Evgeniy Valyaev

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[Evgeniy Valyaev @_valyay_]

A handy checklist to help you decide whether MCP makes sense for your product

[Evil Martians @evilmartians]

MCPs are the new chatbot. Every product has one, even when they don't need it.

Bloomberry analyzed 1,412 MCP servers. Roughly half of those companies have no public API at all.

But shipping an MCP without stable external-facing operations means the interface has nothing to stand on.

This framework by @_valyay_ invites you to answer 8 questions before deciding if an MCP is the right choice for you:

[Evil Martians @evilmartians]

Not every product needs an MCP, and it's also the most expensive option to maintain.

In this post, @_valyay_ presents a framework to decide between direct API calls, CLI, Skills, and an MCP before you pull the lever. It includes what to trust, what it'll cost you, and the soft spots worth watching: https://t.co/JOnAnGsrNU

[Evgeniy Valyaev @_valyay_]

MCP servers are popping up everywhere, and it’s not always obvious when you actually need one.

That’s why I wrote this article. It’s based on hands-on experience: building my own MCP server and working with MCP servers on client projects.

[Evil Martians @evilmartians]

Not every product needs an MCP, and it's also the most expensive option to maintain.

In this post, @_valyay_ presents a framework to decide between direct API calls, CLI, Skills, and an MCP before you pull the lever. It includes what to trust, what it'll cost you, and the soft spots worth watching: https://t.co/JOnAnGsrNU

[Evgeniy Valyaev @_valyay_]

Building agents in n8n? You've now got more tools to debug and inspect them in AgentPrism. Every run becomes a tree you can click through: each LLM call, token count, and retry.
https://t.co/O0VbUpML3L

[Kirill Yakovenko @KSYakovenko]

Just shipped: https://t.co/FxqGGt5qza integration for AgentPrism, our open-source AI observability project.

Better than n8n's built-in trace viz? We store logs forever, or at least until we run out of space. Beyond that, no clue.

Closed beta: https://t.co/7kvv9ILEZM
#n8n

[Evgeniy Valyaev @_valyay_]

@psd_coder Well, since it's a more powerful model, you solve the problem faster and therefore spend fewer tokens

But we know that there will always be more tasks and problems to solve 😄

[Evil Martians @evilmartians]

Waking up to these types of messages is the best way to start the week.

Our backend engineer, Julia Egorova, reduced our client's subscriptions page loading time by 94%!

This is what working with Evil Martians looks like.

[Camila Mirabal @CamiMirabalMktg]

If you're launching a new product, there really just 3 types of content you need to produce:

1. Pre-launch/hype content. Everything that makes your audience excited about your product. E.g., reaction videos of people using your tool, screenshots of your UI.

2. Solution content. This is where you tell your audience how your product solves their problems. E.g., Demos, user wins, or reviews.

3. Connection content. This is where you make your audience build an emotional connection with you. E.g., your founder story, BTS/making of content, and stories on why you chose to solve this problem.

[Pavel Grinchenko @psd_coder]

TIL iterator helpers have been in Baseline since 2025, not 2026, as I thought. This means it’s time to start using them if they fit your browser support list.

Why should we even think about them? I measured two simple examples: 100k items, with some filtering, mapping, and taking just 1k of the final results.

The measurements give us these figures: iterators are ~15x faster (70.85 µs vs. 1.08 ms) and consume ~4x less memory (~270 KB vs. ~1.05 MB).

This is because iterators are lazy, they never build intermediate arrays and they stop early. You don’t need them in every case, of course, but in similar cases, the win can be huge.

[Evgeniy Valyaev @_valyay_]

Linear transforms to GitHub, but I don't mind 😄

[Linear @linear]

Code review, but faster.

Introducing Diffs. A new way to review PRs, directly inside Linear.

• Realtime updates
• Guided reviews with Al (beta)
• Focused notifications
• Iterate with coding agents
• Threaded comments

[Evgeniy Valyaev @_valyay_]

Just don't close your laptop lid and use the $20 for more queries

[sudox @kmcnam1]

jfc....

[Evgeniy Valyaev @_valyay_]

We don't see such a huge increase because reality is far more complex than even the most sophisticated synthetic tests and models

[Karri Saarinen @karrisaarinen]

We keep hearing about 10x or 100x productivity gains in engineering and knowledge work.

But outside the model labs, I haven’t seen the corresponding 10-100x revenue growth across the market or increase in quality.

So where is the productivity going?

[Evgeniy Valyaev @_valyay_]

Has AI reached its peak?

https://t.co/SIp7qeWSQK

[Polymarket @Polymarket]

JUST IN: Uber’s COO says heavy AI spending is getting harder to justify, as higher token usage fails to show a clear payoff in consumer features.

[Pavel Grinchenko @psd_coder]

I needed a tool to compare two versions of the same font, just to make sure my changes in the source file didn’t break anything and that the font still looked the same. I built it quickly with an agent and solved my issue.

This is where LLMs shine brightest. Before, building a tool for a single use was expensive. Now it’s cheap. You can prototype it, use it once, and then forget about it with no regret!

[Evgeniy Valyaev @_valyay_]

https://t.co/8AYFmUL1dZ

[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.

[Evgeniy Valyaev @_valyay_]

Now that’s what I call self-deprecating humor

[Evgeniy Valyaev @_valyay_]

I've already tried handoff and I liked it. I'll definitely have to check out the new version

[Matt Pocock @mattpocockuk]

You asked for it, so here it is: a deep-dive on my new /handoff skill.

It's an alternative to /compact that gives you WAY more flexibility with your context window.

- Think of an idea, handoff to another agent to implement
- Grill, handoff to prototype, handoff BACK

Enjoy:

[@[email protected] @sitnikcode]

Supply chain attacks can’t be solved with one silver bullet. They need a systemic approach.

For every dev layer (not just npm, but CI, Docker, and your editor) ask 4 questions:

1. How can we reduce dependencies?
2. Isolation
3. Update control
4. Review

Thread ↓

[Evgeniy Valyaev @_valyay_]

@skiba_dmitry From my experience, anything that gets pushed "for later" either never happens, or ends up hurting a lot when it finally catches up with you 😄
With AI, it hurts even more

[Evgeniy Valyaev @_valyay_]

AI didn't remove complexity from software development.

It moved it.

Before AI, if you wanted to build something, you had to study the topic first. You had to understand the domain, the constraints, the architecture, and only then slowly turn that understanding into code.

[Evgeniy Valyaev @_valyay_]

@kvixiossa Then you're doing everything right!

[Evgeniy Valyaev @_valyay_]

Anthropic adding Karpathy to the team

[Andrej Karpathy @karpathy]

Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited to join the team here and get back to R&amp;D. I remain deeply passionate about education and plan to resume my work on it in time.