Peter Doolan

Chief Customer Officer for Slack a Salesforce company. Leading a diverse group of strategists, and designers serving strategic customers globally.

[Peter Doolan @peterdoolan]

What’s your organisation’s superpower? If your people and their commitment to #CX isn’t part of the answer, it’s time to rethink: https://t.co/eue2hLGkqE #innovation #4IR

[OpenAI @OpenAI]

Introducing GPT-Realtime-2 in the API: our most intelligent voice model yet, bringing GPT-5-class reasoning to voice agents.

Voice agents are now real-time collaborators that can listen, reason, and solve complex problems as conversations unfold.

Now available in the API alongside streaming models GPT-Realtime-Translate and GPT-Realtime-Whisper — a new set of audio capabilities for the next generation of voice interfaces.

[David Sacks @DavidSacks]

It’s time to demystify Mythos.

Mythos is not magic. It’s not a doomsday device. It’s the first of many models that can automate cyber tasks (just like coding).

OpenAI’s GPT-5.5-cyber can now do the same. And all the frontier models (including those from China) will be there within approximately 6 months.

It’s important to recognize that these models do not create vulnerabilities; they discover them. The bugs are already in the code. Using AI to discover and patch them will actually harden these systems.

The leap from pre-AI cyber to post-AI cyber means that there will be a big upgrade cycle. After that, however, the market is likely to reach a new equilibrium between AI-powered cyber-offense and AI-powered cyber-defense.

Obviously it’s important that cyber defenders get access before cyber attackers. That process is already underway but needs to happen quickly (see point above about Chinese models).

Unlike Mythos, GPT-5.5-cyber appears not to be token constrained so it may be the first cyber model that defenders actually get to use.

[Sam Altman @sama]

we're starting rollout of GPT-5.5-Cyber, a frontier cybersecurity model, to critical cyber defenders in the next few days.

we will work with the entire ecosystem and the government to figure out trusted access for cyber; we want to rapidly help secure companies/infrastructure.

[Riley Brown @rileybrown]

Learn 95% of Codex in 28 minutes

These are the 7 knowledge work capabilities...
inside Codex, the super-app

00:00 Intro
02:19 Capability 1 - Full File Access
07:41 Capability 2 - Persistent Memory
10:46 Capability 3 - Plugins
13:52 Capability 4 - Skills
19:22 Capability 5 - GPT Image Access
21:03 Capability 6 - Browser and Computer Use
23:58 Capability 7 - Automations
25:31 Bonus Feature - Chronicle
27:21 Summary

[Peter Doolan @peterdoolan]

Here it is. Simple. Let’s roll.

[Aaron Levie @levie]

Had meetings and a dinner with 20+ enterprise AI and IT leaders today. Lots of interesting conversations around the state of AI in large enterprises, especially regulated businesses.

Here are some of general trends:

* Agents are clearly the big thing. Enterprises moving from talking about chatbots to agents, though we’re still very early. Coding is still the dominant agentic use-case being adopted thus far, with other categories of across knowledge work starting to emerge. Lots of agentic work moving from pilots and PoCs into production, and some enterprises had lots of active live use-cases.

* Agentic use-cases span every part of a business, from back office operations to client facing experiences from sales to customer onboarding workflows. General feeling is that agentic workflows will hit every part of an organization, often with biggest focus on delivering better for customers, getting better insights and intelligence from data and documents, speeding up high ROI workflows with agents, and so on. Very limited discussion on pure cost cutting.

* Data and AI governance still remain core challenges. Getting data and content into a spot that agents can securely and easily operate on remains a huge task for more organizations. Years of data management fragmentation that wasn’t a problem now is an issue for enterprises looking to adopt agents. And governing what agents can do with data in a workflow still a major topic.

* Identity emerging as a big topic. Can the agent have access to everything you have? In a world of dozens of agents working on behalf, potentially too much data exposure and scope for the agents. How do we manage agents with partitioned level of access to your information?

* Lots of emerging questions on how we will budget for tokens across use-cases and teams. Companies don’t want to constrain use-cases, but equally need to be mindful of ultimate token budgets. This is going to become a bigger part of OpEx over time, and probably won’t make sense to be considered an IT budget anymore. Likely needs to be factored into the rest of operating expenses.

* Interoperability is key. Every enterprise is deploying multiple AI systems right now, and it’s unlikely that there’s going to be a single platform to rule them all. Customers are getting savvier on how to handle agent interoperability, and this will be one of the biggest drivers of an AI stack going forward.

Lots more takeaways than just this, but needless to say the momentum is building but equally enterprises are acutely aware of the change management and work ahead. Lots of opportunity right now.

[Peter Doolan @peterdoolan]

@sama I’ve avoided learning how to use the “expert” features of spreadsheets for the last 30 years and just watched in awe as our operations teams performed numerical wizardry at the high alter of excel. Well, seems my laziness paid off :)

[Peter Doolan @peterdoolan]

Great model summary for those of us trying to keep up with the pace of model change. Congrats to OpenAI on the new model as we work it into our processes.

[Robert Scoble @Scobleizer]

What does @OpenAI GPT 5.4 (just released this morning) mean for developers?

You talked about it. My AI agents read it. Wrote a report. Sent it over to @NotebookLM. Which made this video. Using the new cinematic quality released yesterday.

This was all built with your posts from X.

Damn, I wish I had this decades ago.

Do you all get how insane this is for learning about new things?

