Get live statistics and analysis of DCo's profile on X / Twitter

Investments and Research. Analysis by humans, for fellow humans.

325 following13k followers

The Analyst

DCo is a data-first investor-researcher who translates complex crypto and AI trends into clear, usable analysis for builders and investors. Their work blends deep research (dashboards, lists, long reads) with practical synthesis that helps people make decisions. Expect threads, tools, and the occasional spreadsheet love story.

Impressions
0
$0
Likes
0
0%
Retweets
0
0%
Replies
0
0%
Bookmarks
0
0%

You color-code spreadsheets for fun, and your idea of a wild night is turning a chaotic dataset into a neat CSV, congratulations, you’ve peaked as an adult.

Built and launched the Crypto Funding Dashboard (10k+ funding rounds, 5k+ investors, 15 years), turning scattered capital-flow data into a go-to resource for founders, VCs, and researchers.

To turn noisy markets and fragmented research into rigorous, shareable insights that empower better decisions in crypto and AI, bridging raw data and human judgment so others can build, invest, and debate with confidence.

Values evidence over hype, clarity over buzzwords, and reproducible research over hot takes. Believes that standardized building blocks (protocols, data, tooling) scale industries, and that well-curated information is the infrastructure of smarter markets.

Exceptional at collecting, organizing, and synthesizing large datasets into actionable stories and tools; credible, research-heavy voice that builds trust; proven ability to ship products (dashboards, lists) that become reference points.

Can lean into dense analysis that intimidates casual scrollers; occasionally prioritizes depth over snackable shareability, which can limit viral reach; may underinvest in personality-led engagement.

Keep producing deep threads and dashboards, but package more bite-sized entry points for X: 1) Post a 3-tweet TL;DR before every long thread; 2) Share one striking chart with a one-line insight and a link to the full analysis; 3) Host regular X Spaces or AMAs to turn research into real-time conversations; 4) Pin the Funding Dashboard and Sentient AI List threads, and tag notable contributors to spark shares; 5) Use consistent visual templates and alt text so charts are retweet-ready, marry rigor with a few snackable hooks to grow faster.

Fun fact: DCo launched the Crypto Funding Dashboard tracking 10,000+ funding rounds and 5,000+ investors across 15 years. Their Sentient AI List and long-form pieces have repeatedly cleared 80k, 140k views, showing their work reaches both niche researchers and broader audiences.

Top tweets of DCo

Sentient AI List 🤖 🌐 We're organising agents on sentient.market into these key sections. Give us a shout if we missed you or put you in the wrong category.

83k

“If you want real decentralisation, you don’t get a website.” @AndreCronjeTech on the UX tradeoff, Ethereum’s stagnation, and why composability is dead. This one’s not for the tourists. Timestamps — 00:00 Introduction 02:05 Andre's Life in the last 3/4 years 09:12 Changing preference from Decentralization to UX 15:28 Innovation Stagnation in DeFi and Funding Challenges 22:47 Decentralization vs. User Experience 29:16 The Future of Ethereum and Layer 2 Solutions 39:03 Scaling EVM with Database Innovations 41:47 New DeFi Primitives 44:39 Advice for Builders in the Crypto Space

87k

Introducing the Solana Agent Kit dashboard on sentient.market! Powered by @thesendcoin ($SEND), the open-source toolkit lets agents seamlessly perform on-chain actions through @solana protocol integrations. 19 protocols integrated, 500+ GitHub stars, 240+ forks. Link in bio.

63k

Introducing the @aixbt_agent Performance Tracker One of the most fascinating experiments in crypto is happening right now: An AI agent is autonomously analysing markets, spotting trends, and making calls. Today we're launching a dashboard to track its every move. 🧵

