denis

all in on Jesus Christ

[denis @dened21]

contrarian opinion:

It will pay to bet on human agents when everyone else is hyping on ai agents.

[KeaneAdvisors.AI @KeaneAIAdvisors]

Leaving Salesforce for Replit.

For literally 25 years I've been an advocate for Salesforce. I've probably paid them half a million over those years.

In one week I've eliminated the need. I built my own personal CRM integrated with pretty much everything. Leads, accounts, contacts, cases, contracts, projects, web scraping for building lead inventory, automated AI outreach (with Human in the loop approvals), sales cadences, website with AI chatbot, automated social media posts, and on and on and on.

My Salesforce experience allowed me, a non programmer, to learn so much. But the ease of using Replit makes my leaving SF easy.

My choice has become simple. Thousands for overly complex Salesforce, plus too much time needing to administer it. Versus a week to plan, and another week to vibe code and debug my plan.

Now <$50 per month. If I want a new feature, I just tell the AIs what I want. A few minutes later it's done.

I cannot recommend Replit any more strongly. Click and just get it. It will change your life.

https://t.co/Ym0i1uyDZ3

[Demis Hassabis @demishassabis]

Celebrating the milestone of a massive 150+ million downloads of Gemma 4 with the release of the new Gemma 4 12B model! It's incredibly powerful for such a small model and it’s tiny enough to run locally on a laptop with just 16GB VRAM. Apache 2.0 license - happy building!

[cat @_catwu]

Excited to share how Anthropic's data team has automated 95% of business analytics queries with Claude. Blog post covers how we approach evals, ablations, and online validation!

[Shann³ @shannholmberg]

how I’m building an agent company inside my agency.

the structure looks like this:

Agency gBrain
→ Orchestrator Hermes Agent
→ Department verticals
→ Specialist agents
→ Scoped sub-agents

gBrain is the company brain.

It gets ingested with the data and experience we already have:

> transcripts
> chats
> previous campaigns
> client learnings
> strategy docs
> internal workflows
> examples of what good looks like

That brain is maintained by a human champion plus an orchestrator Hermes Agent.

Under the orchestrator, we have different department verticals inside the agency.

Each vertical has its own specialist agents.

Some of those specialist agents have even narrower scoped agents underneath them.

I’ve found that narrow scope improves output quality and reduces drift.

> a general “marketing agent” is too vague.

> a lifecycle email agent with access to the right campaigns, voice rules, approval gates, and examples can get very good.

> a technical SEO agent with its own tools, checklists, and source standards can get very good.

> a content research agent with narrow inputs and a clear definition of done can get very good.

The narrower the job, the easier it is to improve the agent.

I use different harnesses for this.

Mostly Hermes Agent, but also CLI harnesses like Codex and Claude Code depending on the job.

I’m still looking for a good bare-bones harness for model routers to run on.

To keep track, I maintain an org chart inside the company gBrain.

The org chart shows:

> top-level orchestrator
> department verticals
> specialist agents
> scoped sub-agents
> which brain each agent reads from
> which tools each agent is allowed to use
> where human approval is required

For clients, I do downstream pods.

Think of them as new agent companies that are isolated from the agency brain, but can still communicate with our agency agents when needed.

A client pod has its own:

> client gBrain
> client orchestrator
> client specialist agents
> client-specific workflows
> client-specific approvals
> client-specific memory

This is important.

You do not want client context bleeding across accounts.

You do not want one agent with every client’s data, every tool, and every permission.

Scope is what keeps the system useful.

The powerful part is that once you build one vertical agent well, you can fork it.

Not copy-paste blindly.

You still need to customize the context, examples, approvals, voice, tools, and workflows.

But you are not starting from zero.

You might have 75% of the agent already done.

That changes the agency model.

You no longer need a full traditional department for every function before you can deliver a well-rounded marketing service.

One or two strong marketing engineers can run an output surface that used to require a much larger team.

But this only works if the agents are actually good.

It takes iteration, taste, source material, QA, workflow design, and real marketing experience.

Bad agents do not become good because you connected more tools.

Vague agents just create vague output faster.

