Anıl Şen

building @Bluearf_ | css & econ @kocuniversity

[Anıl Şen @_anil_sen]

What is even more troubling is the psychological pressure this rhetoric creates. Outputs that are often little more than polished demos, and still far from sector-specific, production-grade systems, are being presented as if they are replacing deep professional expertise altogether. That puts real pressure on professionals and managers, making people feel increasingly inadequate at every step, as if they are already falling behind. In reality, the marginal productivity gains of many of these platforms per employee are still extremely limited. Yet, especially in combination with the social-media incentive to chase attention and virality, an entirely different picture is being manufactured. Yes, with the rise of Chatgpt, productivity did increase to a certain extent across many white-collar sectors. But over the last year, the pace of that productivity growth has slowed significantly. Whether people want to admit it or not, the revolutionary leap that investors were hoping for is, at least for now, simply not here.

[Anıl Şen @_anil_sen]

People building and selling no-code platforms are obviously incentivized to argue that coding experience is unnecessary, or even a disadvantage. That is not a neutral analysis; it is a sales narrative. Turning “not knowing how to code” into some kind of entrepreneurial virtue is convenient for their business model, but the argument itself is weak. Coding knowledge does not make founders worse at product, marketing, or problem-solving. It usually gives them more leverage, not less. So this position may be commercially rational, but it is intellectually dishonest, and ethically it is misleading.

[a16z @a16z]

"Not having a coding experience is becoming an advantage."

Replit CEO Amjad Masad:

"You don't need any development experience. You need grit. You need to be a fast learner."

"If you're a good gamer, if you can jump in a game and figure it out really quickly, you're really good at this."

"Coders get lost in the details."

"Product people, people who are focused on solving a problem, on making money, they're going to be focused on marketing, they're going to be focused on user interface, they're going to be focused on all the right things."

"I think this year it's gonna flip, and I think not having a coding background is gonna be more advantageous for the entrepreneur."

@amasad with @jackneel

[Bluearf @bluearf_]

Cumhuriyetimizin Kurucusu, Türk Milletinin Ulu Önderi Gazi Mustafa Kemal Atatürk’ü saygı, sevgi ve minnetle anıyoruz.

Her an senin izindeyiz. İlelebet.

[Anıl Şen @_anil_sen]

@benhylak Designing a UI that everyone can use is already hard — and this one is an extremely difficult problem.
If you think this design is garbage, then go ahead and make a better one, even just as a sketch, and let’s see it

[Anıl Şen @_anil_sen]

@Yesterday_work_ First it was the ‘bla bla is dead’ posts, now it’s engagement farming — a serious problem that’s not just annoying, but toxic.

[Anıl Şen @_anil_sen]

In the coming years, the key differentiator for AI startups will not be the ‘AI’ label, but the strength of their data infrastructures.

Paul Graham’s metaphor of “running downstairs or upstairs” is a powerful analogy for today. Many AI startups are choosing the fastest route—running downstairs. In a time when technology is changing at breakneck speed, this strategy may seem reasonable at first glance.

However, the real challenge emerges for AI startups building products in verticals such as sustainability, finance, or real estate: at the core, these companies need robust data infrastructures. Without one, startups might generate some visible value in the short term but eventually fade away. Building a solid, domain-specific data infrastructure is by far the hardest and most critical part of the game.

Without it, you simply cannot feed your models sustainably. And if you start with no data, or highly fragmented, heterogeneous data, building and operating the infrastructure to bring it into a usable structure can cost tens of times more than the initial investment.

This is why the crucial, often overlooked truth is: @bluearf_ chooses to run upstairs. We have built—and continue to build—a powerful big data infrastructure. This is the first thing we emphasize to investors, partners, and all stakeholders. Because in the future, the AI startups that endure will not be the ones merely training models, but those capable of building their own data ecosystems.

[Y Combinator @ycombinator]

Paul Graham on why startups should deliberately choose hard problems:

[Anıl Şen @_anil_sen]

Our resources are limited, our time is short, and our needs are endless. The path to achieving the best lies not in acting alone, but in the power of moving together.

Sustainability is a vast field that spans hundreds of disciplines, thousands of data points, and tens of thousands of integrations. No single company or institution can shoulder this burden alone. Real transformation is only possible when diverse stakeholders combine their expertise and unite around a common purpose.

This is precisely why today we are introducing the Bluearf Ecosystem.

With the Bluearf Ecosystem, @bluearf_ is no longer just a platform; it becomes an infrastructure where all sustainability stakeholders can come together to co-create solutions to shared challenges. Within the ecosystem, Bluearf will serve as the platform and network provider, while corporate professionals, NGOs, consultants, freelancers, startups, and universities contribute their expertise and drive collective impact. Our goal is to transform individual efforts into collective strength, overcome challenges together, and rise side by side.

In the coming weeks, we will be introducing each of the programs within our ecosystem one by one—stay tuned!

👉 Be part of the ecosystem: fill out the form below and join us:
https://t.co/XSVAZeSd5Q

[Anıl Şen @_anil_sen]

The terms “AI agent” and “AI-powered systems” have largely shifted from being technical descriptors to marketing buzzwords. The logic is simple: flashy terms are assumed to carry weight with investors and customers. Today, many traditional B2B platforms brand themselves as “AI-powered,” and some go even further — claiming to use agentic frameworks or even quantum technology.

Yet, back in early 2021, AI was still a term people approached with caution. Now, it has become a label everyone uses freely — so freely that it has almost lost its meaning. The biggest losers in this shift are the companies that truly train models, perform fine-tuning, and deliver measurable value. In this “false reality,” these companies are finding it increasingly difficult to stand out.

A large portion of market players lack the knowledge and vision to identify high-potential companies. This has become the single largest barrier for genuine AI companies, AI agent–focused startups, and quantum tech innovators alike. In such an environment, we are rapidly losing our innovation potential — a potential already constrained by limited resources. And this loss doesn’t just hurt those companies; it jeopardizes the future of the entire ecosystem.

[@levelsio @levelsio]

If I hear people talk about "AI agents" these days it's generally a red flag and I know they're non-technical ppl reading AI news but not actually shipping anything

Not cause I don't believe in AI agents but it's such a marketing term with no real meaning at this point

[Anıl Şen @_anil_sen]

LLMs have changed our lives in many ways, but this technology could transform our lives from the ground up — that’s how critical it is.

[Dr Singularity @Dr_Singularity]

Genie 3 is probably the most advanced technology humanity has right now, yet over 99% of the world's population has no idea it exists, or how it could change the world.

[Logan Kilpatrick @OfficialLoganK]

Momentum is a crazy self fulfilling prophecy

[Bluearf @bluearf_]

https://t.co/YEVMZt87si

[Revelio Labs @RevelioLabs]

Digital freelance platforms have promised to revolutionize labor markets for years! Has their moment finally come!?

https://t.co/mLm2KFpDKX
#gigwork #freelance #workforce #BigData

[Frontiers - Physics @FrontPhysics]

A Twitter-Based Economic Policy Uncertainty Index: Expert Opinion and Financial Market Dynamics in an Emerging Market Economy https://t.co/UJEXF5wzQt #Physics

[Merih Angin @MerihAngin]

Proud advisor moment: my students Beyza Arslan & Anıl Şen @kocuniversity ranked the 2nd in the Scientific and Technological Research Council of Turkey’s 2242- University Students Research Project Competitions (Education category). Looking forward to the award ceremony in 2 weeks!