We’re delighted to welcome @OpenRouter to Stripe to help developers and businesses optimise their AI usage. As intelligence becomes a large fraction of companies' budgets, allocating that intelligence budget wisely becomes increasingly important.

The ultimate Opus 5.5 coding prompt. Drop this into ANY vibe-coded project you built pre-Opus 5.5. The new model will go in and optimise your entire codebase. You're welcome:

Why use Liquidity Hub rather than supplying directly to a single market❓ 👉 A simple one-click structure that will rebalance across the Venus ecosystem, earning you rewards from multiple sources 👉 No need to monitor APY -- Liquidity Hub rebalances the portfolio within governance-defined boundaries to optimise for you

intelligence should not be treated as a tool subscription you buy but as capital you allocate. a few ways to optimise for it: 1/ budget it by the job, not the tool. ask what a specific task is worth if a model does it well, and then what it costs to run. you'll then be able to fund the ones that pay back. 2/ match the model to what's at stake. if you don't put your best people on low-stakes work, think about intelligence the same way: a cheap model for the high-volume tasks and an expensive one only where a mistake is costly. most teams overpay by running a premium model across everything. 3/ don't over-commit all at once, as intelligence typically gets cheaper every few months. a task that isn't worth automating today often is 2 quarters later. underwrite in short cycles rather than locking in one big flat contract. @stripe also put it well in their openrouter letter: you need to reason for the cost and return of every unit of intelligence the way you would for capital.

£600 to acquire a customer worth £15,000. That's the maths behind one of my businesses and the system that produces those numbers is exactly what I'm breaking down in this week's Masterclass. Most businesses are either spending too much to acquire customers who aren't worth enough, or not spending at all because they don't know their numbers well enough to feel confident. Both problems come from the same root: there's no system generating demand predictably enough to measure, optimise, and scale. When demand is predictable, everything changes. You know what a lead costs and how many leads it takes to make a sale. You also know the lifetime value on the other side. That's how every marketing decision becomes maths instead of guesswork. I've spent 25 years building this into a repeatable system, and the tools available now make it faster and cheaper to implement than at any point in that entire time. Join my free 90-minute Masterclass - The 7-Figure Demand System, where I'll walk you through exactly how I create demand, attract better leads, and turn more of them into clients. Only two sessions this week:

I was trawling through Discord the other day when I saw a message that reminded me that @giga_dex's points program is 50% complete, which is cool! With TGE coming up at the end of August I started doing some maths for myself, but maybe not on the side you'd expect me to focus on. GigaDex is an optimisation on the Ve3,3 model popularised by @AerodromeFi over on @base. Rather than directing emissions directly to LP's, the V3,3 model encouraged token holders to step in and play an active role, locking their own tokens to earn voting rights which they were then able to use to direct future emissions towards the LP's of their choice. Giga saw this model and went, hey, its great, but we think we can optimise further. They started with the same basic framework, token holders earn in line with protocol success, but they cut out a lot of the inherent complication of the voting system by directing emissions themselves. This means that token holders will earn ALL protocol fees, with a model that allows you to stake, select your reward token and walk away. This is the bit I was interested in. I absolutely love models where fees go direct to holders, so I decided to run the numbers at TGE. The entire supply of GIGA is being printed at TGE, which makes it a bit easier to track everything, we're starting with 1 Billion tokens. What I'm interested in is the percentage of those tokens that're starting off as veGIGA, the locked version of the token. This is where all the fees will accrue. Working through the tokenomics model, Initially the veGIGA Machine, the $ROOT protocol allocation, the Launch Partner Allocation and the Community Airdrop will be locked as veGIGA at launch, adding up to 34.5% of total supply initially locked. In addition, the Treasury, Fair Launch Allocation and LP Support have potential to be allocated as veGIGA, adding a potential further 24% of supply locked at launch. So, we're starting with 34.5-58.5% of total supply earning a portion of protocol fees on day 1. The protocol earns 20% on Gauged (currently points earning, in future GIGA emission earning) pools, and 10% on non-gauged pools. GIGA is averaging ~$2000/day in total fees, so lets assume that the majority of that is gauged volume given points are great, meaning we're looking at ~$325/day in fees going into stakers pockets in the form of their choice. This might not sound too crazy, but lets contrast that with @Uniswap, who currently own the majority of volume on @RobinhoodCrypto. It's not a direct analogue as the fee split is a little different, but on average Uniswap is bringing in ~$130k in protocol revenue a day. If Giga can establish themselves to even a third of that daily rev things get pretty nice pretty fast for stakers. At 40k fees a day holding a decent percent of veGIGA could be pretty fun for your wallet, especially with as low as 35% of supply staked initially. With a pretty substantial amount of variance in the amount of supply staked on Day 1 it's a pretty interesting conundrum. Do you think Giga has potential to hit Uniswap numbers? Would you be happy if it chilled and paid you out smaller chunks of USDG over time? Either way, GIGA is an interesting concept and I'll be keeping an eye on them to see how it all pans out. Thanks for reading!