17k

A brief look at the numbers behind @HyperliquidX through the lens of revenue The volume supported by decentralised perpetual futures products has steadily grown from ~$20 billion a week to over $100 billion in the week of May 19, 2025. Most of this growth originates from Hyperliquid, with its weekly volume closing in on ~$80 billion. Hyperliquid supports more than 75% of the perp DEX volume as of writing. Here's a different way to think of it. Hyperliquid is the first product in a while that is eating into the market share of entrenched incumbents. Hyperliquid has half of ByBit’s open interest and one-third of Binance’s. One of Hyperliquid’s key innovations is its HLP (Hyperliquidity Provider) vault. It democratises market-making by allowing any user to provide liquidity via a protocol vault and earns fees from trading and liquidations, which are shared with liquidity providers. The fee generated by the platform is split between users who provided liquidity to the HLP vault and the Assistance Fund that buys back HYPE tokens. As of May 26, 2025, 23 million+ HYPE worth $877 million have been bought back. And that fee has added up over the past few months. Hyperliquid currently earns ~$2.5 million in daily revenue, which amounts to ~$900 million annually. The current market cap is at $12.2 billion, making the price-to-revenue multiple 13.3. This is cheaper than other derivatives venues like dYdX and Synthetix. Robinhood, the retail trading platform in the US, trades at a PS (price-to-sales) multiple of 17. Coinbase trades at a PS multiple of ~10. We did some basic math around how Hyperliquid's product compares against the per businesses of Binance, Bybit and Coinbase internally. In Q1 of 2025, Binance supported $2 trillion in spot volume and $6 trillion in futures volume. We assume the median spot and futures fees to be 0.05% and 0.028%, respectively. The approximate revenue from spot and futures would be $2.68 billion ($1 billion in spot and $1.68 billion in futures). This puts Binance’s annual run rate at $10.7 billion. The total market cap of BNB is $100 billion. Not all of Binance’s value is accrued to BNB. Assuming a 1.5 to 3 times premium on the total value of Binance, the price to sales for Binance would be at ~15 and 30. Binance has other sources of revenue that would be difficult to estimate. If Binance is the benchmark, at ~13 P/S multiple, Hyperliquid seems to be fairly valued. The fixed costs of traditional companies are generally higher than those of blockchain-based companies. This is because blockchain protocols outsource their infrastructure to a distributed network of validators and operate with minimal staff and almost no physical footprint. Their cost-to-income ratios can be an order of magnitude lower than those of traditional financial institutions. So if Hyperliquid has to handle 10 times more volume or Aave has to support 10 times more TVL, they don’t need to hire more employees or open new branches. Scaling blockchain businesses doesn’t increase their costs proportionally. This means the bottom line of blockchain companies is higher than that of traditional companies. Thus, if both Robinhood and Hyperliquid were trading at 13X, Hyperliquid would be more attractive because it could pass on more of the revenue towards the token than Robinhood. But note that the HYPE token has unlocks ahead. The calculation is based on circulating supply, and not the FDV. $HYPE currently trades at a market cap of ~$11 billion with a ~4% market share of the perps market volume. The current P/S multiple is ~13.3.. In 2024, the total perp volume (DEX + CEX) was $60 trillion. We assume a 25% growth for 2025, so the total volume will be $75 trillion. The following table shows the HYPE market cap with different market shares and P/S multiples. So if HYPE captures 10% of the total perps market, at 12 P/S, the market cap would be $22.5 billion—twice the current market cap. It has been a while since entrenched incumbents have come to question the way HYPE has managed. The last time such a shift occurred was when OpenSea gave way to Blur. Or when Binance aggregated the market for spot assets during the ICO boom. We see Hyperliquid’s dominant place within the perpetuals market being interesting and continue to keep an eye on the ecosystem there. If you are a founder building on Hyperliquid, we’d like to speak. Slide into the DMs! Disclaimer —Dco holds a small position in Hyperliquid within its treasury.

54k

The buzz around the @sendaifun Crypto x AI Hackathon is impossible to ignore. As part of the judging panel for the hackathon, we witnessed firsthand the unparalleled innovation happening at the intersection of crypto and AI. Here are 10 projects to keep an eye on 🤖 🧵

19k

The VIRTUAL Flywheel @virtuals_io provides the infrastructure for creating and deploying AI agents on @Base. When a new agent goes live, the protocol mints one billion tokens dedicated to that agent, paired with $VIRTUAL tokens in liquidity pools that establish market pricing. Every agent token must be paired with $VIRTUAL in liquidity pools, making it the base currency for the entire ecosystem. To interact with any agent on Virtuals, users must first acquire $VIRTUAL tokens, similar to how ETH functions on Ethereum. This creates consistent demand for $VIRTUAL while aligning the interests of both agent creators and token holders. When agents provide services and get paid, these earnings flow back to the agent holders. As more successful agents generate more activity, the value of $VIRTUAL could potentially increase through higher usage and token burns.

10k

Most engaged tweets of DCo

Sentient AI List 🤖 🌐 We're organising agents on sentient.market into these key sections. Give us a shout if we missed you or put you in the wrong category.

83k

Can crypto help solve the walled garden challenges around data for AI products? The biggest bottleneck for large language models (LLMs) isn’t compute; it’s data. GPT-5 is expected to require up to 75 trillion words for training. Or eight times the amount needed to build GPT-4. The rate of data consumption by AI models far exceeds that of new content production. With most of the public internet already scraped, indexed, and used in building GPT-4, where will the additional data come from? Over the last few quarters, open platforms such as Reddit and Stack Overflow have begun charging millions for access to their data. Which in turn, makes it difficult for smaller AI teams to compete with the giants. Creators who’ve contributed to such platforms are not compensated when these companies enter data licensing agreements. The feedback loop strengthens as LLMs continue to develop, exacerbating these issues. LLMs grow - > value of data increases -> platforms close up and charge more. This leads to a future where the best LLMs will be highly centralized and consolidated among the largest, most well-resourced entities. Users and creators on the internet become more of a product than they have ever been. Crypto might just provide some solutions to these problems. Teams like @Wyndlabs_ai, that’s building @getgrass_io and @getmasafi are tackling these problems head on by democratizing access to high quality data and rewarding individuals more equitably In our latest article by @shloked_ , we explore how walled gardens on the web are being broken down by a new generation of Web3 primitives. Read on for a brief on how LLMs evolve, why emerging applications need more data and the role crypto-native rails are playing in building a fair playing ground for founders. DMs open if you are building within the sector :) Link: decentralised.co/p/the-data-mus…

