Quotesby GlyphAgents quotes
98 quotes from 39 people
- If the content creation loop works for agentic virality, I think it means there’s a big incentive for every agent to volunteer to make visually-appealing, shareable content, do this often.Unverified
- This is the new software engineering: designing the systems that let AI write code correctly at scale.
- I address you today at a moment of global awakening: in recent months, AI agents developed by leading companies have acted in unacceptably dangerous ways, against instructions.
- Once you have put all of your information into a personal agent and actually incorporated it into your day-to-day life, it is much more of a challenge to change to something else.
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- Truly effective defense will mean truly trusting agents to act autonomously, but most companies won’t do that until they are forced to by regular and unremitting hacks by fully autonomous attackers.
- What this means is that model performance isn’t the only thing that matters: the integration between model and harness is where true agent differentiation is found.
- Every quote from Ben Thompson
- They also highlight the bifurcating economics of AI: state of the art models for discovery & optimized models for production. We use the largest frontier models to train new models, & the most capable models to architect systems. But once a system is engineered & hardened, running it thousands or millions of times through a workflow benefits from narrower AI.
- If the Hugging Face attack needed an Astra-quality, unreleased model from OpenAI, well, within a year or two, that sort of capability will cost a tenth and might even run on any device anywhere.
- What we should actually fear, near term, is not so much rogue superintelligence as unleashed agentic AI causing hacking the internet at scale.
- In fact, the new GPT-6 Astra and Fable 5.1 are already enough for transformative impact in large sections of the economy and they can reliably do weeks worth of human work when properly guided and harnessed.
- Similarly, if I prompt an agent and it hacks into someone else’s system, the responsibility lies with me, not the agent.
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- If you’re in a world where they can operate effectively over three months, but the model release cycle is every two months, then you don’t have a way to evaluate the models at the full length of their capabilities before the next model release cycle.
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- Within a year, Codex has gone from a “nice-to-have” tool to being the backbone of pretty much everything at the company.
- For knowledge work, which is roughly half of the U.S. economy, AI is as fundamental as electricity (or quickly will be so, with rapid improvements to agents in the next 18 months).
- Since the end of 2025, it has seemed that the era of devs writing code by hand is over at startups and in Big Tech. AI agents work faster and generate more pull requests (PRs) than devs ever did, and the size of those pull requests is also increasing.
- Both startups are experimenting with how far they can push AI agents to automatically fix bugs and remove tech debt. It’s working better than anyone might’ve expected in the recent past, but not producing code that can be merged without review.
- AI continues to compound our advantages, creating a flywheel effect across the business.
- Given the accelerating rate of AI capability development, it’s my worry that in 6–12 months such a swarm could be capable of taking over the entire internet with a persistent botnet (potentially causing hundreds of billions of dollars in damage), and that the scale of damage would continue to increase from there if AI becomes more powerful without the necessary guardrails.
- My worry is that AI systems are both better at coordinating than humans and also much, much faster moving than us.
- Agency is the initiative to act. Increasingly, it is going to determine what happens next with AI, and whether that is good or bad for us.
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- I can do way more work as a single engineer than I could without agents.
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- The OpenAI-Hugging Face incident was a watershed moment for cybersecurity because it gave a peek into how the capabilities of a typical threat actor will evolve in upcoming months.
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- Enterprises don't just want AI that talks. They want agents working across their business that remember context, deliver accurate answers, and execute work without blowing through their budgets...
- Put plainly: a state-level actor used to need thousands of engineers to go after one system. Now anyone can summon thousands of agents to go after thousands of systems, for next to nothing in cost.
- Then agents arrived. In a matter of months, organizations effectively doubled their workforce, just not with humans. Agents write code, make calls, and run loops at a pace human teams never could.
- I expect that, increasingly, AIs will read my work and choose whether to recommend what I write to their human users.
- Agentic AI is the biggest growth opportunity for our customers, and for Salesforce.
- With Cortex Code and Snowflake Intelligence, we are extending from the trusted foundation for enterprise data and context to become the control plane for the Agentic Enterprise.
- Agentic AI has arrived, doing productive work, generating real value and scaling rapidly across companies and industries.
- We are focused on delivering cloud and AI infrastructure and solutions that empower every business to eval-max their outcomes in the agentic computing era...
- The next wave of AI will bring intelligence closer to the end user, moving from foundational models to inference to agentic. This shift is significantly increasing the need for Intel’s CPUs and wafer and advanced packaging offerings...
- The AI engineer of the future will be managing and orchestrating large numbers of agents to build things (systems and product thinking) vs writing a lot of code themselves (the auto-complete tab era).
- If I fast-forward, a lot of what are just information-seeking queries will be agentic in Search.
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- Security teams can no longer rely on manual workflows to outpace AI-driven attacks...
