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Samsung's Galaxy Z Flip 8 is slimmer and there's now more activity on the cover display.

Samsung has officially announced the Galaxy Z Fold 8 Ultra foldable smartphone, the flagship in the expand Z Fold lineup.

Google and Samsung have revealed the Gemini-powered AI tools coming to the new Galaxy foldables and smartwatches.

The Samsung Galaxy Ultra Watch 2 has a slimmer and more rugged design than the first Ultra.

Samsung has unveiled a base Galaxy Z Fold 8 model that comes in a different shape than previous Fold devices.

The Z Fold 8 Ultra's improved performance, faster charging and a new ultra-wide camera are nice, but what we really want is the regular model's wider screens.

The new base version of the Z Fold 8 has reworked aspect ratios for both its interior and exterior displays.

We've had Samsung's latest Ultra smartwatch for about a week, and here are our first impressions.

It's a year of minor upgrades for the Z Flip series.

Thinner watches, wider foldables, higher prices.

People spend hours watching videos on their smartphones. The wider, shorter, and lighter Galaxy Z Fold8 caters to exactly that.

Samsung's annual summer event kicked off on Wednesday morning with the company unveiling a new lineup of watches and foldables. Following weeks of rumors and leaks, Samsung announced the Galaxy Z Fold 8 with a completely new design that's shorter and wider than last year's Fold, a new "Ultra" Fold, an updated Flip model, and […]

Samsung's new Galaxy Z Flip 8 feels more like a regular phone than ever. It's thinner, lighter, and has a front screen you can do just about anything on. Whether that's a good or bad thing, I'm not quite sure yet. I spent three hours with Samsung's newest flip phone last week, and it doesn't […]

It's a year of refinement for the Galaxy Watch. With the new Galaxy Watch 9 and Galaxy Watch Ultra 2, which are being announced today, Samsung is more or less taking what people like about its watches and tweaking those elements to be better. The company has been doing this for the past few generations […]

A year after overhauling its Z Fold phone with a radically thinner design, Samsung has changed things up again, this time altering the shape entirely. The Z Fold 8 is wider than any of Samsung's previous foldables, and shorter too, a size and shape somewhere between Samsung's traditional Flip and Fold models. In photos, I […]

While we wait for Apple's rumored foldable iPhone, Samsung is polishing a design it already has on the market. I just spent three hours with my hands on the new Z Fold 8 Ultra, and all I can think about is how Samsung finally made the crease invisible. Samsung says it achieved this thanks to […]

Samsung’s folding phone family has a new middle child with a fresh form factor, but which of its eighth-gen foldables is right for you?

Passionfroot, a German startup building a marketplace connecting B2B creators with brands, has raised $15M in a Series A round led by Insight Partners.

I spent months building an AI agent platform. I launched it on Product Hunt yesterday. Zero signups. The comments were friendly. Three of the four asked for the same thing — not features, not integrations, not a lower price. They wanted to see what the agents did and what they cost . One put it better than my own landing page ever did: they liked that it wasn't "a black box." So I went to make the cost dashboard better. Instead I found out my product had been lying to me for months, and the lies had a pattern. Here's everything, with the code. 1. Every run cost $0.00 The Cost Analytics page reported $0.02 in total across ~100 executions . I'd assumed that meant the platform was cheap to run. It meant the data was being destroyed at write time. cost_cents = int ( ( llm_response . prompt_tokens * 0.5 / 1000 ) + ( llm_response . completion_tokens * 1.5 / 1000 ) ) A typical run on my platform is 56 prompt tokens and 45 completion tokens. That's 0.0843 cents . int() makes it 0 . Not some runs. Essentially every run — because almost every LLM call costs less than one cent. The production numbers: 189 agent runs, 2 with a non-zero cost. 99% of my cost data was zeroes, and the two survivors were just big enough to clear a whole cent. The rates in that formula were correct. I checked them against the providers' pricing pages; the arithmetic is right. The bug is entirely int() on a value that is almost never ≥ 1. A Decimal would have been the textbook fix, but Decimal / float raises TypeError and ~80 call sites do arithmetic on this number, so I widened the column to a float and kept the unit (cents). It's a dashboard estimate, not money — Paddle handles money — so float rounding is irrelevant here. 2. Workflow costs were never recorded at all Truncation at least loses precision. This one lost everything. WorkflowExecution.total_cost_cents and total_tokens_used had no write site anywhere in the codebase . Not a broken write — no write. The columns had been NULL since the feat

If you've built even a simple AI agent, you've probably noticed that the "agent loop" itself is deceptively simple: the model gets a message, decides whether to call a tool, gets the result back, and repeats until it has an answer. But real-world agents need a lot more than that bare loop to actually work well. What happens when a conversation gets so long it blows past the model's context window? What if a tool call gets interrupted halfway through and leaves your message history in a broken state? What if you want the agent to keep a running todo list of what it's working on, or delegate parts of a task to a specialized sub-agent, or read and write files as part of its job? You could bolt all of this onto your agent manually. Or, if you're using Deep Agents, you get most of it for free through something called middleware . This post walks through what middleware actually is, why Deep Agents ships with a default stack of it, and how each piece behaves, with runnable code for each one so you can see it working instead of just reading about it. So What Is Middleware, Really? If you've done any web development, the term "middleware" probably already rings a bell. It's the same idea here. Middleware is code that sits around the core agent loop and gets a chance to run before or after certain things happen, like before a tool call executes, after the model responds, or right before messages are sent to the model. Instead of writing all of this logic directly inside your agent, you attach separate, independent pieces of middleware that each handle one specific concern. This matters for two reasons: You don't have to build common behaviors from scratch. Things like managing a todo list, summarizing long conversations, or handling file access are problems almost every non-trivial agent runs into. Deep Agents ships default middleware for these so you don't reinvent them every time. You can customize behavior without touching the agent's core logic. Need a custom summarizati