PRODUCTS

Gemini 3.8’s edge is intelligence per dollar

Google is adding another lightweight model to Gemini's collection. 

On Wednesday, the company unveiled Gemini 3.8 Flash, the latest addition to its lineup and the third release in the Flash series in six weeks. The company claims the model is its best reasoning and coding model yet but maintains the same speed and cost as its predecessor, Gemini 3.7 Flash. 

The new model comes in two flavors: 

• Gemini 3.8 Flash, which it calls its "most intelligent workhorse model" (the same thing it said about 3.7 Flash just a few weeks ago) with improvements in software engineering, agentic tasks and multi-step reasoning. The new model's introductory pricing is set at $0.75 per million input tokens and $3.75 per million output tokens. 

• Meanwhile, the company also introduced Gemini 3.8 Flash Cyber, its most capable cybersecurity model yet, available specifically for cyber defenders through its Fairwind program, a recently-launched DeepMind program to stay ahead on cyber defense. The company says the model offers "frontier-level performance" in vulnerability detection and automated patching. 

Though the model is still outranked by Anthropic's Claude Opus 5 on benchmarks for knowledge work tasks, long-horizon software engineering tasks, general agentic tasks and computer use, the model beat out Opus 5 and GPT-5.6 Sol on domain-specific tasks for legal, finance, and biology, as well as for agentic terminal coding. Notably, it beats models from frontier labs in one increasingly important domain: Price. 

Gemini's rivals cost 4x to 5x more per token, or higher. Anthropic's Opus 5 costs $5 per million input tokens and $25 per million output tokens, while OpenAI's GPT-5.6 Sol runs $4 per million input tokens and $20 per million output tokens.

Google's latest addition to the Flash family comes as AI rivals like Anthropic and OpenAI navigate releasing their more powerful, bulky and expensive competitors, Mythos and Astra. Google, meanwhile, hasn't released its own heavyweight model since February, when it released Gemini 3.1 Pro, and is rumored to have scrapped internal candidates for Gemini 3.5 Pro because they didn't significantly outperform the Flash series.

Google has all of the pieces necessary to succeed in AI, with access to capital, data and compute and a brand name trusted by the public. Still, it's struggling to put forth the same kind of powerful frontier models that Anthropic and OpenAI have been able to at the same speed. However, with the consistent additions to the Flash series, Google may be trying to capitalize on the movement towards efficiency. Token prices are dropping, largely due to enterprises shifting towards open-source, domain-specific, and small models. As a result, Gemini 3.8 Flash's price-to-performance ratio could be attractive to the businesses by providing more intelligence per dollar.

TOGETHER WITH JUMPCLOUD

AI agents need IAM, too. Meet Agentic IAM.

As businesses put AI agents to work, the opportunity for value grows. But scaling them safely requires IT to know what’s running, who owns it, and what it’s allowed to do.

Agentic identity and access management (IAM) brings agents into the same governance model as people and devices. IT can discover, register, manage, and govern agents throughout their lifecycle, with clear ownership and access controls, rather than creating a separate security model for AI.

That gives organizations a consistent way to manage every identity as their workforce evolves, while maintaining the visibility, accountability, and control security teams need.

Secure every identity. Human or not. That's intelligent, secure IT for the agentic era.

GOVERNANCE

CrowdStrike's answer to AI risk transcends tools

The biggest challenge for humans trying to stop attacks powered by agentic AI is moving fast enough and doing it 24/7. 

On Wednesday at CrowdStrike's Fal.con event in Las Vegas, the company made a series of announcements that allow enterprises to catch up to the pace of AI-powered cyber attacks by giving defenders tools that can move at the same machine speeds as agentic AI. 

"Most research has AI agents outnumbering humans somewhere around 90 to 1," CrowdStrike's chief product officer, AJ Shipley, told the press in a briefing. So enterprises not only need to move as fast as agents, they also have to do it 24/7 and at greater scale.

CrowdStrike's foundational piece for doing that is Agentic Identity Provider (IdP), which aims to force all agents to be identified and shift the security model to continuous identity. And then lock out everything else that's unidentified from accessing sensitive data.

Agentic IdP pulls that off by:

• Giving all agents verifiable cryptographic identities that can't be shared or spoofed

• Registering all agents in a one authoritative directory

• Limiting access to short-lived, tightly-scoped permissions for specific tasks and times

• Connecting every agent action to a human or a workload that initiated it for trackability

"Access can't be a one-time decision. It has to reflect the task, the data, and the risk around it," said Michael Sentonas, president of Crowdstrike, on the Wednesday keynote at Fal.con. "Access only [gets approved] when it's needed, tightly scoped to the specific task, short-lived to reduce risk, and gone when the work is done. You need to remove the access. And when one agent hands off to another, you have to trace that entire chain so that you have explainability."

