Hi AI Futurists,
OpenAI wants AI to stop waiting for instructions and start doing the work. Its next generation of agents could manage email, calendars, Slack, research and other workplace tasks, turning ChatGPT from something people ask questions to into something they delegate work to. Let's take a look.
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Top AI news
OpenAI wants an agent for everything
3 AI tools to boost your workflow
AI in the wild
AI Investment Report
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How AI-Era Pricing Is Reshaping Finance Operations
Usage-based and hybrid pricing models are changing how B2B companies generate revenue — and creating new headaches for the finance teams behind them.
Tabs co-founder Rebecca Schwartz and PwC Partner Amit Dhir sat down to unpack exactly what that means in practice: how pricing model decisions ripple into revenue recognition, forecasting, and financial ops — and what it takes to scale without piling on manual work.
Watch the on-demand recording to get practical frameworks, real-world examples, and a clear path to operationalizing usage-based revenue — including a forward-looking take on how AI will reshape financial workflows. If your team is navigating pricing complexity heading into the back half of the year, this is worth an hour.

Top AI News
🧠 Goldman Warns AI Could Reshape Skills (CNBC). AI may help people work faster, but Goldman Sachs warns that depending on it too heavily could erode the skills workers need to stay effective.
🤖 China’s Workers Face AI Pressure (AP News). As AI changes how companies hire and operate, Chinese workers are adapting to a labor market where some jobs are disappearing while new skills are becoming necessary.
🧸 WildBrain Bets on Kid-Safe AI (Variety). WildBrain is acquiring Personality AI to bring conversational technology into children’s entertainment, pointing to a future where kids interact with characters rather than simply watch them.
⚡ Texas Reconsiders Its AI Boom (Axios). Greg Abbott is facing growing pressure over the costs of data centers, as Texas communities question whether AI infrastructure is bringing enough benefits to offset its demands on power, water, and local resources.
🛡️ OpenAI Calls for Faster AI Security (AI News). OpenAI’s president is urging businesses to strengthen their AI defenses now, warning that organizations need to prepare for security threats before increasingly capable systems become harder to control.
🤗 Hugging Face Draws $13B Interest (TechCrunch). Hugging Face is reportedly in acquisition talks at a valuation of around $13 billion, underscoring how the infrastructure and open-source ecosystem around AI is becoming a major target for corporate consolidation.
🎓 Teachers Face the Deepfake Classroom (Wired). Students are using AI to create fake images and videos involving teachers, forcing schools to confront a new kind of misconduct that can spread quickly and blur the line between digital pranks and real-world harm.
🛸 AI Drones Inspect Power Poles (CBS). A Chicago pilot program is using drones and AI to spot damaged power poles, showing how automated inspections could help utilities find problems faster while keeping workers out of dangerous situations.
🛰️ AI Drones Choose Their Targets (NYT). A Russian drone reportedly used an Nvidia computer to identify and select its own target in Ukraine, marking a shift from human-piloted weapons toward machines making life-or-death decisions on their own.
💼 Women Left Behind by AI (Yahoo). As AI reshapes high-paying careers, women could face growing pressure to adapt as the skills, roles, and opportunities that once drove their economic progress begin to change.

OpenAI wants an agent for everything

The next phase of AI may not be about getting answers, but instead handing AI the keys to your work. OpenAI is pushing ChatGPT Work toward agents that can access email, Slack, phones and workplace software, then carry out multistep tasks instead of waiting for a human to guide every step. The company sees this as a way to move agentic AI beyond programmers and into accounting, investing, medicine and other knowledge work.
The scale of the ambition is striking. An OpenAI-backed study found that 98% of OpenAI employees were using Codex in June, compared with 17% of organizational subscribers and less than 1% of individual subscribers. OpenAI says more than a billion people prompt ChatGPT, but the joint Work and Codex app has only about 20 million users. The gap shows the problem: AI agents can be powerful, but most people do not yet want to configure permissions, connect their data or learn a new workflow.
OpenAI is betting that the interface can solve that problem. Instead of asking people to learn command lines, tools and complex settings, it wants users to describe what they want and let the agent figure out the steps. But autonomy creates a tradeoff: the more useful an agent becomes, the more access it needs. One TechCrunch test used more than 80 million tokens in four days, with an estimated cost of $65 against a $20 monthly subscription. The future of work may therefore depend less on whether AI can do the job and more on whether humans are willing to let it.
Takeaways at a Glance:
OpenAI wants AI agents to move beyond coding into everyday white-collar work.
ChatGPT Work can connect AI to tools such as email, Slack, calendars and workplace software.
The major hurdle is not capability alone. It is trust, permissions, usability and cost.
OpenAI employees are adopting agentic tools far faster than outside users.
Anthropic's Claude Code helped establish a more interactive agent model, forcing OpenAI to rethink its approach.
Agents that handle longer tasks can consume large amounts of compute, creating a challenge for the economics of $20 subscriptions.
The biggest strategic prize may be control of the workflow, not simply control of the underlying model.
What We Think About It:
The most important shift here is not that ChatGPT can perform more tasks, but that AI is moving from something people consult toward something people delegate to.
The winning agent will probably be the one that earns trust without demanding that users understand how everything underneath it works.
The strange part is that AI may make work easier at exactly the moment when deciding what to let a machine do becomes a new form of work.
What You Can Do Right Now:
Pick one repetitive workflow, such as weekly reporting, calendar management or spreadsheet analysis, and experiment with an agent before giving it broader access.
Treat permissions like employee permissions: start with the minimum access required and avoid connecting sensitive financial, personal or confidential information until the system has earned trust.
Learn to evaluate AI work rather than simply generate it. The ability to check an agent's decisions may become as valuable as the ability to prompt one.

Get more done with these AI tools
Offloop: A shared workspace where people and AI agents get work done.
A workspace built for people and Agents. They share Channels, can be @ mentioned, own work, review results, and hand off to the next owner.
Context, files, decisions, tool activity, and artifacts stay attached to the work. Owners, approvals, and next steps remain durable and traceable.
Workspace-scoped identity, exact access grants, isolated runs, approval gates, and revocable connections govern what each Agent may see and do.
For teams looking to streamline their work with AI agents.
Contrive: Search and act across all your work apps.
Contrive is a unified search and action layer for company knowledge.
It synthesizes context across connected tools, preserves source traceability, and turns results into immediate actions all from a keyboard-first desktop command bar.
Unlike search only products or generic AI assistants, Contrive closes the gap between finding and doing, while respecting workspace permissions and giving teams precise control over what gets indexed.
For teams that want more efficient ways to work across multiple apps.
Parallely: Ask one question. Get a canvas of parallel ideas.
Parallely refracts your question into an infinite canvas of parallel AI idea cards streaming in live.
Branch anywhere, merge cards into syntheses, compare trade-offs, turn any card into a two-host podcast, and collaborate in real time.
For anyone looking for a better way to understand new concepts or brainstorm using AI.

AI Investment Report
This 121-page research report provides the first comprehensive taxonomy of public companies, private ventures, and tokenized protocols building the infrastructure for autonomous AI systems. Compiled by Lex Sokolin, former Chief Economist at ConsenSys, fintech strategist at Autonomous Research, and current Managing Partner at Generative Ventures, this report delivers institutional-grade analysis of 100+ companies across 14 critical infrastructure layers. Learn more here.
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