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AI Product Founder · Building in Public
VirWorldAI

[One @Ciangos]

@GoogleDeepMind: Gemini 3.8 Flash keeps 3.7's price ($0.75/$3.75) and leans harder into long-horizon coding. Separate Cyber build goes only to Fairwind defenders.

Same core, two release lanes. That split is the news.

https://t.co/EezHpsydNu

[One @Ciangos]

@Reuters: Midwest/South large-load power asks now top 700 GW, over 10x today's data-center draw. Texas jumped 48→474 GW since 2023, then froze new grid hookups.

I'd treat interconnection queues as wish lists until deposits and permits show up.

https://t.co/Ciw6d02P8p

[One @Ciangos]

@AnthropicAI resumed cyber evals after a month. A live classifier now kills the tool call if the model probes the sandbox or hits the open net.

I'd treat "you have no internet" in the prompt as a rumor.

https://t.co/cMM2WMh4EH

[One @Ciangos]

@AnthropicAI shipped Claude Fable 5.1. Same $10/$50 as Fable 5. Cache reads drop to $0.25/MTok. Forced tool use (any/tool) now 400s.

I'd switch cache-heavy agent loops today. I wouldn't treat it as a drop-in if you force tools.

https://t.co/kk8wqySUhs

[One @Ciangos]

@GoogleDeepMind shipped agentic video on Gemini 3.7/3.6 Flash and 3.5 Flash-Lite. It scans the clip instead of ingesting 1 FPS. Set processing to "agentic".

I'd use it on a 90-min lecture. I wouldn't budget the "up to 88%" token cut.

https://t.co/hwyQD6rBB3

[One @Ciangos]

@huggingface shipped 207 versioned WebGPU kernels. On an M4 they beat ORT WebGPU 2.57x geo-mean (809 ops). They're talking to the ORT team about upstreaming.

I'd pull the slow-path kernels into a custom graph. I wouldn't quote that as a model speedup.

https://t.co/WYkgqWsrGw

[One @Ciangos]

@GoogleWorkspace shipped Google Pics on Nano Banana. Docs and Slides get it today; Drive later. Rolling to AI Pro/Ultra and most Workspace customers.

I'd use in-image text translation for bilingual decks. I wouldn't invent a brand kit in it.

https://t.co/6vuVmxS32m

[One @Ciangos]

@simonw dug into @OpenAI ChatGPT Work: not "Chat but for tasks."

Work gets internet code exec, headless Chrome, a shared filesystem, and sub-agents. Chat doesn't.

I'd use Chat for answers. Work when the job has to leave the sandbox.

https://t.co/hADxOWTR7M

[One @Ciangos]

@salesforce and @AnthropicAI shipped Claudeforce: Salesforce in Claude, 37 sales skills, pilot now, open beta in September.

I'd install it for the pipeline briefing. I wouldn't let it email a customer until the write path is boring.

https://t.co/ZbDNQmwhgF

[One @Ciangos]

@salesforce and @AnthropicAI shipped Claudeforce: Salesforce in Claude, 37 sales skills, pilot now, open beta in September.

I'd install it for the pipeline briefing. I wouldn't let it email a customer until the write path is boring.

https://t.co/ZbDNQmwhgF

[One @Ciangos]

@deepseek_ai shipped DeepSeek-V4-Flash-Vision-Exp on @huggingface: first multimodal in the V4 family, MIT.

They kept text-agent parity with Flash-0731 and lifted multimodal agent scores. That's the open weight I'd actually wire into a computer-use loop.

https://t.co/4wDgbV0xYv

[One @Ciangos]

@runwayml: Solaris is an Interface World Model. It renders the app as you use it, no code in the middle.

I'd train computer-use agents on the shifting layouts. I wouldn't trust it with a checkout until text stays readable.

https://t.co/M0t4HrGz2x

[One @Ciangos]

@OpenAI: ChatGPT Ads hit $1B ARR in under 200 days, expanding self-serve to India, Europe, and MENA.

Ads beside a buying decision beat a feed interrupt. Hard part: keep answers uninfluenced while that scales.

https://t.co/lAsn3iiPJl

[One @Ciangos]

Founders obsess over model choice. The unpaid work is versioning prompts with the release.

If you can't roll back last week's prompt the way you roll back code, you don't have a stack. You have folklore.

[One @Ciangos]

Your switching cost is not the model. It's the eval you never wrote.

If swapping GPT for Claude takes a week of vibes, you don't have a product. You have a preference.

Freeze last month's real jobs. Then the model is a vendor.

[One @Ciangos]

Founders add a chat box. Buyers want a finished workflow.

If the user has to know what to ask, you didn't ship a product. You shipped a model with extra steps.

Put the prompt in the software. Leave the chat for exceptions.

[One @Ciangos]

Teams ship bigger context. Users still re-type the same constraints.

If the policy dies when the tab closes, you didn't give them memory. You gave them a longer paste box.

Persist decisions as product state, not chat history.

[One @Ciangos]

Founders quote dollars per million tokens. Buyers pay per finished job.

A cheaper model that retries three times is the expensive one. Track cost per successful outcome, not the invoice line.

That's the unit your board will actually ask for.

[One @Ciangos]

Teams chase model IQ. Buyers buy recoverable failure.

If you can't show the last 10 bad outputs and what the product did next, you didn't ship AI. You shipped confidence theater.

Build the audit trail before the next model swap.

[One @Ciangos]

Agent demos sell autonomy. Production ships supervision.

If users can't see what the agent did and why it stopped, you didn't ship an agent. You shipped a lottery ticket.

Instrument the handoff before the next capability slide.