CrowdStrike also made two other announcements to help enterprise security teams move at machine speeds. The first is aimed at accelerating investigations if a successful attack happens. The second is aimed at protecting the open-source packages that your team's legitimate coding agents use to build software.

The company showed off its AI security operations center (Agentic SOC) that can do investigations across endpoint devices, identities, SaaS apps, clouds, and networks. This use AI and agents to allow security analysts to execute investigations that used to take hours and do them in minutes. The goal here is to use agents to empower humans to work at the same speed as AI and stay in control. 

The other thing the company is doing is dealing with one of the most challenging attack vectors that has emerged in 2026 with the rise of the AI coding agents that  developers and enterprises are using to build, update, and fix bugs in software. Attackers are embedding exploits inside the open-source that these coding agents commonly use. So CrowdStrike has launched Real-Time Supply Chain Attack Protection that scans and blocks malicious packages before they can compromise software and workflows that your coding agents build.

The biggest development from CrowdStrike beyond the actual AI tools to level up enterprises is the sense of confidence that businesses are not overmatched by bad actors using agents to launch attacks at unprecedented speed and scale. CrowdStrike has provided a whole set of tools including Falcon Guardian that we covered yesterday to help enterprises wrestle back control over an environment that has gotten even more scary this summer in light of the OpenAI-Hugging Face incident. The best thing CrowdStrike may have done was give a vote of confidence to the security community that the good guys can come together, share learnings in real-time, and give themselves strategic advantages over adversaries who want to use AI for nefarious purposes. Beyond just the tools, the impact of the conviction and the collaboration shouldn't be underestimated. 

Disclaimer: Jason Hiner's travel to CrowdStrike's Fal.con 2026 event was paid for by CrowdStrike. The Deep View's coverage is editorially independent from the companies we cover.

TOGETHER WITH CRUSOE

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GOVERNANCE

Cheap AI raises the cost of bad judgment

AI makes software easier to create, but the harder and more valuable challenge is controlling what gets built, proving that it works, and managing it over time.

In this episode of The Deep View Conversations, we sit down with Florian Douetteau, CEO and co-founder of Dataiku, to explore how large organizations can turn AI agents from impressive demos into safe, maintainable systems that deliver measurable business results.

Douetteau explains why enterprise AI models are becoming commoditized, why companies may buy 90% of their agents but build the 10% that differentiates their business, and why the emerging discipline of "agent management" will be essential. He also breaks down the dilemma facing CEOs: move too slowly and competitors may gain a structural cost advantage; move too quickly without control and one major AI failure could create a crisis.

Topics covered:

• Why the cost of creating with AI is falling toward zero

• Where value will accrue as models commoditize

• How to balance openness, innovation and enterprise control

• Why subject-matter experts must retain ownership of AI agents

• Why business problems, not perfect data, should drive data strategy

• How enterprises can prioritize transformative AI use cases without stifling experimentation

• The three qualities Dataiku now values most when hiring

• How leaders can use AI without falling into cognitive laziness

If you’re trying to move enterprise AI beyond pilots, govern a growing portfolio of agents or understand where durable value will emerge as AI creation becomes cheaper, this conversation offers a practical framework for building quickly without losing control.

📺 Watch on YouTube
🎧 Listen in your favorite podcast player 

Subscribe to Deep View Conversations for interviews with the leaders shaping the future of AI, business, and technology: tdv.transitor.fm 

LINKS

• Why Sonos is opening its speakers to any AI model 

• OpenAI joins ChatGPT Health with Epic EHR for 325 million patients

• AI security firm HiddenLayer raises $100 million Series B

• Enterprise AI firm Wonderful raises $550 million at $5 billion valuation

• OpenAI is reportedly building "automated shutdown" capabilities for AI

• Zuckerberg says Watermelon, Muse Spark open weights "coming soon"

• Cursor Cloud Agents can now run in locked down Cloudflare Sandboxes

• Gemini Notebook: expanding Short Video Overviews to 70+ new languages

• Qwen3.8-Max-0902: debuted at #1 overall in the Code Arena

• Google Pics: AI image creation rolling out to Workspace and AI Pro & Ultra subscribers

• Atlas: world's first multimodal world model that generates image and video frames with "pixel-perfect camera control and reconstructs them in 3D"

• Muse Voice Transcribe: first real-time audio perception model developed by Meta Superintelligence Labs

• Adobe for Slack: 70+ tools from Adobe’s creative and productivity suites in Slack

• Logicbroker: AI Engineer

• Fudo Partners: Artificial Intelligence Engineer

• Stott and May: AI Engineer-Agentic Workflow

• Corebridge Financial: AI Engineer

GAMES

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