Gamaliel

Software Developer

[Gamaliel @MeetGamaliel]

@ExchangeHunker @shadrac_matata @paydhq They messed us up with an event we had last year. It took close to 3 months post event plus a lot of legal to get the event money we processed through their platform.

[Jay @jayair]

Okay let me tell you about what's happening with DeepSeek v4 Flash.

First some background, it launched on Aug 1st and within 2 weeks it went from doing 3T tokens a day to 18T tokens a day on OpenCode; an absurd 6x increase. To put it in context, that's close to doubling up all of OpenRouter's daily volume. It's also likely 30-50% of DeepSeek's total volume.

Jumps like these over a 2-week span are not normal. This happened because the model is absurdly cheap; 350x cheaper than Fable, 175x cheaper than 5.6 Sol, 70x cheaper than Sonnet, and 7x cheaper than Luna. And secondly, it was a marked improvement over the previous Flash model.

For the first time our users got a feel for AI that's "too cheap to meter".

Then on August 16th DeepSeek raised prices by 5x (for peak hours, 2.5x off-peak hours). And it completely killed the growth of the model. It's doing less than half the tokens per day from its peak.

Obviously people were unhappy with the sudden change. Our guess is that DeepSeek genuinely could not handle the absurd 6x jump. Also, it's likely that the increase in GPU prices meant that even if they acquired new capacity, they wouldn't be able to serve it at the original prices.

A quick aside on why DeepSeek Flash is so cheap. It looks like they are running some custom infrastructure to cache way more tokens, for far longer. This matters because we've been scrambling trying to find providers that can fill this near 10T token per day void left by DeepSeek Flash. Unfortunately there are just a couple of people who are able to match DeepSeek's original pricing and that's likely only the case because they are using newer hardware.

That brings us to the current state of things. Over the last week we've talked to as many people as possible to get DeepSeek hosted at the original price. The issue is that even if somebody is able to, it's very hard for them to have enough capacity to handle our volume. It'll take roughly 1000 B300s to handle our throughput.

This is why if you've been using DeepSeek Flash on Go over the past few days, you might not have had the best experience. We've unfortunately cycled through a few different providers.

This 10T token per day gap, though, is an opportunity for every other model lab. It's very clear there's an appetite for a model that's at least as competent and cheap as DeepSeek Flash.

And somehow that still feels like the floor.

[Gamaliel @MeetGamaliel]

@Soihapa2012 @LarryMadowo He went to attend because of the groom who is his friend. What do you mean?

[Gamaliel @MeetGamaliel]

@Fadhili_254 @LarryMadowo Its just sad how people reason.

[Gamaliel @MeetGamaliel]

@Benowitiyada @LarryMadowo @_mbithee He has freewill to post! Plus he's just responding to critics. There's nothing wrong with that🤷‍♂️

[Tencent AI @TencentAI_News]

🤯Introducing Team Memory, same idea as Agent Memory, except your teammates' agents can read it too

2.0.0 beta out today, and the repo hit #1 on github's typescript trending this week

Highlights:
> Solo builders: one place to manage memory across all your agents and AI tools, chat, code, tasks. Built for the one-person company

> Teams: a shared memory hub that turns conversations, docs and code into four reusable assets, Chat Memory, Skill, LLM-Wiki, Code-Graph, governed and shared across agents and frameworks

changelog and repo → https://t.co/BFObcln0Uk

[Kimi.ai @Kimi_Moonshot]

Releasing the model weights and technical report of Kimi K3.

Kimi K3 is our most capable model: a 2.8T MoE model with native visual understanding and a 1M-token context window.

New model architecture: 2.5x the intelligence per unit of compute, not just more params.

Alongside Kimi K3, we're opening up more of the stack behind it — high-performance attention kernels, MoE communication library, and infrastructure for running agent environments at scale.

Model weights: https://t.co/7m7eEg6Y0B
Tech report: https://t.co/yeu6cjpMCT
Tech blog: https://t.co/YTfiMSNM1f

[Brady Long @thisguyknowsai]

Another WTF moment.

A developer just open-sourced a coding agent harness that boots 245x faster than Claude Code. It's called jcode. You launch it and the first frame renders in 14 milliseconds. Claude Code takes 3,436. One active session uses 27.8 MB of RAM. Claude Code uses 386.6. Run ten sessions in parallel and jcode holds at 117 MB while OpenCode swells to 3.2 GB.

Each agent has a semantic memory graph instead of a scratchpad. Every turn gets embedded as a vector. The graph is queried on every turn for related memories, and a sideagent verifies the hits before injecting them into context. Consolidation runs in the background to check for stale or conflicting facts. No manual /remember calls. No token burn on lookup tools.