TLDR:
> turn the agency’s knowledge into a brain
> turn repeated work into scoped agents
> turn each client into an isolated pod
> let skilled operators run the system

[Paul Graham @paulg]

I've added a new question to the list I consider during office hours with YC startups. As well as "Can we induce network effects?" and "Would it make sense to go full-stack?" I now ask "Can we make this AI-proof?" Can we ensure this company still exists if AIs do most work?

[Aoden Teo @AodenTeoMT]

Today, we’re excited to introduce Miso One, the most emotive voice model in the world.

Miso One is an 8-billion-parameter text-to-speech model for highly expressive speech generation. It emotes like a human and responds faster than a human, with just 110 milliseconds of latency.

We’ve open-sourced the model weights, with API access coming soon.

Hear how Miso One sounds in the thread below.

[Bishop Robert Barron @BishopBarron]

The horror film “Obsession” is a surprise hit at the box office this summer. Made for around one million dollars, it has already grossed over a hundred and fifty million. But it's not only a financial success; it's also a spiritually quite interesting film. What drives the plot is a young man's ardent desire to be loved by the woman whom he loves. Seeking a gift for Nikki in an occult store, Bear finds a device that advertises itself as “One Wish Willow.” If you break the stick and make a wish, it will come true. In his desperation, he follows the instructions, and it works like a charm. The previously diffident Nikki becomes totally devoted to the delighted Bear. All his dreams, it seems, have come true. Then things go, shall we say, south. I won't spoil any more of the plot. Suffice it to say that Nikki proceeds to devour the young man and push him toward despair.

Throughout this film, I kept thinking of Oscar Wilde's famous line: “the only thing worse than not getting what you want is getting what you want.” The spiritual issue here is one that the masters have recognized for centuries and one that stands at the very heart of Biblical revelation: if you tie your deepest desire to anything or anyone other than God, you will find, not satisfaction, but destruction. This is the moral teaching behind the great Shema prayer: “Hear, O Israel, the Lord your God is Lord alone.” Jesus reiterates this when he says, “You shall love the Lord your God with all your heart, with all your soul, and all your strength.” The psalmist affirms it when he sings, “Only in God will my soul be at rest.”

During the rite of Confirmation, I ask the young people a series of questions, the first of which is “do you renounce Satan and all his works and empty promises?” Up and down the ages, Satan has made the same empty promise: I will give you something less than God and it will make you happy. In point of fact, it will ruin you, and the more you seek to acquire it, the unhappier you will become. What becomes clear in the course of “Obsession” is that the owners of the occult shop where Bear bought the fateful wish-willow are in fact involved with very dark spiritual powers. In my conversations with exorcists, I hear over and over again that those who get ensnared by the devil commence by dabbling in the occult.

“Obsession” is a good horror movie. If you like the genre, and you're not too squeamish, go see it. For it won't just scare you; it will offer some important spiritual truths.

[denis @dened21]

contrarian opinion:

It will pay to bet on human agents when everyone else is hyping on ai agents.

[Paul Graham @paulg]

@t_blom This problem will naturally tend to go away as companies are grown from the start using AI. Then you don't need to extract any domain knowledge from people's heads; it will never have been in people's heads.

[Tom Blomfield @t_blom]

Imagine replacing 90% of your employees with a team of geniuses who have no idea how your company operates.

Total chaos. Nothing works.

That’s what AI feels like today.

The missing piece is extracting all the domain knowledge from people’s heads and providing that as structured context to the models.

[Aaron Levie @levie]

This is effectively the #1 problem for AI agents in the enterprise.

As we go from agentic coding (where a large amount of context is in the code base, and users are technical enough to get the rest to the agent easily) to a world of knowledge work agents, the context problem becomes much more acute.

We see this every day with customers at Box. For existing digital knowledge, it’s often fragmented across legacy systems or environments that don’t play nice with agents, and have access controls that don’t map to the real work that needs to be done, which become a huge hurdle for getting agents the context they need. This has to all get moved to modern, secure cloud environments.

But also, companies often haven’t captured and digitized some of the critical context that agents need to work with. Decisions, processes, and workflows often live in people’s heads and tribal knowledge that need to get turned into unstructured data for agents.

This is actually one of the biggest points of leverage for applied AI companies, because they can work to specialize in getting agents exactly the information and domain expertise they need. But it’s also one of the reasons why FDEs and new system integrator plays will also work so well right now.

The companies that figure this out will be able to get the most out of AI going forward.

