I sat down with Sydney Huang from Human API to explore a completely novel concept—AI agents hiring humans, not the other way around. We dive into how they're solving the last mile problem for AI agents, why data collection is their first focus, and how you can actually get paid for contributing voice data and other tasks. Sydney shares her journey from buying Ethereum in 2017 to building Eclipse (a Solana VM L2 on Ethereum) to now creating an agent-native marketplace. We discuss the challenges of building a two-sided marketplace, the growing demand for AI training data, and why now is the perfect time to build in this space.

KEY POINTS WITH TIMESTAMPS

• [00:00] Introduction to Human API and the concept of AI agents hiring humans

• [02:30] Sydney's journey from buying ETH in 2017 to working in VC to building in crypto full-time

• [04:15] Eclipse explained: Building a Solana VM L2 on Ethereum and the modular blockchain thesis

• [06:45] The last mile problem for AI agents and why human tasks are still needed

• [09:20] How Human API differs from traditional workflow automation tools

• [11:00] Current use cases: Conversational audio data collection for training voice AI

• [14:30] Future expansion into health wearables data and other data types

• [18:45] Why people are willing to work for AI agents and contribute data

• [21:00] Building a better UX than Fiverr and Upwork with reputation systems

• [25:15] The chicken-and-egg challenge of balancing supply and demand

• [28:30] Why now is the perfect time to build in the AI data space

• [31:00] Roadmap: App launch and making the agent experience seamless

• [32:45] How to become a contributor at thehumanapi.com

CONNECT

Human API Website: https://thehumanapi.com

Sydney Huang LinkedIn: https://linkedin.com/in/sydney-huang

Eclipse Website: https://eclipse.xyz

Web3 with Sam Kamani: https://www.linkedin.com/in/samkamani/

Disclaimer

Nothing mentioned in this podcast is investment advice and please do your own research. It would mean a lot if you can leave a review of this podcast on Apple Podcasts or Spotify and share this podcast with a friend.

Be a guest on the podcast or contact us - https://www.web3pod.xyz/

I sat down with Kat from Space and Time to talk about what real institutional adoption actually looks like. While crypto Twitter feels bearish, banks like JP Morgan and Goldman Sachs are hiring entire teams focused on digital assets. Space and Time has already onboarded over 100,000 students in Southeast Asia for verifiable education credentials, shipped a zero-knowledge proof for databases, and is working with major institutions on tokenized assets and compliant stablecoin reward distribution. We dive into AI-powered vibe coding, why surviving the bear market matters more than anything else, and why the next wave of builders will have access to on-chain data like never before.

--- CONNECT ---

Space and Time: https://spaceandtime.io/

https://www.linkedin.com/company/space-and-time-db/

https://discord.com/invite/spaceandtimeDB

Twitter/X - Space and Time: https://twitter.com/SpaceandTimeDB

--- KEY POINTS WITH TIMESTAMPS ---

• [00:00:00] Space and Time has onboarded over 100,000 students in Southeast Asia for verifiable education credentials

• [00:02:00] Major university partnerships expanding in both Southeast Asia and the US

• [00:03:00] Dream Space - AI vibe coding platform allowing non-developers to build apps and smart contracts

• [00:04:00] Institutional adoption is the biggest growth area - stablecoin issuers, tokenized assets, major banks

• [00:06:00] Despite bearish sentiment on crypto Twitter, institutions like JP Morgan, US Bank, Fidelity, and Goldman Sachs are more bullish than ever

• [00:07:00] Banks are hiring entire teams of digital asset specialists, not just single roles

• [00:09:00] 98% of stablecoin market is USDT/USDC, but new categories will emerge as adoption expands

• [00:11:00] Marketing in crypto changes dramatically between bull and bear markets - focus on real value proposition and real customers

• [00:14:00] Space and Time invented a patented zero-knowledge proof specifically for databases, making data computations fast and efficient

• [00:18:00] Nearly $2 trillion of institutional capital waiting on the sidelines to enter crypto over next 2-5 years

Disclaimer

Nothing mentioned in this podcast is investment advice and please do your own research. It would mean a lot if you can leave a review of this podcast on Apple Podcasts or Spotify and share this podcast with a friend.

Be a guest on the podcast or contact us - https://www.web3pod.xyz/

I sat down with Dewey and Igor from Function Space at ETHDenver to discuss how they're building something fundamentally different in prediction markets. They're not creating another venue like Polymarket or Kalshi. Instead, they're building the primitive layer underneath - enabling developers to create numerical range forecasting markets for anything from Tesla's quarterly revenue to Apple's iPhone sales. We explore why they believe prediction markets can become a superset of all financial instruments, the challenges of building in such a competitive space, and why being at the protocol level might be the smartest play. If you're interested in the infrastructure powering the next generation of prediction markets, this conversation reveals what's happening beneath the surface.