[Peter Doolan @peterdoolan]

The SDLC will never be the same. Everyone will be a developer.

[Slack Developers @SlackAPI]

✨ From idea → deployed Slack agent in ~15 min.

@vercel's Slack Agent Skill handles app setup, OAuth, events, and deploys for you.

Read more: https://t.co/wuRRcuqhzX

[Slack @SlackHQ]

Same sidebar, only nicer. 💅

We’re rolling out fresh updates to make your Slack sidebar cleaner, more organized, and easier on the eyes:

➡️ Channel indentation for better visual hierarchy
➡️ Smart breakpoints for those who prefer a sleek, narrow sidebar
➡️ Consistent padding & alignment
➡️ Default icons for all of your sections

Refresh your Slack app and get the new sidebar glow-up! ✨

[Slack @SlackHQ]

Organizing your workspace just got a major upgrade! 💖

Now you can share your beautifully-organized channel sections with a simple link, perfect for onboarding new teammates and keeping longtime collaborators in the loop.

Just right-click your custom section and select “Copy section link.” Drop it in a canvas, a DM, or any channel and voilà — you and your team are instantly on the same page!

(Before you ask, your private and Slack Connect channels won't be included. 😉)

Start tidying up today! 🧹

[Shanaka Anslem Perera ⚡ @shanaka86]

A blog post just wiped $30 billion off IBM in a single afternoon.

Not a product launch. Not an earnings miss. Not a competitor undercutting on price.

A five-minute blog post explaining that Claude can read COBOL.

IBM dropped 13%. Worst single-day loss since October 2000. Twenty-five years of stock resilience ended by one AI company publishing a capability update.

Here’s what happened:

95% of ATM transactions in America run on COBOL. Hundreds of billions of lines power banking, airlines, and government systems. The developers who built them retired decades ago. The knowledge left with them. Finding engineers who can even read COBOL gets harder every quarter.

IBM’s moat was never the technology. It was the fact that nobody else could understand it. Entire consulting empires existed because the code was too old, too tangled, and too critical to touch. Companies paid IBM billions because the alternative was catastrophic system failure.

Then Anthropic published a blog post saying Claude Code can map dependencies across thousands of lines of COBOL, document workflows, identify migration risks, and translate legacy logic into modern languages. Modernization in quarters instead of years.

The market heard: the priesthood just lost its monopoly on the sacred language.

And this isn’t the first time. Last week Anthropic announced Claude Code Security for vulnerability scanning. CrowdStrike dropped. Okta dropped. Cloudflare dropped. One company is serially destroying legacy moats with blog posts.

Now here’s where it gets surreal.

This same company, on the same day, also published evidence that three Chinese AI labs ran 24,000 fake accounts and 16 million exchanges to steal Claude’s capabilities. DeepSeek used it to build censorship tools. MiniMax pivoted within 24 hours when a new model dropped, redirecting half its traffic to steal the latest version.

And yesterday, the Pentagon summoned this same company’s CEO for what officials called a “sh*t-or-get-off-the-pot meeting,” threatening to blacklist them like Huawei for refusing to let the military use Claude without safety restrictions.

Three stories. One company. Twenty-four hours.

The company destroying legacy moats faster than the market can reprice them is simultaneously being threatened by its own government and looted by foreign competitors.

Anthropic is valued at $380 billion. Its CEO says a 12-month delay in AI would make him bankrupt. The Pentagon wants to designate it a supply chain risk. Chinese labs are running industrial espionage against it. And it just proved it can vaporize $30 billion in market cap with a Monday morning blog post.

Whatever you think about AI disruption, IBM’s stock just settled the argument.

Full institutional analysis on my Substack.

https://t.co/AEv8EMPdsZ

[Peter Doolan @peterdoolan]

Our customers inside us every day …

[Slack @SlackHQ]

Massive productions.
Constant coordination.
No second chances.
See how @MrBeast's team uses Slack to plan, decide, and execute videos where there are no reshoots. https://t.co/VfXTjPLbPi

[Karri Saarinen @karrisaarinen]

Now live in SF, NYC, and LDN.

Create work with the @linear agent in Slack, delegate it to background agents, and add leverage across your whole org, from product to marketing to sales.

[Slack @SlackHQ]

🥁 Introducing the all-new, intelligently redesigned Slackbot: The out-of-the-box personal agent for every employee. 🎊
https://t.co/YA9tdzjC1I

[Slack @SlackHQ]

Coming soon. 👀

[Peter Doolan @peterdoolan]

@jimfarley98 Will we see you in a ARA rally car? Fiesta is a great way to start. Or better still grab a Mark II Escort from the UK or Ireland :)

[Slack @SlackHQ]

Boost your team’s efficiency in Slack with https://t.co/7GTNpJGNEw 📈

@relay.app helps you automate routine work, connect your go-to tools, and keep tasks moving — all from Slack.

Build no-code workflows that trigger from messages or reactions, integrate apps like Asana, Gmail, Notion and Salesforce, and use AI to summarize info or draft updates when you need an extra hand. 🤝

If your team lives in Slack, https://t.co/7GTNpJGNEw makes getting work done faster and easier. Now available in the Slack Marketplace 👉https://t.co/Ejvn1cEPJ1

[Peter Doolan @peterdoolan]

The entire software development stack is being reschuffled before our eyes at lightning speed. We are seeing the new stack for the next generation of devs scaffold before our eyes. 👀

[Peter Doolan @peterdoolan]

@ES_News_ @grok tell me more about UK police