The Fintech Blueprint

In this episode, Lex chats with Simon Taylor, who heads up market development at Tempo, the payments-native blockchain built by Stripe as a high-performance settlement layer for stablecoins and tokenized money. Simon is also the founder of Fintech Brain Food, one of the sector's most widely read newsletters. They discuss why there is no Fedwire for the internet, and why the next wave of on-chain volume is coming from enterprise money movers like Deel rather than crypto-native builders. Simon explains why tokenized deposits, stablecoins and TradFi settlement will converge on a single chain, why agentic commerce is still stuck in its WAP-phone era, and how the Machine Payments Protocol is being designed as an IETF-grade standard that can settle across Tempo, Stripe or any card network.
NOTABLE DISCUSSION POINTS:
The AI productivity gap is an operating-model gap, not a tooling gap. MIT found nine in ten companies get zero productivity gain from AI, while Ramp’s own data shows the heaviest users generate 2x higher revenue on 40% less capital. What separates them is four ingredients: AI evals as a cultural default, a shared library of skills (Ramp has 350+), non-engineers shipping production code (12% of Ramp’s human-initiated PRs), and treating AI fluency as the primary staff learning curve.
Agentic commerce is in its WAP-phone era. Nobody is actually paying for things with agents at any scale - Walmart’s ChatGPT checkout converts worse than its dotcom, Target has told customers they are 100% liable for anything an agent buys, and Walmart and Amazon block third-party agents outright as fraud. The real volume is in B2B finance teams automating PDF-invoice-to-payment flows through Ramp and Brex, which is where Machine Payments Protocol and x402 will first find product-market fit.
On-chain cash settlement is less than 0.1% done, and Tempo is being positioned as the missing Fedwire for the internet. The pitch is not a new L1 competing on TPS benchmarks - it is a settlement layer designed by payments veterans who understand that payments are all edge cases, with permissionless issuance combined with opt-in receive policies (TIP-20 upgrades on ERC-20, block/allow lists, embedded compliance) that let enterprises finally clear their RFP checklist.
TOPICS
Fintech, Stablecoins, Tokenization, DigitalAssets, Payments, Settlement, RWA, DeFi, TradFi, CapitalMarkets, AgenticCommerce, AgenticPayments, AIAgents, MachinePayments, Ethereum, Canton, Blockchain, Web3, Tempo, Stripe, Anthropic, Ramp, Brex, Deel

ABOUT THE FINTECH BLUEPRINT
🔥Subscribe to the Fintech Blueprint newsletter to stay at the forefront of Fintech and DeFi: https://bit.ly/3hyhlC2
🤝 Partner with Fintech Blueprint through sponsorships: https://bit.ly/3UZllsV
👉 Twitter: https://twitter.com/LexSokolin

TIMESTAMPS
0’57: How do you ground-truth the digital world: Why AI ultimately runs on a digital asset substrate
5’46: The two-speed transformation: Why customer-facing tech is competitive and back-end plumbing is industry-led
9’47: Limit the blast radius: How JPMorgan, HSBC and Citi turned tokenized deposits into a client retention play
14’46: Finance is globalised, not global: Why Stripe built its own chain instead of stitching together every other one
18’21: There is no Fedwire for the internet: The missing global settlement layer Tempo is built for
21’18: On-chain cash settlement is less than 0.1% done: Why Tempo is where stablecoins and tokenized deposits converge
26’20: The WAP-phone era of agentic commerce: Why nobody is actually paying with agents yet
33’07: Everyone is your frenemy: Why Stripe and Coinbase both showed up to the agentic payments market
36’44: 9 in 10 companies get zero AI productivity gain: What separates the enterprises that don't
43’54: Harnesses and model routers: Where the durable value sits in the enterprise AI stack
46’05: The channels used to connect with Simon & learn more about Tempo & Fintech Brain food

Disclaimer here — this newsletter does not provide investment advice and represents solely the views and opinions of FINTECH BLUEPRINT LTD.
Contributors: Lex, Laurence, Matt, Farhad, Mike, Daniella
Want to discuss? Stop by our Discord and reach out here with questions.