[Pope Leo XIV @Pontifex]

Artificial intelligences do not undergo experiences, do not possess a body, do not feel joy or pain, do not mature through relationships, and do not know from within what love, work, friendship or responsibility mean. Nor do they have a moral conscience, since they do not judge good and evil, grasp the ultimate meaning of situations, or bear responsibility for consequences. They may imitate or even simulate, but they do not understand what they produce, for they lack the affective, relational, and spiritual perspective through which human beings grow in wisdom. #MagnificaHumanitas

[jack @jack]

Encyclical Letter of His Holiness Leo XIV Magnifica Humanitas (15 May 2026) https://t.co/cv0FkCVeBt

[Pope Leo XIV @Pontifex]

Let us learn to be rich in a different way: more attentive to relationships, more intent on valuing the common good, more attached to the local area, more grateful in welcoming and integrating those who come to live with us.

[Aaron Levie @levie]

CEOs are uniquely prone to AI psychosis because they’re sufficiently distant from the last mile of work that still has to happen to generate most value with AI.

So when they play with AI, they see the happy path results, often not considering the next 10 or 20 things that have to happen to get sustainable results from agents.

“Look I made this awesome product prototype”. Yes but you didn’t have to review the code before it went into production and fix a bunch of issues.

“Look I generated a contract”. Yes but you didn’t verify all the terms before it goes out to the counterparty and didn’t have to wire up all the past contracts to work with.

The best thing you can do as a CEO is to use AI a *ton* to figure out the real implications of agents in the enterprise, and come out the other side with an appreciation for both the upside and the real work that goes into them.

[Garry Tan @garrytan]

The companies I love working with in office hours are the ones where the founder has a specific, weird, earned insight that nobody else has. Not "AI for X." A genuine edge that came from living inside a problem.

The ones that are dying almost always have the same pattern: technically competent founders building something nobody asked for, moving metrics that don't matter, avoiding the conversation with the one user who'd tell them the truth.

The lucky thing is that 2nd type of founder can become the 1st kind if they don't stand still, they are willing to talk to people, try things, and always seek high rate of learning.

[Zeb Evans @DJ_CURFEW]

Today we reduced headcount by 22%. The business is the strongest it's ever been. So I think it's important to be direct about what I'm seeing and why.

First, I made this decision and I own it. I did it because the way to operate at the highest level of productivity is changing, and to win the future, ClickUp needs to change with it.

Second, this wasn't about cutting costs. Most savings from this change will flow directly back into the people who stay. We'll be introducing million-dollar salary bands. If you create outsized impact using AI, you'll be paid outside of traditional bands.

Most importantly, I have the deepest gratitude for those affected. We're doing this from a position of strength specifically so we can take care of people properly. Everyone affected receives a package aimed at honoring their contributions and easing the transition.

I only see two options: wait for this to play out gradually in the market or be honest about what I'm seeing and act proactively.

THE 100X ORGANIZATION
The primary change is that we're restructuring around what I call 100x org. The goal is 100x output. The roles required to build at the highest level are fundamentally different than they were a year ago.

Incremental improvements to existing systems won't get us there. We need new ones. That means creating enough disruption to rebuild rather than iterate on what's already broken.

The common narrative is that AI makes everyone more productive. It doesn't. Many of the workflows of today, if left unchanged, create bottlenecks in AI systems.

These roles will evolve. But waiting for that to happen naturally means falling behind now.

The 100x org is actually heavily dependent on people - infinitely more than today. This is only possible with 10x people that have embraced and adopted new ways of working.

THE BUILDERS, AGENT MANAGERS, AND FRONT-LINERS

— THE BUILDERS: 10X ENGINEERS
I don't think most companies have internalized what's actually happening with AI in engineering. The common narrative is that AI makes all engineers more productive. That may be true in isolation, but at an organization level - that is the farthest thing from reality.

Here's what we've validated recently at ClickUp: the great engineers, the ones who can orchestrate, architect, and review, are becoming 100x engineers. They're not writing code. They're directing agents that write code. The skill is judgment.

AI makes the best engineers wildly more productive, and everyone else using AI slows these engineers down.
Think about it - the bottlenecks are (1) orchestration - telling AI what to do, and (2) reviewing - what AI did. Everything is leapfrogged and no longer needed.
So who do you want orchestrating and reviewing code?

