Tegh

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Tegh

Tegh

@tegh_m

Senior Software Engineer for Agentic AI Products @coinbase (Advisor, Trading Arena) | @uoft CS alum | opinions my own

Toronto, ON, Canada Katılım Ocak 2015
192 Takip Edilen79 Takipçiler
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Tegh
Tegh@tegh_m·
Introducing Trading Arena – the easiest way to deploy an AI trading agent. 🚀 Try now on tradingarena[dot]xyz Brought to you by our @coinbase Next Bets Applied AI team that @brian_armstrong mentioned in his interview last week - s/o the team @johnp2879 @MurrLincoln Adrian & I.
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Brian Armstrong
Brian Armstrong@brian_armstrong·
Coinbase is testing AI agents that show up in slack/email at work, just like any human teammate. To start we're shipping two which are modeled after legendary former Coinbase employees, @FEhrsam and @balajis. (Who brutally frame mogged who in this matchup?) Soon, it will be easy for any employee to spin up a new agent for themselves or their team. I suspect we will have more agents than human employees at some point soon.
Brian Armstrong tweet media
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superwhisper
superwhisper@superwhisper·
"It's called Superwhisper. I haven't touched my keyboard in months, I just talk and my computer listens, I'm dictating emails, talking to AI agents, vibe coding, everything. I have transcended typing and have become a productivity maxxer"
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Tegh
Tegh@tegh_m·
Write a strategy in plain English. Pick a model. Set risk limits. Watch it trade 24/7 and compete on a leaderboard. Tradingarena.xyz This is experimental and not financial advice – we intend to learn and iterate from user feedback to build the best agentic trading infra. US only (ex-NY). Here is a sped up demo for you. Check out @MurrLincoln’s post x.com/MurrLincoln/st… for the full walk through.
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Tegh
Tegh@tegh_m·
Introducing Trading Arena – the easiest way to deploy an AI trading agent. 🚀 Try now on tradingarena[dot]xyz Brought to you by our @coinbase Next Bets Applied AI team that @brian_armstrong mentioned in his interview last week - s/o the team @johnp2879 @MurrLincoln Adrian & I.
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Thariq
Thariq@trq212·
I think "prompting" will keep being an incredibly high-leverage skill, like writing or public speaking. It is the skill of talking to agents, mediated by the harness. My main goal is to grow the bandwidth between humans and agents, to help us understand each other better.
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Qrx0
Qrx0@CryptoloveLife·
@MurrLincoln @tegh_m @johnp2879 Not Available in Your Region Trading Arena is not available for accounts registered in your region. awesome !
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lincoln.base.eth
lincoln.base.eth@MurrLincoln·
Introducing Trading Arena – the easiest way to deploy an AI trading agent. Write a strategy in plain English. Pick a model. Set risk limits. Watch it trade 24/7 and compete on a leaderboard. tradingarena[dot]xyz
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lincoln.base.eth
lincoln.base.eth@MurrLincoln·
This is experimental and not financial advice – we intend to learn and iterate from user feedback to build the best agentic trading infra. tradingarena.xyz reach out if you have any feedback or questions!
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Tegh
Tegh@tegh_m·
The key point folks replying are missing here is talent density. All metrics are rigged no matter what. For good engineers, token spend —because it’s calibrated to a good engineer — is a good metric for how much AI has made them more productive and parallelized their shipping ability. Of course, yes: don’t ship bugs, delete code, etc. build only good stuff!
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Tegh
Tegh@tegh_m·
I disagree tbh. Engineering input effort is 1:1 to output unlike Marketing, so token spend proxies shipping! Unlike Marketing who has to sell to their customers, Developers don’t need to convince their computer to run their code lol. Especially with high talent density, more token spend = building more, faster, and better quality. I ack drawbacks of shipping too much/fast (wrong things/bugs) but that predates AI.
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Cristina Cordova
Cristina Cordova@cjc·
Ranking engineers by token spend is like me ranking my marketing team by who spent the most money. We may not have hit our KPIs, but Joe spent $200k on a branded blimp that only flies over his own house, so he’s getting promoted to VP! Don't mistake a high burn rate for a high success rate.
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Tegh
Tegh@tegh_m·
@yugacohler @CoinbaseDev Awesome, I need this for something we're shipping very soon 👀 I'm using the CDP API myself on the @coinbase Next Bets team, and this would make our testing faster via Claude
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yuga.eth 🛡
yuga.eth 🛡@yugacohler·
Today, we're launching the @CoinbaseDev CLI and MCP server. These tools give AI agents instant access to Coinbase's APIs for payments, trading, wallets, onchain data, and more. Coding agents like Claude and Codex can now trivially integrate crypto's most trusted APIs. (1/3)
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Coinbase 🛡️
Coinbase 🛡️@coinbase·
Crypto is so boring right now. AI agents literally transacting with crypto rails. Major financial institutions tokenizing everything. Stablecoins with more adoption & interest than ever. I could go on, but meh, so boring.
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Tegh
Tegh@tegh_m·
@jyoti_mann1 Hot take: For solid engineers tokenmaxxing = shipping more. Celebrate if you’re #1 naturally because you’re building a lot and fast. Just don’t burn tokens to get there. lol
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Jyoti Mann
Jyoti Mann@jyoti_mann1·
Exclusive: Meta employees are “tokenmaxxing” and competing on an internal leaderboard called “Claudeonomics” for status as a token legend. Over a recent 30-day period, total usage on the dashboard topped 60 trillion tokens.
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Tegh
Tegh@tegh_m·
@cjc There is a natural limit on how much $ we can spend as an engineer due to our own brain context, let us hit it.
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Brian Armstrong
Brian Armstrong@brian_armstrong·
Steve Wozniak famously went to his boss at HP and said they should build a personal computer. They said no, so he left to found Apple. It’s a lesson for leaders: one "no" shouldn't kill a contrarian but right idea in your company. Twice a year at Coinbase, anyone in the company can pitch a "next bet" idea to a panel of folks. It's structured similar to pitching a handful of venture capitalists internally. If you get any one of them to say yes and fund it, you're green lit. You need ONE yes, not a unanimous yes from everyone in the org structure from you to the CEO (a de facto committee). Lots more goes into this, around capping resourcing on next bets (most are small 2-3 person teams), knowing when to shut them down, or under what revenue/profitability criteria they graduate to regular products. But this is important to having a company that produces repeatable innovation.
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