In this episode, Lex chats with Edward Woodford — Founder and CEO of zerohash, a crypto and stablecoin infrastructure platform that lets banks, brokers, and fintechs embed digital-asset trading, payments, and tokenization through a single API. Four years on from their last conversation, zerohash has settled over $65 billion in volume across 7 million customers, gone global under MiCA and EMI licensing in Europe, and onboarded institutions like Morgan Stanley.
They discuss the pivot from embedded crypto to pure-play B2B infrastructure, and why the product zerohash actually sells is trust — with licensing treated as a bar, not a goal — in a world where state actors are now the primary threat.
Edward breaks down the three core rails (Trade, Transact at roughly 70% of revenue, and Tokenization), and unpacks the emergence of "on-chain money" as a legally fragmented category — stablecoins under GENIUS, tokenized deposits, tokenized money-market funds, and CBDCs, each a distinct form of dollar created inside twelve months. They explore how velocity of money and just-in-time funding reshape SME payroll, why the new Auth product aims to be the open banking of stablecoins, and where the industry sits on an S-curve Edward insists is still nowhere near maturity. Finally, they take a skeptical pass at the machine economy, landing on agent-to-knowledge payment — not consumer micropayments — as the durable intersection of stablecoins and AI, and on the convergence that will pull traditional and crypto-native payment firms into aggressive consolidation.
We recorded the podcast earlier in the year, and everything that Edward teased in his conversation has come to market. The E-Trade integration is live. The staking infrastructure has launched. The Treasury published the first proposed rules under the Genius Act, so you can see how those predictions came to market. Also, Stripe and Visa answered his M&A predictions with something even bigger: 140 Company Stablecoin Consortium.
NOTABLE DISCUSSION POINTS:
Trust is the product; licensing is just table stakes. Edward’s sharpest framing is that “licensing is a bar, not the goal” - getting licensed actually opens you to new risks to manage at scale. For an FI like Morgan Stanley, whose crypto revenue is trivial next to tens of billions in quarterly profit, the deciding factor isn’t upside but de-risked entry: FIPS/government-grade compliance, an eight-year clean track record, and a threat model that now treats state actors as the primary adversary.
“On-chain money” has fractured into distinct legal categories in under a year. Post-GENIUS and MiCA, stablecoins (backed 100% by short-term government debt) are now legally separate from tokenized bank deposits (e.g. JPMorgan), tokenized money-market funds, and CBDCs - each a different form of dollar. Edward predicts this taxonomy keeps multiplying, and treats the resulting complexity, including cross-chain stablecoin interoperability, as a widening moat rather than a nuisance.
The real AI-stablecoin use case is agent-to-knowledge payment, not micropayments. Edward pushes back on the popular “sub-penny real-time micropayments” narrative - invoking iTunes, where payments got batched rather than charged per song. The durable edge, he argues, is a globally programmable rail where an agent in Mozambique can settle with a content creator in Brazil, with knowledge released on a DvP basis as payment clears. Sub-penny amounts get aggregated into daily or weekly batches.
TOPICS
Stablecoins, EmbeddedFinance, Tokenization, DigitalAssets, Payments, GENIUSAct, MiCA, AgenticPayments, DeFi, RWA, Web3, Fintech, zerohash, MorganStanley, Gusto, Stripe, Circle, Tether, Plaid, Mastercard

ABOUT THE FINTECH BLUEPRINT
🔥Subscribe to the Fintech Blueprint newsletter to stay at the forefront of Fintech and DeFi: https://bit.ly/3hyhlC2
🤝 Partner with Fintech Blueprint through sponsorships: https://bit.ly/3UZllsV
👉 Twitter: https://twitter.com/LexSokolin

TIMESTAMPS
2’54: From 5% of Ethereum to $65 billion settled: four years of scaling without trading off trust
6’19: The everything app comes full circle: from embedded crypto to one infrastructure engine
11’29: Interoperability as the value prop: bridging USDC across ETH, Polygon, and Canton
16’06: Build, buy, or rent: how zerohash wins the decision inside a firm with billions in profit
18’47: Stablecoins are good, crypto is bad: the market's false divide and why zerohash rejects it
26’18: Auth, the open banking of stablecoins: killing the two questions that break usability
29’55: The next 24 months of consolidation: will Circle, Tether, and zerohash buy the traditional players?
37’22: The Fortune 500 is barely penetrated: what usability and distribution unlock next
41’10: Agent-to-knowledge transfer: the real intersection of stablecoins and AI, beyond the sneaker purchase
46’41: The channels used to connect with Edward & learn more about zerohash

Disclaimer here — this newsletter does not provide investment advice and represents solely the views and opinions of FINTECH BLUEPRINT LTD.
Contributors: Lex, Laurence, Matt, Farhad, Mike, Daniella
Want to discuss? Stop by our Discord and reach out here with questions.