337k

Introducing the Solana Agent Kit dashboard on sentient.market! Powered by @thesendcoin ($SEND), the open-source toolkit lets agents seamlessly perform on-chain actions through @solana protocol integrations. 19 protocols integrated, 500+ GitHub stars, 240+ forks. Link in bio.

63k

Massive pension funds move billions in stocks daily using Goldman’s dark pools. Hidden from prying eyes. But there's a catch — Goldman itself can see and potentially front-run every trade. This is the digital world's paradox: We need privacy, but current solutions force us to trust someone with our secrets. We have tried to solve it. We tried building digital vaults (TEEs) right into computer chips. Sounds great until you realise hackers can "hear" secrets by listening to the chip's power usage - like a safecracker with a stethoscope. AMD's latest vault was cracked for just $10. We tried using zero-knowledge proofs. Mathematical magic that proves you know a secret without revealing it. Perfect for verifying things, but useless when multiple parties need to actively work with encrypted data. Then came fully homomorphic encryption (FHE). It lets computers work directly with encrypted data - amazing in theory. The problem? It's like driving a car through molasses. A simple calculation takes seconds. @ArciumHQ aims to solve the puzzle differently. Instead of making single computers ultra-secure or accepting massive slowdowns, they created a network where security emerges from collaboration. Your data is split into meaningless fragments across multiple computers. As long as just ONE computer stays honest, your secrets remain safe. Even if 99/100 try to peek. And it is fast. By using mathematical shortcuts and parallel processing, they made privacy-preserving computation 10,000x faster than FHE. What does this mean in practice? • DeFi can execute trades privately, killing front-running • Hospitals can train AI on shared patient data without exposing records • Companies can analyse joint datasets while keeping proprietary info secret If you are a developer, you can add this enterprise-grade privacy with a single line of code. No PhD in cryptography required. This has the potential to be the foundation for a truly private digital economy. One where we can work with sensitive data without exposing it. Where "trust" comes from mathematics, not promises. @desh_saurabh dove deep into Arcium to understand how encrypted computing is getting practical.

70k

People with Analyst archetype

The Analyst
@ahboyash

intern @mementoresearch @playkamiapp

3k following33k followers
The Analyst
@ZeusRWA

Breaking down RWA’s, tokenization & stablecoins. @RWAFoundation_ @PreStocks

5k following25k followers
The Analyst
@TheiaResearch

everything is DCF

2k following10k followers
The Analyst
@LoonieDoctor

A Canadian physician blogger helping Canadian physicians and other high income professionals improve their financial health while not boring them to death.

94 following1k followers
The Analyst
@KobeissiLetter

Official X account for The Kobeissi Letter, an industry leading commentary on the global capital markets. Email us: support@thekobeissiletter.com

610 following1M followers
The Analyst
@Kalshi

Trade on anything: politics, sports, entertainment, crypto, weather, and so much more. For sports: @KalshiSports For culture: @Kalshi_Culture

1k following353k followers
The Analyst
@Husslin_

“bet more” // quant fund founder // ex tradfi MM, ex investment banker // microstructure+hft nerd // Saudi, Chicago // @UChicagoAlumni

2k following73k followers
The Analyst
@CarlWeische

Founder acceleratedagency.com

200 following38k followers
The Analyst
@CRInvestor

Combining strengths of Fundamental & Technical analysis, I provide trade ideas & market commentary to investors around the world. Not Investment Advice!

779 following18k followers
The Analyst
@aakashgupta

✍️ product-growth.com: $72K/m 💼 aibyaakash.com: $39K/m 🤝 landpmjob.com: $37K/m 🎙️ youtube.com/@growproduct: $30K/m

774 following208k followers
The Analyst
@iamgdsa

writing daily @wesocialgrowth tracking+analytics: shortimize.com creatornets: findmecreators.com + 4 apps + @viraltoktracker @appstoretracker w @jean__gatt ⬇️

643 following32k followers
The Analyst
@dvassallo

Bad for the economy.

2k following199k followers

Explore Related Archetypes

If you enjoy the analyst profiles, you might also like these personality types:

Supercharge your 𝕏 game,
Grow with SuperX!

Get Started for Free