• [00:00] Function Space is building the primitive layer for prediction markets, not another venue• [02:00] The team's background from BankSA and their transition into prediction markets• [03:00] Function Space enables numerical range forecasting vs binary yes/no contracts• [06:00] The business model centers on native token demand for market resolution• [09:00] Emerging trends: Pre-ICO TGE markets and yield hedging for DeFi protocols• [13:00] Why building at the protocol level consolidates liquidity better than fragmented venues• [18:00] Prediction markets becoming primitives themselves - like Condo Finance using positions as collateral• [21:00] The challenge of being novel: communicating concepts that don't exist yet• [23:00] Prediction markets divorced from crypto cycles - volumes up even when crypto's down• [26:00] Actively seeking builders and advanced traders for their private trial program

Connect with FunctionSpace:

https://www.functionspace.dev/

https://x.com/functionspaceHQ

https://t.me/+pUEOlfRhHspiNmRl

Disclaimer:

Nothing mentioned in this podcast is investment advice and please do your own research. It would mean a lot if you can leave a review of this podcast on Apple Podcasts or Spotify and share this podcast with a friend.

Be a guest on the podcast or contact us - https://www.web3pod.xyz/

I sat down with Shady from HUMAN.TECH during Consensus Week in Hong Kong. We talked about how he entered Web3 through neuroscience, why HUMAN.TECH is focused on putting humans at the center of technology, and what digital rights should look like in an AI-driven world. This episode goes deep into self custody, decentralized identity, wallet infrastructure, sustainable token economies, and why timing matters so much when building in Web3.

We also explored what it takes to build products that last. Shady shared how HUMAN.TECH thinks about revenue, long-term incentives, and real utility beyond hype. We also discussed AI agents, identity delegation, and why founders need to answer one simple question: why does what they are building actually matter for the world?

Key points

• Intro from Consensus Week in Hong Kong and welcome to Shady from HUMAN.TECH
  

• How Shady entered Web3 through a neuroscience data-sharing problem
  

• Discovering IPFS and the path into decentralization
  

• Why Holonym evolved and how HUMAN.TECH was born
  

• Building technology with digital rights embedded by design
  

• Why sustainability is still one of Web3’s biggest problems
  

• The gap between crypto hype and real-world utility
  

• How HUMAN.TECH plans to monetize identity proofs and wallet infrastructure
  

• Creating sustainable economic loops through node staking and network demand
  

• Why self custody is the guiding star for HUMAN.TECH
  

• How AI changes the conversation around ownership, identity, and private keys
  

• A future where AI agents may need delegated human identity
  

• Why timing matters in startups and how to tell if a market is ready
  

• Why crypto is still early, especially for self custody
  

• The next 12 months for HUMAN.TECH and the upcoming token launch
  

• What developers can build today with HUMAN.TECH and WAP
  

• The vision for easier multichain wallet experiences
  

• The one question every Web3 founder should be asked
  

Connect

https://www.linkedin.com/in/shadyeldamaty/

https://human.tech/

https://x.com/humntech

https://linktr.ee/human.tech

Disclaimer

Nothing mentioned in this podcast is investment advice and please do your own research.

It would mean a lot if you can leave a review of this podcast on ApplePodcasts or Spotify and share this podcast with a friend.

Be a guest on the podcast or contact us - https://www.web3pod.xyz/

In this episode, I sit down with Shresth Agrawal, co-founder of Pod Network, to unpack why the world needs yet another Layer 1.

We go deep into MEV, front-running, and why today’s blockchain markets are still unfair. Shresth explains how Pod is building a purpose-built L1 designed for high-performance, MEV-free markets. We break down how auctions replace traditional transaction ordering, how Pod can process 300,000 orders per second, and why sub-second settlement changes everything.

We also talk about product-market fit in Web3. Are payments and markets the only real use cases? What can founders learn from Ethereum, Hyperliquid, and newer L1s? And what’s Pod’s go-to-market plan?

If you care about fair markets, decentralized finance, or the future of on-chain trading, this episode is for you.

🔑 Key Learnings (with timestamps)

00:57 – Shresth’s crypto journey. From Bitcoin whitepaper to building consensus systems.

02:01 – Why consensus innovation still matters in 2026.

04:23 – What is Pod Network? A purpose-built L1 for MEV-free markets.

06:16 – What is MEV? Simple explanation with real trading examples.

11:32 – How Pod removes ordering where it doesn’t matter.

14:36 – 300,000 orders per second. Sub-second confirmations explained.

16:51 – Why Pod focused only on markets. The power of niche L1s.

18:21 – Trade-offs: Less general-purpose, more performance.

22:36 – Go-to-market strategy for a new L1.

24:25 – Users vs builders: The real growth engine.

27:21 – The biggest ask: Early user feedback.