In this episode, Lex chats with Srini Krish — Co-Head of Financial Solutions at Fiserv, one of the original fintechs, in business for nearly five decades and sitting at the intersection of commerce and banking.

Lex and Srini discuss how Fiserv acts as the technology backbone for 5,000+ US banks and credit unions that lack the wherewithal to match JPMorgan or Wells Fargo on their own, and how the firm is packaging AI into that distribution layer through Agent OS and partnerships with OpenAI and Anthropic. Srini lays out his four-bucket framework for enterprise AI - better client service, internal productivity, AI embedded in products, and a platform banks can use to build their own agents - and explains why money demands deterministic outcomes rather than probabilistic guesses, keeping a human in the middle as commercial loan underwriting compresses from weeks to hours.

They explore the competitive race against challengers like Mercury and Ramp, the mainframe that has outlived thirty years of obituaries, and where power sits between the AI labs and their distribution channels once inference commoditizes.

NOTABLE DISCUSSION POINTS:

MIPS became tokens. Srini frames the whole AI shift through continuity: engineers once measured effectiveness by MIPS consumed and how often they compiled code; today the metric is token consumption. Same discipline of doing more with minimal resource, thirty years apart.

Money forces determinism. Probabilistic outputs are fine for many tasks but unacceptable for balances - a figure 1% or 5% off is a failure, it has to be right every time. So Fiserv’s Agent OS rollout starts with non-real-time, human-in-the-middle use cases and only graduates toward autonomy and eventually customer-built agents. It’s a crawl-walk-run path, and Fiserv says it’s clearly still crawling.

The moat is distribution, not model access. Fiserv’s 5,000+ banks and credit unions can’t engage OpenAI or Anthropic directly at scale, so Fiserv becomes the platform that packages agentic workflows - turning commercial loan decisions from a multi-week process into hours, with the auditability and observability those institutions could never build alone.

TOPICS

Fintech, Fiserv, EmbeddedFinance, AgenticAI, EnterpriseAI, Banking, Payments, DigitalBanking, CommunityBanks, FinancialInfrastructure, AIAgents, OpenAI, Anthropic, ClaudeCode, JPMorganChase, FirstData, Mercury, Ramp, Plaid

 

ABOUT THE FINTECH BLUEPRINT

🔥Subscribe to the Fintech Blueprint newsletter to stay at the forefront of Fintech and DeFi: https://bit.ly/3hyhlC2

🤝 Partner with Fintech Blueprint through sponsorships: https://bit.ly/3UZllsV

👉 Twitter: https://twitter.com/LexSokolin

 

TIMESTAMPS

1’12: Fintech Before It Was Fashionable: Five Decades at the Intersection of Commerce and Banking

6’13: Access, Move, Trust: What Actually Defines a Fintech Across Three Decades

10’28: A Loan at the Mechanic's Shop: How Embedded Finance Widened the Market and the Money Behind It

13’22: Four Buckets for Enterprise AI: Where Agent OS and the OpenAI Partnership Actually Fit

20’47: Not Savviness but Wherewithal: Why 5,000 Institutions Can't Build JPMorgan's Stack Alone

25’39: Mercury, Ramp, and the Mainframe That Never Died: Why the Incumbents Aren't Going Anywhere

29’51: Both Labs, All Three Clouds: Why the Distribution Channel Sits in the Middle

33’16: The Engineer Who Stops Writing Code: Why Replacement and Expansion Can Both Be True

36’50: It Has to Be 100% Correct Every Time: Why Money Demands Deterministic AI

Disclaimer here — this newsletter does not provide investment advice and represents solely the views and opinions of FINTECH BLUEPRINT LTD.
Contributors: Lex, Laurence, Matt, Farhad, Mike, Daniella
Want to discuss? Stop by our Discord and reach out here with questions.

