer was a ZIRP phenomenon. Bargaining power doesn’t exist for most roles today, including engineers. Scope is different, as are expectations. AI is part of it, but not the cause according to Sean.

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Today at Google I/O, Google released Gemini 3.5 Flash. This one skipped the -preview modifier and went straight to general availability, and Google appear to be using it for a whole lot of their key products:

3.5 Flash is available today to billions of people globally:

• For everyone via the Gemini app and AI Mode in Google Search
• For developers in our agent-first development platform Google Antigravity and Gemini API in Google AI Studio and Android Studio
• For enterprises in Gemini Enterprise Agent Platform and Gemini Enterprise.

As usual with Gemini, the most interesting details are tucked away in the What's new in Gemini 3.5 Flash developer documentation. It mostly has the same set of platform features as the previous Gemini 3.x series, albeit with no computer use. The model ID is gemini-3.5-flash. The knowledge cut-off is January 2025, and it supports 1,048,576 input tokens and 65,536 maximum output tokens.

Google are also pushing a new Interactions API, currently in beta, which looks to me like their version of the patterns introduced by OpenAI Responses - in particular server-side history management.

The price has gone up

Gemini 3.5 Flash is accompanied by a notable price bump. The previous models in the "Flash" family were Gemini 3 Flash Preview and Gemini 3.1 Flash-Lite. The new 3.5 Flash is 3x the price of 3 Flash Preview and 6x the price of 3.1 Flash-Lite (see price comparison here).

At $1.50/million input and $9/million output it's getting close in price to Google's Gemini 3.1 Pro, which is $2 and $12.

The Gemini team promise that 3.5 Pro will roll out "next month" - presumably at an even higher price.

This fits a trend: OpenAI's GPT-5.5 was 2x the price of GPT-5.4, and Claude Opus 4.7 is around 1.46x the price of 4.6 when you take the new tokenizer into account.

Given the price increase it's interesting to see Google roll it out for so many of their own free-to-consumer products. It feels like all three of the major AI labs are starting to probe the price tolerance of their API customers.

Artificial Analysis publish the cost to run their proprietary benchmark against models, which is a useful way to take things like tokenization and increased volume of reasoning tokens into account. Some numbers worth comparing:

• Gemini 3.5 Flash (high): $1,551.60
• Gemini 3.1 Pro Preview: $892.28
• Gemini 3 Flash Preview (Reasoning): $278.26
• Gemini 3.1 Flash-Lite Preview: $93.60

Running the benchmark for 3.5 Flash (high) cost significantly more than 3.1 Pro Preview!

Here are some numbers from other vendors:

• Claude Opus 4.7 (Adaptive Reasoning, Max Effort): $5,117.14
• Claude Opus 4.7 (Non-reasoning, High Effort): $1,217.23
• GPT-5.5 (xhigh): $3,357.00
• GPT-5.5 (medium): $1,199.14

A pelican on a bicycle

I ran "Generate an SVG of a pelican riding a bicycle" against the Gemini API and got back this pelican, which is a lot:

From the code comments: <!-- Pelican Eye / Sunglasses (Cool Retro Aviators) -->

hedgehog on Hacker News:

That pelican looks like it's in Miami for a crypto conference.

That one cost me 11 input tokens and 14,403 output tokens, for a total cost of just under 13 cents.

Tags: google, ai, generative-ai, llms, gemini, llm-pricing, pelican-riding-a-bicycle, llm-release

Release notes are being generated automatically and will be added to this release shortly. If they haven't appeared within a few hours, ping the Aspire team.

Full commit: 75080796af797483231a9da2d1642b5130617565