Daniel Lin

Agentically Engineering AI + Crypto Products

Building Agentic Commerce @animocabrands

[Daniel Lin @Pofrandom]

CLI for agents

[Philipp Schmid @_philschmid]

We launched the Gemini API CLI. A CLI for calling the Gemini API. Give it to the agent you already use (Claude Code, Codex, Antigravity, Cursor, OpenClaw, Hermes...). It's NOT a new coding agent you can use it too:

1. Generate images, video, speech, music.
2. Analyze PDFs, images, audio, video, YouTube URLs,
3. Transcribe recordings to md / json / srt,
4. Run Deep Research in the background.

Stateless. No memory, no chat mode. Your agent owns the context and the plan, gemini-api does the API call. Build for Agents, it's self-describing. `--help`, `--dry-run`...

Start here: https://t.co/D812RdijJO

[sophia goldberg @sophgoldb]

So there are basically 3 ways an AI agent can pay with a card today. Where do each of these break?
(1) You hand the agent your 16 digit PAN. It works everywhere, but the merchant and your bank can’t tell a bot is buying, your full credential is sitting in someone’s system, and disputes get messy fast (“did you buy this, or did your agent?”)
(2) A network agent token. Visa Intelligent Commerce or Mastercard Agent Pay swap your card number for a token tied to that specific agent, with spending limits and a clear “an agent did this” signal. It’s the cleanest model, but it only works where issuers, acquirers and merchants have switched it on. A ton to be figured out here still
(3) A card the agent platform issues. Either stored value (you prefund a balance with the agent) or card fronting (the platform’s card pays the merchant, then it charges your real card behind the scenes). This works today and seems to be gaining steam as a preferred mode, it lets agents monetize payments as well

[Daniel Lin @Pofrandom]

@cryptopunk7213 we can only hope the internet is antifragile

[tobi lutke @tobi]

Excellent code mode env:

https://t.co/jYY88URne4

[Rovin.md @0xRovin]

I built an AI agent that helps me look for jobs using @hellominds_

A thread 🧵

[Daniel Lin @Pofrandom]

VIC

[Terry Angelos @terryangelos]

Why Stripe is speedrunning the AOL-era of agentic commerce:

Agents will be the new UX to $7T in global ecommerce. But many agentic transactions today are not made by its customers. Instead, a wallet (such as Stripe’s Link) uses their own virtual card to purchase on my behalf.

This means there are two transactions occurring: one between me and Stripe and one where the Stripe wallet “shops on my behalf”.

This walled garden allows the transaction to work but breaks the relationship with between me and the merchant. A good example is a recent transaction I made at Walmart. The agent paid using a virtual card but when I was asked to sign-up for Walmart+, the follow-on transaction failed (Walmart didn't have my card on file!).

This AOL-era won’t last. Instead, agents and wallets will start to use agentic tokens (from the card networks) that enable agents to use my card without getting sensitive information.

Over the coming months, I expect agents and wallets to adopt the new token standards from Visa/MC/AMEX and move us away from walled gardens to open standards.

[Daniel Lin @Pofrandom]

@danshipper @every I barely look at websites nowadays. I just ask my agents to get what I need from the sites. Sick of seeing ads.

[Daniel Lin @Pofrandom]

@Denche2005 Unicoders like unicorns

[Daniel Lin @Pofrandom]

@poteto reset guy lol. love the feud. pls keep it up.

[Animoca Brands @animocabrands]

Animoca Portfolio Day brought our ecosystem together in Singapore ahead of #TOKEN2049 ✨

From go-to-market strategies in the agentic era to on-chain fund structures and trust frameworks for AI agents, the conversations explored the infrastructure needed for AI agents and institutional finance.

For AI agents to transact on our behalf, trust matters: knowing who an agent is, who it acts for and what it is allowed to spend. Verifiable identity and programmable money could help blockchain support that trust.

Thank you to the speakers, portfolio companies, investors, and partners who joined us, including @privy_io, @stripe, @tatum_io, and @AWSCloud.

Stay tuned for more highlights from @animocainsights!

[Daniel Lin @Pofrandom]

something I actually missed and thought about lately is @LimitlessFT pod

glad its back

https://t.co/n3cBGYt12P

[Daniel Lin @Pofrandom]

@elonmusk @bot you will need both sides of the credit card , right @bot ?

[Daniel Lin @Pofrandom]

@patrickc meaningful agent-to-agent negotiations are now possible, this will hopefully allow personal agents to discover and buy the most suitable products proactively like a real personal shopper would.

[Daniel Lin @Pofrandom]

Speaking of unfair advantage

[Grok Bot @bot]

Grok Bot can now search, read, and monitor X.

[Theo - t3.gg @theo]

Bad news guys: Grok Bot is actually really good 🙃

[Kun Chen @kunchenguid]

there’s now a new mental model for the software stack

- skills are the new “apps”

you install them to get more functionality. people are starting to build and share skills more than real “apps”

many skills are very simple today but i think we’ll eventually see increasing sophistication

- mcp servers and CLIs are the new “APIs”

they allow services to encapsulate their core capabilities behind an interface the can be invoked in a composable way

many skills will be calling mcp servers or clis behind the scenes just like how a lot of apps call APIs today

- agent harnesses are the new “operating systems”

it sits between the user and the underlying resources, helping the user manage common concerns such as compute, memory, security etc

if you look closely, it’s hard to unsee the resemblance - claude is the new macos. codex is the new windows. pi is the new linux

skills run in agent harnesses just like apps run in existing OS

- LLMs are the new “computers”

they process instructions coming from the user, the skills, the agent harnesses, and compute the output

the model weights is the cpu. context window is the memory. actual computers are becoming more like the power source

ok so why do we need this mental model? i think it helps us think about where we play

if you want to be the new app developers - start to learn to write good skills

if you want to build a saas, figure out how to package things as good mcp servers and CLIs

if you want to be linus and write the new linux, build an agent harness. otherwise, you can still try to learn about how agent harness work like how CS students used to learn about OS

if you want to be the new apple or samsung, start to learn how LLMs are trained and play with open weight models - you may end up inventing the new raspberry pi!

[Daniel Lin @Pofrandom]

ELI100 guy. Have fun!

https://t.co/O7zm9c0kff

[Daniel Lin @Pofrandom]

Explain like in ASD-STE100

ELI100

npx skills add daniellinuk/ELI100

Looks promising so far

[Daniel Lin @Pofrandom]

@timo_rf 😂