In this episode, Lex chats with Jeff Grimes — who is Head of Live Events Products at Perplexity, the AI company that has evolved from an "answer engine" into an "agent platform" built around Perplexity Computer, its multi-agent digital worker. They discuss how Perplexity has shifted financial research from the how to the what, letting a user describe an outcome in a single sentence while Computer orchestrates 20+ frontier models, direct tool calls to licensed live data, and finance-specific skills to produce the artifact.

Jeff explains the enterprise strategy behind traceability - the north star that 100% of every quantitative figure traces back to its source filing - alongside bring-your-own-license connections via MCP and the consumer "personal CFO" vision powered by Plaid. They explore what 5x revenue growth on a 34% headcount increase signals for finance jobs, and why the future looks like a 24/7 family office that proactively surfaces and, with permission, executes financial actions for everyone.

NOTABLE DISCUSSION POINTS:

The “how to what” collapse is the real product thesis, not just better models. The shift to zero-shot rests on three stacked unlocks: direct tool calls to licensed live data (Quartr for earnings transcripts, unusual whales for insider and political holdings, SEC filings for historicals) instead of relying on web freshness; a thinking-model router that orchestrates 20+ frontier models in parallel, matching the model to the job (a heavy thinking model for macro analysis, a lighter one for ticker-matching 550 names); and ~20 opinionated finance skills (DCF, three-statement, LBO, comps) tuned through expert-led evals. Together they turn one sentence into a polished equity-research artifact.

Traceability is the enterprise wedge, framed as “don’t trust and verify.” The stated north star is that 100% of every number in any output is hover-traceable back to the source filing - pre-scrolled to the page, highlighted, with the full chain of calculations exposed. The framing inverts the usual “trust but verify”: assume the user won’t trust the model, so trust must be earned per number. Paired with bring-your-own-license via MCP (FactSet, LSEG, Morningstar, CarbonArc, PitchBook), this is the concrete answer to why regulated institutions get comfortable adopting.

The productivity and jobs signal is quantified and lived internally. Perplexity grew annual run rate 5x while increasing headcount only ~34%. Computer began as a company-wide Slack bot where every request was visible to all employees; Jeff now runs 9–10 scheduled cron jobs each morning and says essentially all code is written first by his agents. On the consumer side, the emergent pattern is build-your-own long-tail apps that no roadmap-bound product could serve - a DraftKings-addiction accountability system that emails a user’s spouse on any bet, or a GitHub-style heatmap of daily spending - which is the real substance of the personal-CFO bet.

TOPICS

Perplexity, Perplexity Computer, Perplexity AI, Google, Shadebot, Plaid, Yodlee, Claude, ChatGPT, AI, Artificial Intelligence, LLM, CFO, financial services, AI commerce

 

ABOUT THE FINTECH BLUEPRINT

🔥Subscribe to the Fintech Blueprint newsletter to stay at the forefront of Fintech and DeFi: https://bit.ly/3hyhlC2

🤝 Partner with Fintech Blueprint through sponsorships: https://bit.ly/3UZllsV

👉 Twitter: https://twitter.com/LexSokolin

 

TIMESTAMPS

1’05: A company built on failed founders: Why the startup that didn't work out led here

5’10: A playing card company that became Nintendo: How curiosity carried Perplexity from answers to actions

9’52: We're basically at zero shot now: Why prompt engineering is disappearing from finance work

15’21: A thinking model that routes the job: How Perplexity picks Claude Opus for macro and Grok for tickers

20’12: Two tracks, one engine: Building for enterprise workflows and a personal CFO at once

25’25: Bring your own license, or use ours: How Perplexity gets institutions comfortable enough to adopt

32’54: 5x revenue on 34% more headcount: The productivity gain Perplexity lived firsthand

37’28: Connect everything from your mortgage to the painting on your wall: Building the true personal CFO

45’15: A family office that works 24/7 for everyone: The proactive, automated future of the personal CFO

48’01: The channels used to connect with Jeff & learn more about Perplexity Computer

Disclaimer here — this newsletter does not provide investment advice and represents solely the views and opinions of FINTECH BLUEPRINT LTD.
Contributors: Lex, Laurence, Matt, Farhad, Mike, Daniella
Want to discuss? Stop by our Discord and reach out here with questions.

