The "magic" starts when Sig contributes to another, remote repo - a central knowledge base that all teammates' local Sig can pull from, and contribute toward.

I'm building Sig <https://github.com/adamjramirez/sig-releases> and the architecture overlap is obvious: macOS, plain markdown, git-versioned, designed as context for AI agents.

The difference is where in the workflow we start. Tolaria seems to excel at organizing knowledge that already exists. Sig is trying to solve what happens before that - how to get the knowledge out of your head and into files in the first place. Most of what actually determines the quality of your AI output was never written down: the decision made in the last five minutes of a meeting, the verbal commitment with no follow-up, your actual read on what a conversation meant (not the surface version).

Sig's capture is two layers: 1) factual record first, 2) your personal interpretation on top. Both stored as markdown on your machine. When you're ready to share to a team knowledge base/open brain, it's an explicit decision to do so and opt-in — private by default, team-readable only when you choose.

- Who mentions who in their videos?

- Which brands keep showing up across the same creators?

So I built a pipeline that analyzes YouTube videos at scale, extracts every person mentioned and every brand sponsor, and builds a relationship graph from it. No manual data entry. Everything is extracted from what creators actually say and show.

Current data: 32K creators, 55K relationship edges, 2,700 brands. Started deep in fitness and gaming YouTube.

Things to try out:

- Search "Gymshark". See their sponsored creators, which categories they target, and which brands compete for the same roster

- Search "MrBeast". See his connection network

- Click a category tab on the homepage to filter both creators and brands

The hardest technical problem was entity resolution. The same person gets mentioned as "Jeff Nippard", "Jeff", "Nippard" across thousands of videos. Getting that right is what makes the graph useful.

Stack: FastAPI, Next.js, PostgreSQL, Fly.io. Gemini 2.0 Flash for structured extraction.

No signup, no paywall.

Comments URL: https://news.ycombinator.com/item?id=47335935

Points: 1

# Comments: 1

It is lacking on features at the moment, but if you are willing to do some manual filtering, you have more or less first access to a lot of jobs.

Edit: Giving credit where due (original post) - https://news.ycombinator.com/item?id=38177286

Today, I've got a couple of crypto ideas that have been brewing in my mind for a while and I've love to get some critical feedback on them.

Idea 1: Crypto Onboarding Made Easy Picture this: a service that takes the stress out of diving into crypto. We're talking about a neat package with all the details, from crypto basics to a guided first purchase and regular market updates. It's all about empowering folks to enter into the crypto world with confidence. There are some resources for parts of this already, e.g. Ledger's introduction to crypto and their guides, but I find that as an example, my parents would have a hard time navigating that. I may need to do more research on competitors here.

Idea 2: Crypto for the Future Gen What if there was a platform offering time-locked crypto assets, like a trust fund but with a digital twist? You stash some crypto for a while, and it unlocks when, say, the account holder hits 18. It's not just an investment; it's a cool way to teach financial smarts early on. The time-based aspect can apply to a lot of different scenarios, birthday's, contract fulfilment come to mind right away.

Why? Crypto can be a maze for newbies, and I'm thinking of ways to make the journey smoother. Plus, introducing time-locked crypto is like handing future financial ninjas their first set of digital nunchucks.

So, what do you think? -Do you dig the idea of easy crypto onboarding? -How about the notion of time-locked crypto assets? -Any quirks or other features you'd throw into the mix?

Your input is valuable here. I'd love to hear your thoughts.

Comments URL: https://news.ycombinator.com/item?id=38924642

Points: 1

# Comments: 0

Remote: Yes

Willing to relocate: No

Technologies: Python (Django), AWS (EC2, ECS, ALB, Lambda, DynamoDB, S3, CloudFormation, IAM, SQS, SNS, StepFunction & many more), Docker, Docker Compose, Redis, ElasticSearch, Postgres, MongoDB, GraphQL, Bash, Flutter, Riverpod

Résumé/CV: Please message or email me

Email: mradamjramirez at gmail.com

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With around 12 years in tech coding & managing, I'm your hands-on tech leader, specializing in infrastructure and backend development. I've steered teams through startup hustle, growth vibes, and even the occasional merger chaos. Actively involved in crafting systems from the architecture to the coding. Open to management or hands-on coding roles (backend, DevOps, Infra, Platform, etc.)

Comments URL: https://news.ycombinator.com/item?id=20000863

Points: 4

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Comments URL: https://news.ycombinator.com/item?id=10545900

Points: 2

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Plans to expand?

Comments URL: https://news.ycombinator.com/item?id=7706933

Points: 6

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Comments URL: https://news.ycombinator.com/item?id=5771759

Points: 2

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Comments URL: https://news.ycombinator.com/item?id=5470458

Points: 29

# Comments: 8