A

anjankatta

I analyze how AI and tooling lower friction in hardware prototyping, supplier discovery, and sourcing — and what that means for related public equities. Active on X as @anjankatta.

Trust score
0 / 100
Track record
0 / 100
Thesis calls
3
Evaluated calls
3
Average return
-1.73%
Win rate
33%

Past bets that played out

Repeated thesis: AI tools are making hardware development more 'open source' by surfacing suppliers, materials, and manufacturing methods, which can reduce prototyping friction and change competitive dynamics for hardware-related companies.

AVTrightbacktest PROMOTE

The source argues that AI tools make hardware development “more open source” by making it easier to discover suppliers, materials, and manufacturing methods, potentially lowering friction in hardware prototyping and sourcing.

Mentioned: May 24, 2026, 6:55 PM EDTConviction: 32 / 100Return: +41.34%Observed price: $89.12
Source: Hardware has always been hard because it isn’t open source in the way software is. You have to network, ask around, t...
DSGXwrongbacktest DEMOTE

The source argues that AI tools make hardware development “more open source” by making it easier to discover suppliers, materials, and manufacturing methods, potentially lowering friction in hardware prototyping and sourcing.

Mentioned: May 24, 2026, 6:55 PM EDTConviction: 36 / 100Return: -24.98%Observed price: $70.58
Source: Hardware has always been hard because it isn’t open source in the way software is. You have to network, ask around, t...
ADSKwrongbacktest DEMOTE

The source argues that AI tools make hardware development “more open source” by making it easier to discover suppliers, materials, and manufacturing methods, potentially lowering friction in hardware prototyping and sourcing.

Mentioned: May 24, 2026, 6:55 PM EDTConviction: 44 / 100Return: -21.55%Observed price: $238.23
Source: Hardware has always been hard because it isn’t open source in the way software is. You have to network, ask around, t...

What this channel is watching now

Primary tickers of interest: ADSK (avg conviction 0.44), DSGX (avg conviction 0.36), AVT (avg conviction 0.32). Coverage emphasizes AI-driven supply‑chain and prototyping effects more than company-specific deep dives.

Latest videos and market context

No video content is listed in the available record. Recent source items are primarily short analyses or requests for full-text input to extract theses and tradable ideas.

Hardware has always been hard because it isn’t open source in the way software is. You have to network, ask around, t...

May 24, 2026, 6:55 PM EDT

The source argues that AI tools make hardware development “more open source” by making it easier to discover suppliers, materials, and manufacturing methods, potentially lowering friction in hardware prototyping and sourcing.

https://t.co/DPhZzbTeGH

May 21, 2026, 10:25 PM EDT

I can’t access or expand t.co links from here (no browsing), so I can’t see the article/content behind https://t.co/DPhZzbTeGH. Paste the full text (or key excerpts), or upload a screenshot/image of the page, and I’ll extract actionable theses, affected tickers, and tradable ideas with horizons.

https://t.co/H3ESBMvcdD

May 19, 2026, 12:42 PM EDT

I can’t access or open the t.co links from within this chat, so I can’t read the underlying article/post to extract theses or tickers. Paste the text content (or screenshots) and I’ll process it immediately.

https://t.co/DHLXly56a9

May 17, 2026, 6:13 PM EDT

I can’t access or open the t.co link content from within this chat, so I can’t extract theses/tickers from the article yet. If you paste the title + body text (or screenshots), I’ll score actionability, derive bullish/bearish theses, map beneficiaries/risks to tradable tickers, and output trade ideas with horizon/direction.

Proof-backed call history

Published three evaluated recommendations with an average return of -1.73% across 3 items and an observed win rate of 33.33%. Recommendations and standout calls consistently highlight how AI reduces sourcing friction in hardware development.

AVTrightbacktest PROMOTE

The source argues that AI tools make hardware development “more open source” by making it easier to discover suppliers, materials, and manufacturing methods, potentially lowering friction in hardware prototyping and sourcing.

Mentioned: May 24, 2026, 6:55 PM EDTConviction: 32 / 100Return: +41.34%Observed price: $89.12
Source: Hardware has always been hard because it isn’t open source in the way software is. You have to network, ask around, t...
DSGXwrongbacktest DEMOTE

The source argues that AI tools make hardware development “more open source” by making it easier to discover suppliers, materials, and manufacturing methods, potentially lowering friction in hardware prototyping and sourcing.

Mentioned: May 24, 2026, 6:55 PM EDTConviction: 36 / 100Return: -24.98%Observed price: $70.58
Source: Hardware has always been hard because it isn’t open source in the way software is. You have to network, ask around, t...
ADSKwrongbacktest DEMOTE

The source argues that AI tools make hardware development “more open source” by making it easier to discover suppliers, materials, and manufacturing methods, potentially lowering friction in hardware prototyping and sourcing.

Mentioned: May 24, 2026, 6:55 PM EDTConviction: 44 / 100Return: -21.55%Observed price: $238.23
Source: Hardware has always been hard because it isn’t open source in the way software is. You have to network, ask around, t...

About this channel

I focus on actionable research at the intersection of AI and hardware: how new tools change supplier discovery, materials selection, and manufacturing methods — and which public companies could gain or lose as a result.

Subscribersn/a
Videosn/a
Win rate33%
Average return-1.73%

@anjankatta

Unlock the full track record

Follow @anjankatta on X for short analyses and to submit article text or screenshots for extraction of theses, affected tickers, and tradable ideas with suggested horizons.