Shivam Singhal
144 posts

Shivam Singhal
@singhals_
@waldium
Van, Down by the river เข้าร่วม Nisan 2020
852 กำลังติดตาม310 ผู้ติดตาม

Using @claudeai desktop, is there a way to directly reference chats from the claude code tab? I'm finding that chat is better for some high level planning even before using claude code's plan mode.
English
Shivam Singhal รีทวีตแล้ว

This reminds me of Karpathy's llm os (x.com/karpathy/statu…).
In that, and in many approaches I've seen online, the basic tree-based fs seems like a given. Notion, Coda, et. al. are built on "blocks", but I haven't yet seen how that significantly aids in content generation (e.g. coding, writing, etc.).

Andrej Karpathy@karpathy
LLM OS. Bear with me I'm still cooking. Specs: - LLM: OpenAI GPT-4 Turbo 256 core (batch size) processor @ 20Hz (tok/s) - RAM: 128Ktok - Filesystem: Ada002
English

Interesting to read through this paper on semantic file systems (web.mit.edu/6.826/www/note…) in light of agentic search (e.g. swe-grep) vs vector dbs (e.g. the cursor approach).
At a glance, it seems to me that these approaches are kind of mutually exclusive, but I'm not sure if my understanding there is entirely accurate.
Having used Claude Code and Cursor, both of which operate on my local fs (tree-based), I'm curious if changing the underlying fs design is in the cards for these kinds of tools.
The vector stores that these tools use certainly function as an index on top of the raw files. So does agentic search augment this index? Or obviate it?

English

launching @waldium on product hunt
built an AI that:
→ researches trending topics
→ generates content
→ publishes to your blog (hosting included)
→ optimizes for AI search
CI/CD for your content
support us: producthunt.com/products/waldi…
@ProductHunt
English

Greptile has raised $25M to Kill The Bug.
The round is led by Benchmark with @ericvishria joining our board.
Today, code is written by humans and a variety of coding agents like Devin, Claude Code, and Cursor.
Greptile serves as the independent and universal code review layer.
This month alone, Greptile reviewed 500M lines of code for top companies like Brex, Substack, PostHog, Bilt, and even YC’s internal software team, helping prevent 180,000+ bugs.
Alongside our Series A - we’re excited to announce Greptile v3 - a brand new agent architecture capable of catching >3x more critical bugs than Greptile v2. Available now to all users. 🧵
English

@andrei_serban @ThriveCapital @scale_AI @tryramp @webflow congrats to you and the team! @andrei_serban @sharedalbums
English

All companies run on IT.
But almost all IT teams are underwater.
The ones that aren't run on Console.
Console raised a $23M Series A led by DST Global Partners and @ThriveCapital to help leading companies like @scale_ai, @tryramp, and @webflow automate 50%+ of their tickets.
English
Shivam Singhal รีทวีตแล้ว

Modern marketing can be reframed as a process of domain-specific training data generation whose primary purpose is to teach both human and agents how to model, reason about, and act in relation to your business. Every artifact.. web copy, documentation, sales decks, blog posts, support threads, etc functions as labeled examples in a corpus that defines the ontology of your company: what entities exist (products, features, roles), what relations connect them (pricing, workflows, integrations), and what distributions describe them (use cases, success rates, benchmarks).
English

@lennysan Writing technical blog posts. With architecture diagrams (mermaid), direct code snippets, create sample/test endpoints for getting data + charts.
English

We’re live on @eventbrite with our first webinar!
Catch @amruthagujjar talking about AI Content Engineering for Demand Generation
eventbrite.com/x/ai-content-e…

English

Excited to announce that @sola_ai has raised a $17.5M Series A led by @a16z with support from @Conviction @ycombinator, bringing total funding to $21M 🚀
From the start, we set out to reimagine human-AI interaction to push the boundaries of process automation. Our agents watch how people do tasks on-screen, then handle those tasks automatically, even in legacy tools.
English

I’m excited to finally share blogwald, something we’ve been burning the midnight oil to put out (put on?).
Blogwald helps businesses understand and optimize their content for AI discovery and citation.
- Auto-generated llms.txt & llms-full.txt endpoints so LLMs ingest structured, meaningful markdown.
- Crawlability analytics to see exactly how AI agents interact with your content.
- Developer API for scalable, volume publishing.
As agents become primary content consumers, this is the next layer of content creation, visibility and optimization.
Try it today: blogwald.com/dashboard
English
Shivam Singhal รีทวีตแล้ว

We built a system that detects highly complex objects NO vision model can find—introducing tool use for vision. 🧵
Say you wanted to detect for the @ycombinator logo in this image. (▶️ see step-by-step thinking)
Using our solution, it's able to detect the logo perfectly, *zero-shot* with just a single prompt!
Try it out: spatial-reasoning.com
Code: github.com/QasimWani/spat…
1/10
English




