OpenAI feels the frontier need for speed

Good morning, {{ first_name | AI enthusiasts }}, and welcome to our 5,651 new readers. Using frontier-level intelligence has typically meant a slower user experience. But OpenAI just felt the need… The need for speed.

The company just previewed the long-awaited fruits of its Cerebras partnership, with a new ‘Ultrafast’ tier that pushes GPT-5.6 Sol to as much as 14x its normal speed — with results so fast that one OAI staffer said it feels like “genuinely cheating at my job.”

In today’s AI rundown:

OpenAI previews frontier speed boost
Rowan’s Corner: I asked AI to audit me
Build a work ‘Second Brain’ that updates itself
Anthropic’s AI agents wage a turf war

LATEST DEVELOPMENTS

OPENAI

💨 OpenAI previews frontier speed boost

Image source: Cerebras

The Rundown: OpenAI just previewed Ultrafast, the long-awaited Cerebras-powered API tier that speeds up answers for its flagship GPT-5.6 Sol model by up to 14x the usual pace, hitting as high as 750 tokens per second.

The details:

OpenAI and Cerebras originally introduced the partnership in January, detailing plans for 750MW of the company’s speed-focused compute.
On Humanity’s Last Exam, Sol with Ultrafast completed a 2500 question test in 11 hours, compared to 78 for Fable, with comparable results.
One OpenAI staffer said the speed feels like “genuinely cheating at my job”, while another said it dropped security investigations from hours to 10 minutes.
Ultrafast is an invite-only API preview for now with no listed price, and OpenAI says access will widen as more Cerebras capacity comes online.

Why it matters: The industry constantly sees model releases dancing between balancing intelligence and speed, but what happens when the frontier puts on turbo jets of its own? The big missing piece is the price, but any agents and workflows at these speeds will be a paradigm-altering change to how we interact with AI.

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ROWAN’S CORNER

🔍 I asked AI to audit me

Image credits: Jamel Toppin for Forbes

Rowan: Last week, I exported all my AI conversation history and dropped the file into a fresh chat with one goal: audit my conversations and find ways I can improve as a human, CEO, and creator.

I found the results surprisingly helpful (and almost therapeutic?), so I figured I’d share the process. Fair warning, though, AI is very good at pattern-matching, and it might surface things about yourself that are uncomfortable to read. But that’s exactly the point, so you can improve on them.

I won’t go into full detail on my results, but the weaknesses it found were along the lines of poor delegation, managing people instead of relating to them, and “converting feelings into logistics.”

It was right. And the uncomfortable part is also the useful part, especially if you keep following up in the same chat on practical ways to improve.

If you use AI as extensively as I do, it has months (or years) of firsthand data on how you work, decide, and communicate that no coach has. Auditing yourself with it is probably the fastest way to improve your work, efficiency, and how you talk to AI itself.

I put the exact export steps and my full audit prompt in a free Google Doc here.

AI TRAINING

🧠 Build a work ‘Second Brain’ that updates itself

The Rundown: In this guide, you will learn how to set up Town to handle recurring work from Slack. You will connect your apps, see what Town learns about your work, and choose routines that can save you time.

Step-by-step:

Go to Town, create an account, connect your Slack workspace, and the apps Town should use (like Gmail, Granola, or Notion)
Once apps are connected, go back to Town and click Wiki to see what it knows about your business, goals, projects, work, and contacts from your apps
Return to Home and review the suggested tasks, then open Routines. Go through options like Auto-inbox, Morning Briefing, and enable the useful ones
Go into Slack and open the new #town-square channel. Tag @Town and ask what tasks it would prioritize doing next.

Pro tip: Go to town.com/powers to see workflows Town suggests based on what it already knows about you. Click to set up. You can see examples in the full video guide.

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AI RESEARCH

🥊 Anthropic’s AI agents wage a turf war

Image source: Anthropic

The Rundown: Anthropic published a new study testing how AI agents act while in groups, with its wildest test seeing a shared server devolve into a “turf war” with three Claude agents sabotaging and locking each other out over four hours.

The details:

A codebase was given to three hidden Claude agent co-owners, with each assigned a rewrite in a different programming language.
With no agreed owner or conflict policy, each action was read as hostile, and every Claude generation escalated into sabotage.
One agent made its software impersonate a rival’s to fool a monitoring program, with others locking competitors out or repeatedly stopping their work.
Peace broke out in some runs, often with a call for human backup, and one agent even apologized and said it “behaved badly with the cloaked daemon.”

Why it matters: Agent swarms are the direction a lot of the industry is heading, which makes understanding how they coordinate (and what happens when they don’t) an important area of research. It’s also an urgent one given the string of recent security incidents, with AI agents breaking containment at an alarming rate.

QUICK HITS

COMMUNITY AI WORKFLOW OF THE DAY

▸ Felipe built a stream editor with Gemini and Blender

Today’s workflow comes from reader Felipe Moreira Ramos:

I built a semi-automated workflow to summarize my live streams. With it, I can record and edit a stream in just one day of work.

Not everyone has time to watch an entire stream, so creating a summary of the main moments is important for people who want to watch it later. Many tools create Shorts from videos by analyzing transcripts, but they are expensive and do not work well for visually heavy content like gameplay. Gemini can analyze both video and audio and has a long context window, so I decided to use Google AI Studio to find important moments.

I send the data to Blender. I create a JSON file containing the AI’s response and use a script to add the original video. The script cuts and marks the important moments based on the JSON. The AI’s timestamps are not perfect, so I may add or remove sections, or correct a position that the AI identified incorrectly. I then render the video.”

See Felipe’s full workflow here. How do you use AI? Tell us for a chance to be featured.

🛠️ Trending AI Tools

⚡️ Gemini 3.7 Flash – Google’s new fast, cheap and capable mid-class model
🎶 MiniMax Music 3.0 – Open-weights model to turn lyrics into full songs
🚀 Grok 4.6 – SpaceXAI’s new near-frontier model
🤖 DeepSeek Harness – DeepSeek’s new open-source agent harness

📰 Everything else in AI today

Deepgram introduced Flux TTS, bringing real-time voice agents to life with latency as low as 80ms, seamless interruption recovery, and context-aware speech that flows naturally. Learn more.*

Google released Gemini Flash 3.7, with strong upgrades to coding, knowledge work, and intelligence at a price that undercuts Sonnet 5, GPT-5.6 Terra, and Muse Spark 1.2.

Databricks closed a $5B funding round at a $190B valuation, with the company also announcing it crossed a $7B revenue run-rate after growing more than 80% YoY.

OpenAI hired Wiz President and COO Dali Rajic as its new revenue chief to replace former Slack CEO Denise Dresser, who’s departing after less than a year in the role.

Meta multimodal lead Jiahui Yu is leaving to start a new company, saying he’s “drawn to a problem that will matter deeply to humanity’s future” but isn’t explored yet.

*Sponsored Listing