Performance: dev-browser: 3m53s, $0.88, 100% success rate — beats MCP configs, Chrome extensions, 'browser skill' stacks.

One Agent can now: open X (Twitter), scroll the feed, extract tweets, return clean JSON. No plugins. No extensions. No orchestration.

Add dev-tools package with wt worktree manager CLI - New packages/dev-tools with standalone wt CLI for git worktree management - Commands: wt new, wt scratch, wt prune - Uses Vertex AI (gemini-2.5-flash) for branch name generation via gcloud ADC

Austin built the whole pipeline from his Claude Code terminal using the Notion API. He brain-dumped the desired outcome using Monologue, let Claude Code create the database and data pipeline, and pasted the generated instructions into the Notion custom agent setup.

Open Loop + Infinite Demand = Creative Amplifiers. Content creation & marketing strategy. AI can generate a thousand ad variations or blog posts.

Closed Loop + Finite Demand = Efficiency Plays. AI bookkeeping categorizes transactions, reconciles accounts, files returns. Deterministic rules applied to numbers.

accounting and auditing showing nearly a 20 percent jump on GDPval and even domains like police / detective work showing a nearly 30 percent improvement.

METR conclude that “the length of tasks AI can do is doubling every 7 months”. I’m not convinced that pattern will continue to hold, but it’s an eye-catching way of illustrating current trends in agent capabilities.

The chart shows tasks that take humans up to 5 hours, and plots the evolution of models that can achieve the same goals working independently. As you can see, 2025 saw some enormous leaps forward here with GPT-5, GPT-5.1 Codex Max and Claude Opus 4.5 able to perform tasks that take humans multiple hours—2024’s best models tapped out at under 30 minutes.

f you define agents as LLM systems that can perform useful work via tool calls over multiple steps then agents are here and they are proving to be extraordinarily useful. The two breakout categories for agents have been for coding and for search.

Home security company Vivint, which uses Agentforce to handle customer support for 2.5 million customers, experienced these reliability problems firsthand. Despite providing clear instructions to send satisfaction surveys after each customer interaction, The Information reported that Agentforce sometimes failed to send surveys for unexplained reasons. Vivint worked with Salesforce to implement "deterministic triggers" to ensure consistent survey delivery.

All of us were more confident about large language models a year ago," Parulekar stated, revealing the company's strategic shift away from generative AI toward more predictable "deterministic" automation in its flagship product, Agentforce.

I believe the final policy shall contain robust rationale and, in the best way possible, avoids the perception of rAIcial discrimination

“You have to assume that things can go wrong,” shared Waymo’s head of cybersecurity, Stacy Janes. “You can’t just design for this success case – you have to design for the worst case.”

Side note: When I flagged yours as a dupe during review, the review system slapped me in the face and seriously accused me of not paying attention, a ridiculous claim by itself since locating a (potential) dupe requires quite a lot of attention.

Yes, autoexpect is a good tool, but it is used just to automatically create TCL-expect scripts, by watching for user. So it’s can be equal to writing expect-scripts by hand.

You can now distribute your add-on. Note, however, that your add-on may still be subject to further review, if it is you’ll receive notification of the outcome of the review later.

that can be partially automated but still require human oversight and occasional intervention

but then have a tool that will show you each of the change sites one at a time and ask you either to accept the change, reject the change, or manually intervene using your editor of choice.

Overestimating robots and AI underestimates the very people who can save us from this pandemic: Doctors, nurses, and other health workers, who will likely never be replaced by machines outright. They’re just too beautifully human for that.

the demand for products will keep climbing as well, as we’re seeing with this hiring bonanza.

Last week, Amazon officials announced that in response to the coronavirus they were hiring 100,000 additional humans to work in fulfillment centers and as delivery drivers, showing that not even this mighty tech company can do without people.

Why haven’t the machines saved us yet?

And that’s all because of the vulnerabilities of the human worker.