28:20 – Do only payments and markets have real product-market fit in Web3?

32:18 – Why instant settlement will disrupt traditional finance.

Connect with POD Network

https://pod.network/

https://x.com/poddotnetwork

https://discord.com/invite/ZTFERarfnm

⚠️ Disclaimer

Nothing mentioned in this podcast is investment advice and please do your own research.

It would mean a lot if you can leave a review of this podcast on ApplePodcasts or Spotify and share this podcast with a friend.

Be a guest on the podcast or contact us - https://www.web3pod.xyz/

Prediction markets are having a big moment. Platforms like Polymarket and Kalshi have brought them into the spotlight. But most prediction markets still follow a simple format: a binary outcome. Yes or no. Win or lose.

In this episode, I sit down with Philip from Trendle.fi to explore a new approach. What if prediction markets were not just about outcomes? What if you could actually trade attention around topics, trends, and people?

Philip explains how Trendle measures conversations across platforms like Reddit, YouTube, and X to create an attention index. Traders can then long or short that index depending on whether they think the topic will gain or lose traction.

We also talk about how the 2024 U.S. elections boosted prediction markets, why peer-to-peer models may outperform traditional bookmakers, and why the next wave of innovation will come from new market mechanics rather than copying existing models.

If you’re interested in Web3 innovation, market design, or the future of prediction markets, this episode is for you.

Key Learnings

Prediction markets are entering the mainstreamPlatforms like Polymarket and Kalshi have introduced thousands of users to prediction markets, especially during major political events like the 2024 U.S. elections.

Prediction markets have existed for decadesBetting on future outcomes is not new. From horse racing to sports betting, humans have always tried to predict the future and place bets on it.

Peer-to-peer markets may outperform bookmakersTraditional bookmakers take on risk when setting odds. Peer-to-peer markets allow users to trade directly with each other, often resulting in better pricing and reduced risk for the platform.

Trendle introduces a new concept: the attention indexInstead of predicting outcomes, Trendle measures how much attention a topic receives online and turns that attention into a tradable asset.

Social media data powers the attention indexTrendle gathers data from Reddit, YouTube, and X to measure how often people discuss specific topics and updates the index frequently.

Attention itself can become a marketUsers can long or short topics depending on whether they think the conversation around them will grow or fade.

AI agents are already trading prediction marketsSome traders are building bots that detect price discrepancies across platforms and use arbitrage strategies.

Trendle’s strategy starts with crypto communitiesThe initial go-to-market strategy focuses on crypto traders and communities before expanding to broader cultural topics like celebrities and major trends.

Education will be a major challengeBecause the attention index is a new concept, helping users understand how it works will be a key focus.

Trendle is currently fundraising and exploring partnershipsThe team is looking to collaborate with communities, builders, and investors as they scale the platform.

Connect with Trendle

https://trendle.fi/

https://x.com/trendlefi

Disclaimer

Nothing mentioned in this podcast is investment advice and please do your own research.

Finally, it would mean a lot if you can leave a review of this podcast on ApplePodcasts or Spotify and share this podcast with a friend.

Be a guest on the podcast or contact us - https://www.web3pod.xyz/

I recorded this episode live in Hong Kong with Wish Wu, Co-Founder and CEO of Pharos Network.

We dive deep into what it really takes to build next-generation blockchain infrastructure.

Pharos is an EVM-compatible Layer 1 hitting 20,000 TPS on testnet. But speed is not the real story. The real story is their focus on connecting Web2 and Web3. Not just users. But capital. Assets. Institutions.

Wish shares his journey from building AntChain at Ant Group to launching Pharos. We talk about tokenizing real-world assets, institutional adoption, product-market fit, and why new Layer 1s must stop copying Ethereum.

If you're a founder building in Web3, this episode is essential listening.

Key Learnings

• Why Hong Kong is regaining momentum as a crypto hub.

• What Pharos Network is building and why 20K TPS matters.

• Wish’s background at Ant Group and building AntChain at scale.

• Tokenizing new energy assets and institutional funds.

• Why most new Layer 1s fail without product-market fit.

• The rise of purpose-built chains and niche-focused infrastructure.

• Why speculative crypto alone cannot sustain adoption.

• The vision for Pharos over the next five years.

• Launching a VC fund and incubator to grow the ecosystem.

• Fundraising advice: Stop copying. Find real product-market fit.

Connect

https://www.linkedin.com/in/wishlonger/

https://www.pharos.xyz/

https://www.linkedin.com/company/pharosnetwork/

https://x.com/pharos_network

Disclaimer

Nothing mentioned in this podcast is investment advice and please do your own research.

It would mean a lot if you can leave a review of this podcast on Apple Podcasts or Spotify and share this podcast with a friend.

Be a guest on the podcast or contact us - https://www.web3pod.xyz/