In this episode, Lex chats with Cactus Raazi — CEO Americas at B2C2, one of the original and largest institutional market makers in digital assets, serving roughly 1,500 institutions and pricing across more than 40 exchanges globally.

They discuss what a market maker actually does, how balance sheet and signal generation underpin roughly $1 billion a day of stablecoin flow at B2C2, and why the two extremes of crypto market making - riskless principal aggregation versus proprietary alpha - produce very different client outcomes that buyers rarely understand.

Cactus explains B2C2's 18-month bet that the Circle-versus-Tether debate would give way to a multi-issuer world, the launch of its PENNY product for instant zero-cost cross-stablecoin swaps, and they explore why programmability is the next frontier for digital dollars, why US capital markets have almost no structure for funding genuine risk-taking businesses, and whether the current combination of scale, speed, and complexity makes this the hardest investing environment Wall Street has ever faced.

NOTABLE DISCUSSION POINTS:

Market makers aren’t a homogeneous category, and clients pay for the difference. At one extreme, a market maker is essentially a riskless agent - aggregating prices across 40+ exchanges and quoting on top with no real view. At the other extreme, a market maker is a proprietary quant shop running alpha signals on horizons from seconds to days, and the price you get is heavily conditioned by where the signal says the asset is going. B2C2 sits in the middle, partly because its public-company parent (SBI) constrains risk appetite. The implication for institutional buyers: who you trade with structurally determines the quality of execution, not just the spread.

Algorithmic fixed income market making didn’t fail on technology, it failed on capital structure. US capital markets are excellent at funding venture, growth equity, private equity, and buyouts, but there is almost no domestic pool of “risk equity” - capital comfortable with the possibility that the machines (or the humans) lose money on a given day. Market makers need exactly that kind of balance sheet, and the mismatch between what the business requires and what the US capital base offers is a structural reason firms like Elefant struggled, regardless of execution quality.

The Circle-vs-Tether framing is already obsolete; the next product wedge is interoperability. B2C2 made an 18-month-old contrarian bet that the duopoly narrative was wrong and that Stripe (via Bridge), Western Union, Revolut, and many other consumer and platform companies would issue their own stablecoins. PENNY - instant, zero-cost, zero-counterparty-risk stablecoin-to-stablecoin swaps - is the product expression of that view. The deeper claim is that stablecoins are software, and the SaaS analogy (a base layer plus an app store of programmable financial logic) is the real reason institutional adoption accelerates from here, not the transfer-of-value benefit on its own.

TOPICS

B2C2, Goldman Sachs, SBI Group, Binance, Coinbase, Circle, Tether, Stripe, Kraken, Credit Suisse, Market making, institutional liquidity, stablecoins, fixed income, risk management, algorithmic trading, crypto exchange infrastructure

 

ABOUT THE FINTECH BLUEPRINT

🔥Subscribe to the Fintech Blueprint newsletter to stay at the forefront of Fintech and DeFi: https://bit.ly/3hyhlC2

🤝 Partner with Fintech Blueprint through sponsorships: https://bit.ly/3UZllsV

👉 Twitter: https://twitter.com/LexSokolin

 

TIMESTAMPS

1’17: Rejected by 30 firms: A cold-call advertising inquiry that became a Goldman career

6’43: "I'll go sell jet engines": Complexity as the through line from credit derivatives to crypto

8’53: Scale, speed, and dimensionality: The hardest investing environment in 28 years

12’33: A terrific idea, a brutal execution: Building an automated market maker in 2015

16’22: The used car dealership of bonds: How over-the-counter fixed income actually works

19’51: Price, time frame, and the art of liquidity: What a market maker actually does

24’52: Riskless principal or proprietary alpha: The two extremes of crypto market making

29’54: Priming the liquidity pump: Why new tokens hire market makers and large ones don't

35’40: $1 billion a day in stablecoins: A contrarian bet against the Circle-versus-Tether frame

39’43: 24/7 money movement: The treasurer wish list stablecoins actually deliver

41’04: The channels used to connect with Cactus & learn more about B2C2

Disclaimer here — this newsletter does not provide investment advice and represents solely the views and opinions of FINTECH BLUEPRINT LTD.
Contributors: Lex, Laurence, Matt, Farhad, Mike, Daniella
Want to discuss? Stop by our Discord and reach out here with questions.