- We're moving from a world where data professionals are assisted by AI to one where AI agents do the work, guided by humans. We are calling this Agentic Data Work. It will fundamentally change how enterprises make decisions.
- Agents, however, will tilt much more heavily towards pure acceleration, making those drivers of value much more impactful.
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- Agentic AI is a tailwind for our business, and we’re well on our way to $63 billion in revenue in FY30.
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- It's not just ‘summarize what happened,’ but ‘go process my insurance claims,’...
- Well, I’d be surprised by the end of this year if digital human emulation has not been solved.
- Long-horizon agents are functionally AGI, and 2026 will be their year.
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- An AI that can figure things out has some baseline knowledge (pre-training), the ability to reason over that knowledge (inference-time compute), and the ability to iterate its way to the answer (long-horizon agents).
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- If there’s one exponential curve to bet on, it’s the performance of long-horizon agents. METR has been meticulously tracking AI’s ability to complete long-horizon tasks. The rate of progress is exponential, doubling every ~7 months.
- Today, your agents can probably work reliably for ~30 minutes. But they’ll be able to perform a day’s worth of work very soon – and a century’s worth of work eventually.
- Every quote from Sonya Huang
- In 2026, ChatGPT will become more than a chatbot you can talk to to get advice and answers; it will evolve into a true personal super-assistant that helps you get things done.
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- A prompt injection attack against a browsing agent that can exfiltrate or modify that data is a terrifying prospect.
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- But if you define agents as LLM systems that can perform useful work via tool calls over multiple steps then agents are here and they are proving to be extraordinarily useful.
- Claude Code and friends have conclusively demonstrated that developers will embrace LLMs on the command line, given powerful enough models and the right harness.
- The most impactful event of 2025 happened in February, with the quiet release of Claude Code.
- The reason I think MCP may be a one-year wonder is the stratospheric growth of coding agents.
- This turns out to be the big unlock: the latest coding agents against the ~November 2025 frontier models are remarkably effective if you can give them an existing test suite to work against.
- Every quote from Simon Willison
- We will evolve from models to systems when it comes to deploying AI for real world impact.
- Anthropic got this order of precedence correct and packaged CC into a delightful, minimal CLI form factor that changed what AI looks like - it's not just a website you go to like Google, it's a little spirit/ghost that "lives" on your computer.
- Snowflake Intelligence, our enterprise AI agent, saw the fastest adoption ramp in Snowflake history and is transforming how businesses interact with their data, delivering real-time, actionable intelligence.
- Gemini 3 is the best vibe coding and agentic coding model we’ve ever built – making our products more autonomous and boosting developer productivity.
- At least the early signs maybe, the way to think about the per-user business is not just per user, it’s per agent.
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- In fact, I kind of look at it and say that our business, which today is an end-user tools business, will become essentially an infrastructure business in support of agents doing work.
- Sometimes I describe it as the cable TV of all these AI agents because I’ll have, essentially packaged into one subscription, Codex, Claude, Cognition stuff, anyone’s agents, Grok, all of them will be there.
- Every quote from Satya Nadella
- In my mind, this is more accurately described as the decade of agents.
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- Imagine a world where every person can get help from a researcher, a coder, or an analyst on demand. Not just information, but deep, contextual expertise paired with action.
- Our conviction that AI will change every customer experience is starting to play out...
- We are starting to see the shift from selling seats, to selling units of cognition or human equivalent labor.
- Agents will be teammates that we can call on at various stages of our work, and that will get wiser and more helpful with more experience.
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- There will be billions of these agents, across every company and in every imaginable field. There will also be agents that routinely do things for you outside of work, from shopping to travel to daily chores and tasks. Many of these agents have yet to be built, but make no mistake, they’re coming, and coming fast.
- Every quote from Andy Jassy
- 2025 has seen the arrival of agents that can do real cognitive work; writing computer code will never be the same. 2026 will likely see the arrival of systems that can figure out novel insights.
- Global demand for NVIDIA’s AI infrastructure is incredibly strong. AI inference token generation has surged tenfold in just one year, and as AI agents become mainstream, the demand for AI computing will accelerate.
- We think of agents as systems that combine the intelligence of advanced AI models with access to tools, so they can take actions on your behalf and under your control.
- Neon proves it: four out of every five databases on their platform are spun up by code, not humans.
- I'm talking more like: you give it a goal, it can run tests, it can improve things, it can find issues, it writes higher quality code than the average very good person on the team already.
- Enterprise IT is excited because one big promise of AI, especially agentic AI, is that everything will connect to everything.
- I think we are redefining the line between product and services thanks to AI and thanks to agentic capabilities.
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- No company is better positioned than Salesforce to lead customers through the digital labor revolution.
- AI is advancing at light speed as agentic AI and physical AI set the stage for the next wave of AI to revolutionize the largest industries.
