Raghav
11 posts

Raghav
@NonDualistCoder
Code x consciousness. Polymath. Law, Metacognition, Agentic AI, Math, Materials Science. @LBS grad. Scaled Decacorns.
Remote Inscrit le Ocak 2025
63 Abonnements0 Abonnés

@ParthJadhav8 This has great potential and is getting a public release very soon. It supports all desktop platforms. I am contributing as well. @FreestyleVoice
freestylevoice.com
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Woke up today, made breakfast for my family, vacuumed the whole house and then I open X and found out it's blown up. 😅
Thank you @theo 💜
ps: Lots of cool stuffs are coming in the upcoming weeks! So stay tuned.
Theo - t3.gg@theo
First donation is up, just gave $2,000 to @heyandras to support open source alternatives to Codex App and Claude Desktop 🫡 Also pumped that this can help with Coolify, the coolest open source hosting option for people exiting platforms like Vercel
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Raghav retweeté

Some news: This week I am starting at @GoogleDeepMind as Director of AGI Economics on @shanelegg’s team. I will be joining the other amazing cross-disciplinary scientists researching AGI there.
My team will study how frontier AI could reshape the economy: what happens to work and labor, how wealth and power are distributed, how institutions adapt, how AI agents shape markets, and what kinds of models can help us reason clearly about futures that may look very different from the past. I’m incredibly excited to help build this research agenda.
If AGI changes how society operates, economics is going to be critical for shaping our shared future. Many more announcements soon.

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After 200+ apps shipped with Lovable — we collected every prompt that cut build time by 75%.
These are the same prompts we used to help founders:
- Ship MVPs in 2 weeks using @lovable
- Land their first paying users within 30 days
- Automate full product flows without writing a single line of code
- Design products that look and feel world-class from day one
I’ve consolidated the 8 best into one actionable doc.
Follow + comment “Prompts” and I’ll send it over DM.
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Raghav retweeté

Everyone's losing their minds over OpenAI's Agent Builder.
I spent the last 24 hours testing it and analyzing community reactions.
Here's what nobody's saying about the $4B "democratization" play that's actually just vendor lock-in with a canvas:
The hype: "Agent Builder democratizes AI! No-code revolution! Zapier killer!"
The reality: It's a drag-and-drop builder for developers that's locked to GPT-only models.
That's not democratization. That's an ecosystem play.
I tested it against n8n, Make, and Flowise.
Complexity level: Same (if not slightly higher)
Integration flexibility: Worse (thin node sets)
Model options: One (GPT only)
Migration benefit: Zero
The GPT-only lock is the real killer.
I use Claude for complex analysis. Gemini for specific tasks. GPT for... honestly, the braindead simple stuff.
Being forced into one model is like telling a carpenter they can only use hammers.
Community reactions are split exactly how you'd expect:
Positive takes:
→ "Built a buyer agent in hours, 70% iteration reduction!" (Ramp)
→ "Game-changer for prototyping" (@piotrmacai)
→ "Seamless OpenAI integration" (obviously)
Reality checks:
→ "UI too complicated, features basic" (@wyndomb)
→ "Not autonomous, just rigid scripts" (@Vivek_5151)
→ "No migration incentive" (me + many others)
The pattern I'm seeing: Great for prototyping IF you're already deep in OpenAI's ecosystem.
Not great for: Production systems, multi-model workflows, anyone using n8n/Make successfully.
Here's what the docs won't tell you:
✓ Fast prototyping (true)
✓ Good for demos (true)
✓ Enterprise features (true)
✗ Vendor lock-in risk (ignored)
✗ Limited node library vs competitors (ignored)
✗ Still requires technical knowledge (ignored)
✗ Not actually "no-code" for non-technical users (ignored)
The "democratization" claim falls apart under scrutiny.
Community feedback shows it's "too technical for teams" and "missing features for production-scale."
It's low-code for developers, not no-code for everyone.
Real talk: If your workflows already work in n8n or Make, save yourself the migration headache.
The math doesn't add up:
→ Rebuild all integrations
→ Learn new platform
→ Lock into single model
→ Hope features catch up
For what benefit? "OpenAI native" that you can already get via API calls?
Where Agent Builder actually makes sense:
1. You're already 100% in OpenAI ecosystem
2. You need fast prototyping for demos
3. You're building customer service bots (their sweet spot)
4. You don't care about model flexibility
Everyone else? This is a solution looking for a problem.
The controversial truth: Agent Builder validates visual agent building as a category, but it's not the revolution they're selling.
It's an incremental improvement for a narrow use case wrapped in "democratization" marketing.
The winners: OpenAI (ecosystem lock-in), enterprises already using their stack
The losers: n8n/Make users expecting a reason to switch, anyone needing multi-model flexibility
My take: Good prototyping tool. Not worth migrating for. Overhyped by 3-5x.
The real opportunity isn't in the tool itself.
It's in the $400M-$4B consulting market that opens up when everyone realizes prototyping ≠ production deployment.
Stay where you are. Let others debug the hype cycle.
Your existing automations work. Your team knows the platform. Your models are flexible.
"OpenAI native" isn't a feature when you can call their API from anywhere.
Agree? Disagree? Drop your take below.
I'm curious if anyone found a compelling reason to migrate that I'm missing.
OpenAI Developers@OpenAIDevs
Introducing AgentKit—build, deploy, and optimize agentic workflows. 💬 ChatKit: Embeddable, customizable chat UI 👷 Agent Builder: WYSIWYG workflow creator 🛤️ Guardrails: Safety screening for inputs/outputs ⚖️ Evals: Datasets, trace grading, auto-prompt optimization
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