Allow us to introduce ourselves
Welcome to the digital workshop of Garrett and Iain, formally known as Better Than Good.
We’ve been long distance friends (roughly 4,850 miles by plane, train, and automobile) for 15 years, worked together in a past life and found ourselves at an identical career juncture during one of the most frenetic moments in tech. One thing led to another, and after a few phone calls the stars aligned and we gave the idea of working together two thumbs up (hence our logo).
Garrett Winder
Garrett started a web design company during college, co-founded and sold a social analytics platform, then joined Erskine Design in England, working with clients like the BBC. Later he started Good Work, growing it to a seven-figure agency serving clients like Tito’s, PBS and Caesar’s Entertainment before selling in 2024.
Garrett on LinkedIn
Iain Harper
Iain started his career at the UK’s first internet bank, Egg, going on to work extensively in insurance and financial services at companies like Zurich, before building and selling an Insuretech startup. Most recently, he was at Oxford University where he gained a master’s degree in Artificial Intelligence for Business.
This is not our first rodeo (though it may be Garrett’s 47th)
We’ve taken a lot of trips around the sun (and most of them have been on the internet). In other words, there are few problems we’ve not encountered and solved along the way. And we’ve done it for businesses of all shapes and sizes.
Most studios like ours give you a long list of services. AI strategy! Digital transformation! Agentic AI! Algorithmic vibe alignment! But telling you we do this or that is a bit like a butcher saying they sell sausages. And that’s why we deliberately avoid long lists of services and capabilities.
That said, if you genuinely need a complex autonomous system that is easy to use and can handle thousands of sensitive decisions a day, we can build that for you (which is probably good to know). Maybe that’s why our official company name is BTG Space Exploration and Cattle.
Here are some recent problems we’ve solved for organizations just like yours:
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Rebuilding the work before bringing in the robots
We mapped a client’s workflows, sorted what to script, what to hand to agents and what to keep with humans, plugged it into their existing tools and stuck around to keep tuning it.
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Turning operational chaos into profit
We untangled a client’s siloed billing and on-off-boarding to flip a leaky service line from red to black.
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Automating complexity from research to revenue
We built a tool that replaces a complex multi-step process with an automated pipeline from research to sale (actually, we do this a lot).
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Proving growth capacity with confidence
We mapped a small shop’s committed work to show them that they can double headcount tomorrow to make more money and still have seven months of runway.
We think that your idea/problem should go here.
The robots do the dishes
Speaking of technology, most businesses like ours scale by hiring, but we scale by building. Our ‘factory floor’ (strategy, ops, delivery, the boring bits) is an agentic team we built, and continue to optimize, ourselves. ‘They’ handle the busywork so we don’t have to hire a bunch of people to handle the busywork.
So what does this mean for you? It means you get Garrett and Iain x10 (and we’re dead-set on figuring out how to make that x100).
From day one with our clients, the plan is to give you the tools to be self-sufficient. After that, you stay on the Christmas card list and we’re here to help when you need us.
The system grows and the (human) team doesn’t, and you still get Garrett and Iain.
If you’ve made it this far it’s probably time to join the family. Sign up for our bi-monthly newsletter or grab the RSS feed like it’s 2008.
Latest blog posts
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Apple’s bicycle without a chain
Steve Jobs described the computer as a bicycle for the mind. Apple Intelligence so far is more like a bicycle with no chain. The frame is gorgeous, and the engineering is extraordinary, but you cannot get far with it.In early 2025, Xe Iaso published a piece that landed like a brick through a window in the Apple developer community. The argument was simple and damning: Apple had built the holy grail of trusted compute with Private Cloud Compute, a genuinely unprecedented piece of security infrastructure, only to fill it with half-baked notification summaries and an image generator that produce…
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Weeknotes vol. 17: business, schmizness
Hello and happy casual weeknotes Friday.I stopped writing these about a year ago when I began the transition into consulting (solving fun and challenging problems), and to say a lot has changed since then would be the understatement of the century.In summary: Iain joined full time, we’re helping people solve operational problems and optimize their work across pretty much all aspects of business, and we’re having a lot of fun doing it. Iain has his masters in AI for Business, which has pushed me to go down the biggest rabbit hole I’ve been down since HTML/CSS in college (and we know where that…
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The ten trillion dollar gamble
In November 2025, on stage at the Wall Street Journal’s Tech Live event, the chief financial officer of OpenAI was asked how her company planned to honor roughly $1.4 trillion in compute contracts on $13 billion of revenue. Sarah Friar said she was looking to assemble a network of banks, private equity, and a federal “backstop” or “guarantee.” By the following evening, she had posted to LinkedIn explaining that “backstop” had muddied the point, that what she meant was something more like a public-private partnership, and that the United States government has been “incredibly forward-leaning” …
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Never talk about goblins
Buried in a JSON file that OpenAI posted to GitHub recently, inside the configuration for its newest coding agent, sits an instruction that reads like a footnote written by someone losing their composure. “Never talk about goblins, gremlins, raccoons, trolls, ogres, pigeons, or other animals or creatures unless it is absolutely and unambiguously relevant to the user’s query.” The line appears more than once. Whoever wrote it wanted to be sure the model understood.Most readers, including ones who follow AI closely, may be unaware of what a “base instruction” is, where it lives, or why anyone a…