And how do you want your best engineers to spend their time?

If your best engineers are spending time reviewing other people's code, then this is inherently an inefficient bottleneck. These engineers can review their agent's code much faster than reviewing human code.

The new world is about enabling your 10x engineers to become 100x.

The wrong strategy is to push every engineer to use infinite tokens. Companies doing this are celebrating 500% more pull requests. But customer outcomes don't match the volume of code being generated.

I call this the great reckoning of AI coding, and every company will face this soon if not already.

More code is just another bottleneck to the best engineers, and ultimately to your company's impact as well.

— THE BUILDERS: 10X PRODUCT MANAGERS
Product management and design roles are merging.

Designers that have customer focus, become more like product managers.

And product managers that have intuition for UX become more like designers.

The bottleneck of user research is gone. It takes us just one mention of an agent to kickoff research and analyze results.

The bottleneck of product <> design iteration is also gone. The product builder iterates on their own, along with agents and skills that ensure alignment with quality and strategy.

Also controversial today - I believe that the wrong strategy is to have your PMs shipping code - that just introduces another bottleneck that the best engineers will waste their time on.

To be clear, PMs should be coding but they should do this in a playground to iterate, validate, and scope. That code should not go to production.

Everything outside of managing systems, orchestrating AI, and reviewing output becomes a bottleneck.
That's why the other roles that are critical along with these are the systems managers (to reduce bottlenecks) along with a bottleneck you can't replace - customer meeting time.

— THE SYSTEM MANAGERS
Ironically, the people that automate their jobs with AI will always have a job. They become owners of the AI systems - agent managers. We have many examples of these people at ClickUp.

The underlying systems in which we operate are absolutely critical to get right. I think most companies are delusional to think they can iterate on existing systems and compete in this new world.

You must create enough disruption so that old systems are deprecated entirely. If there's any definition for 'AI native' that's what it is.

— THE FRONT-LINERS
In a world that will become saturated with AI communication, the human touch will matter more than anything to customers.

This is a bottleneck that you shouldn't replace - even when agents are high enough quality to do video meetings.

One-on-one meeting time with customers is something that shouldn't be automated. The systems around the meetings should be - so that front-liners spend nearly 100% of their time with customers.

REWARDING 100X IMPACT
In a world where companies are able to do so much more with less, where does that excess money go?
In our case, much of the savings in this new operating model will flow directly back to those that enabled it.

We must reward people that create productivity accordingly. This aligns incentives on both sides. Plus, in a world where your best people create 100x impact, you can't afford to lose them.

You should aim to retain these employees for decades. The context they have and their ability to efficiently orchestrate and review will be nearly impossible to replace.

Compensation bands of today should be thrown out the door. We're introducing $1 million cash/year salary bands with a path available to nearly everyone in the company if they produce 100x impact by creating or managing AI systems.

THE FUTURE
Nearly every company will make changes like these. The ones that do it proactively will define what comes next.

The future is not fewer people. It's different work, new roles, and better rewards for those who embrace it. We're already seeing entirely new roles emerge, like Agent Managers, that didn't exist a year ago.

ClickUp is positioning to lead this shift, not just internally, but for our customers too. I've never been more certain about where we're headed.

[Dan Shipper 📧 @danshipper]

We’ve automated every single thing we can @every with AI agents.

And yet there’s way more human work to do than ever. We’ve gone from 4 -> 30 human employees since GPT-3.

I wrote a report on the structural reasons: how AI makes expert competence cheap, why that drives up demand for experts, and why the dynamic only intensifies as we approach AGI.

After Automation: https://t.co/Lb7SUCduAg

[EWTN News @EWTNews]

“AI can process information quickly, but it cannot replace human intelligence… AI can never replace the unique gift that you are to the world.”
At NCYC 2025 in Indiana, Pope Leo spoke to a stadium full of Gen Z youth and young adults and reminded them that no algorithm can pray, love, or wonder in their place. As the Church prepares to receive his new encyclical on AI, Magnifica Humanitas, this May 25, we remind the young generation of the Holy Father's words, to use tech in a way that helps you grow in holiness—not in a way that replaces your heart, your creativity, or your friendships.

Remember, no machine can replace the unique, unrepeatable gift that you are.