The provider list is 30+ deep. Claude, ChatGPT, Gemini, GitHub Copilot, Azure, OpenRouter, DeepSeek, Groq, Mistral, Perplexity, Fireworks, Ollama, LM Studio, and any OpenAI-compatible endpoint you point it at. Ran out of tokens on your first ChatGPT Pro sub? /account swaps to the second.

Then there's Swarm. Spawn two agents in the same repo and the server manages them. When agent A edits a file agent B has been reading, agent B gets pinged and can check the diff. Agents can DM each other, broadcast to the room, or spawn their own worker teams for parallel tasks. Groups, channels, and completion statuses are handled automatically.

The UI has live side panels that render mermaid diagrams inline. To make it fast, the author wrote a Rust mermaid renderer 1800x faster than the JavaScript one, then wrote a custom terminal called Handterm because no existing terminal could do smooth partial-line scrolling.

Self-dev mode is where it gets wild. Tell your agent to enter self-dev and it starts editing jcode's own source code, rebuilds the binary, reloads it live, and keeps working across your existing sessions. You can also resume broken sessions from Claude Code, Codex, OpenCode, or pi directly inside jcode. Anthropic's cache goes cold at the 5-minute mark and you're staring down a big cache miss on your next turn? The UI warns you before you spend the tokens.

Written in Rust. MIT licensed. Runs on macOS, Windows, Linux, and Termux. Sitting at 11.2k stars with a native iOS app coming.

https://t.co/OonuUaLXAr

[Gamaliel @MeetGamaliel]

@the_alex Then there’s Kimi - the Xiaomi

[Gamaliel @MeetGamaliel]

@jumaf3 Missed one - Glasshouse PR

[Gamaliel @MeetGamaliel]

@EmmanuelMido @Uglycash What happened?

[Justnx @improvingnox]

7 signos de que tu cuerpo se está inundando de cortisol (y no te habías dado cuenta):

1. Espasmos musculares randoms.

[Claude @claudeai]

Fable 5 is back.

[Gap | Suby @gaspardlezin]

https://t.co/GHbDEvCqkC

[FOEG @foeg_Labs]

BusinessConnect is in motion. Currently addressing pain points in business as shared by the audience. What elements in our ecosystem cater to these? We'll be sharing some of the solutions here Do follow us. @AvaxTeam1 @AvaxAfrica @Team1NG #FoeGLabs #BusinessConnect

[` @lisaawrites]

According to Philosophy, the highest form of peace is to have zero desire to be understood, admired, pitied or even known.

[Google Gemini @GeminiApp]

The Gemini app is now on Mac.

With this new desktop app, you can access Gemini from any screen with Option + Space and share your window to get answers based on the documents, code, or data you're working on.

[Claude @claudeai]

Introducing Claude Managed Agents: everything you need to build and deploy agents at scale.

It pairs an agent harness tuned for performance with production infrastructure, so you can go from prototype to launch in days.

Now in public beta on the Claude Platform.

[Aakash Gupta @aakashgupta]

Let me explain exactly why Apple still uses drag-to-install in 2026, because the joke here accidentally proves Apple right.

A macOS .app is a single self-contained folder disguised as a file. Every dependency, every framework, every resource lives inside it. Drag it to Applications, it works. Drag it to Trash, it's gone. No registry entries. No leftover DLLs. No uninstaller that misses half the files.

Windows installers scatter fragments across Program Files, AppData, the registry, system32, and a dozen temp directories. Uninstalling a Windows app is an archaeological dig. Five years later you're still finding config files from software you forgot you owned.

Linux is worse. Dependency hell is so common they named it. Entire package managers exist to solve the problem of "I installed something and now nothing else works." Flatpak and Snap were invented specifically to copy what macOS bundles already did natively.

The macOS bundle architecture came from NeXTSTEP in 1989. Steve Jobs brought it to OS X in 2001. The core design hasn't changed because the core design was correct. An app is a folder. Installation is a copy. Removal is a delete. Three operations that map perfectly to how humans already think about files.

The drag-to-install window with the arrow isn't lazy UX. It's the entire thesis of the system made visible. You are literally just moving a folder. There is no "installation" step because there's nothing to install. The app is already complete.

Every other OS eventually tried to get here. Windows got MSIX. Linux got Flatpak. Mobile figured it out from day one because phones shipped after Apple proved the model. The pattern everyone else converged toward is the pattern this tweet is calling outdated.

The funniest part: the app being dragged in that screenshot is Claude. An AI that can write code, analyze documents, and reason about complex systems. And the most advanced step in getting it onto your machine is holding down a mouse button and moving your wrist two inches to the right.

That's not a design failure. That's a 37-year-old architecture so good that the most sophisticated software on earth still ships inside it.

[tt✮⋆ @Bluebirdeyessss]

My coping mechanism for everything is either cracking jokes or complete isolation. There's no in between.