Introducing https://t.co/4oowUo7AQT
The new hub for Gemma, including
📚Inference and training guides
🧠 Deep visual architectural guides
🖼️ Online demos, even running models in the browser
And a lot more to come, check it out!
😅Google keeps announcing a future I can't touch.😅
Stayed up late for Google's Gemini agent stream. Expected a Gemini upgrade for everyone.
Enterprise-only. Not for subscribers.
3.5 Pro never shipped. Argon is cyber-defenders-only. The agent is enterprise-only.
Gemini Agent is built for high-ceiling work where EACH task gets its own computer.
You can choose Gemini 4 Argon or Claude Opus 5.5.
10 things that make it a universal work Agent (read till the end to see what a REAL work agent looks like):
1. One Agent, one API
Chat, autonomous objectives, and code generation from a single interface. Assign it work, schedule it, or have it respond to events.
2. Coworker agents with their own identities
It creates job-specific sub-agents, each with its own identity, and computer running in parallel for hours or days.
Each Coworker agent gets its own Workspace account: an agent email, calendar, Drive, and presence in your company directory. You mention it in Chat. It acts under its own identity, not yours, and sees only what you share.
3. Everywhere, including headless
Web, iOS, Android, Windows, Mac, command line, Workspace, Microsoft 365, Slack. It also runs as a headless agent with no dedicated interface.
4. Work 24/7 in the cloud
It keeps one set of memories, context, and personalization graph across every device and channel. Work that takes hours or days keeps running after you close your laptop. You never have to re-brief it.
5. Layers of memory that improve over time
- Session: the task in front of it, even when it runs for days.
- Semantic: a structured knowledge base it builds as it reads documents, talks to people, and works with other agents.
- Procedural: how a job gets done, including skills it writes for itself.
- Episodic: everything it has done before.
6. Proactive by design
It does not wait to be prompted. An email asking you for a deck gets flagged as delegatable, one click to hand off. Your inbox ranks by what matters, not by what just arrived, and tells you why.
7. Tools and skills, with company registries
Salesforce, ServiceNow, Jira, Git, Confluence, Microsoft 365, Slack, BigQuery, Databricks, Postgres, Snowflake, your desktop files, and any MCP server inside or outside your network. Teams publish their own tools and skills to a shared company registry.
8. Model Choice so you are not locked in
It runs each job on the model that fits best, running across the Gemini and Claude models from Anthropic today, with other private and open models to come.
9. Governed like an employee
Every agent gets a cryptographically attested identity with least-privilege permissions, and an audit trail attributed to the agent rather than a person. Agents run in a sandbox behind Agent Gateway, an AI network firewall. Write the policy once and it applies to every agent.
10. Costs you can actually cap
Smart Routing puts each workload on the model with the best performance at the lowest cost. Set a hard spend limit in Cloud Billing and that project's agent pauses until you resume it in one click.
Thank you for reading so far. Stay tuned for updates.
We are 100% committed to make it the best Agent for work.
Hark Pro doesn't show remaining credits in the app yet.
Easy fix, I thought: just have Hark build me a credits panel on Home.
Then it hit me: to check how many credits I have left, I have to spend credits.
Schrödinger's balance 😂
@hark_labs@adcock_brett native usage display, maybe?
And because I'm a human, not a bot: bits of my daily life too.
If you're figuring out AI alongside everyone else — follow along. Let's learn in public.
I'm not an AI expert. I'm just a regular person learning AI by actually using it every day.
This account is my public notebook: experiments, honest fails, small wins — and some real life.
Here's what to expect 🧵
Here's what you'll find here:→ things I try with AI (tools, prompts, workflows)→ what actually happened (no hype)→ honest takes on AI news when it's worth talking about