Arjun Prabhulal

@GoogleDevExpert Cloud & AI | , | Opinions my own

[Arjun Prabhulal @ArjunPrabhulal]

How I built semantic search over 300 million plus academic papers, served from one CPU server.

GPU ingestion, FAISS IVF-PQ, INT8 re-scoring, a separate title lookup, and measured latency: about 240 ms for a new query, about 40 ms when repeated.

What worked and what didn't:
https://t.co/bZxF8BeW9Z

[Omar Sanseviero @osanseviero]

Introducing https://t.co/4oowUo7AQT

The new hub for Gemma, including

📚Inference and training guides
🧠 Deep visual architectural guides
‍🖼️ Online demos, even running models in the browser

And a lot more to come, check it out!

[Arjun Prabhulal @ArjunPrabhulal]

Interesting read especially #18 agent insurance is coming

[GREG ISENBERG @gregisenberg]

I spent 48 hours in SF hanging out with billionaires, data labs and AI founders and execs running $1B to $100B companies.

My observations:

1. Sooo MANY stories of data brokers making like $2M a WEEK selling company data to labs. I can't tell if it's the beginning or a bubble, and I kept wondering which niches are left. Digging into it actively.

2. At dinner, someone asked the table, "If a new model drops next month, does your company get better or worse?" HALF the table went quiet! I think that's the best question to ask about any AI startup right now.

3. The bar people talk about now is hitting $1B in revenue in 12 months (I guess that's the new unicorn?). What I didn't hear much about is retention. AI revenue can come in fast and leave fast, and I think we're going to see a lot of stories of AI companies with huge revenue and terrible retention.

4. It's pretty clear we're living through the reinvention of the computer. The model is the CPU, the harness is the operating system, and skills and plugins are the apps. Thinking about it that way makes it easier to see where the whitespace is.

5. We're maybe 12 months from an agent that can watch you work for a week and then do your job without any instructions. The screen recording plus agent memory plus local model combination makes this possible right now.

6. Agent harnesses feel like the new GPT wrappers, in a good way, especially vertical ones. The best teams I talked to treat the model as swappable. One founder walked me through routing different models to different jobs: one for taste and visuals, a cheaper one for the everyday stuff, another for text.

They use prompts they can move across models over fine-tuning, and A/B test the output on what users actually do with it: do they edit it, export it, share it? A vertical harness is basically four things: the connectors for that industry's data, evals written by people who know the work, rules for what the agent can and can't touch, and a clean screen for a human to review. The model is maybe 20% of it.

7. There's a lot of reverse engineering going on/cloning going on more than I've ever seen. People are decompiling software and rebuilding it with agents, and someone showed a suite of like 10 apps that are worth $5B+ each all that he cloned open source. Me and everyone are still thinking through what it means when software gets this easy to copy.

8. My guess is the value moves to data. If the software can be rebuilt quickly, what's worth paying for in a legacy SaaS company is the years of customer data and workflows inside it. Some SaaS companies are secretly data companies.

Gets me thinking about how do you truly value data for this saas companies? Like if we were buying these dying saas companies at 2x ARR before (as example), maybe there is a better metric. Idk, just thinking out loud here.

9. It feels like a good chunk of legacy software won't make it to the agentic era, especially anything built around people clicking through a lot of screens.

10. Every company I talked to wants to pipe its internal data into one place and expose it to agents through MCP. Then they look at the data and realize it's a mess: five versions of the same customer, old Slack channels, PDFs nobody can search. Cleaning that up feels like a big consulting opportunity!

11. A lot of founders are building the basic building blocks for agents: APIs, data layers and tools. Some of the companies I saw barely have a UI because the main user is an agent. I really believe the startups that build primitives to this agentic era will do extremely well. Building blocks is the best way to think about it.

12. Labs can get plenty of training data, but it's harder to get real examples of agents failing inside companies. Whoever has those logs has something valuable.

13. Someone running a big consumer company told me the next fight is over memory. The model that remembers the most about you wins, and the smartest model matters less than people think.

14. Physical AI came up a lot. Astra I think was the first model that got people into AI can actually do CAD, and I think a lot of people are thinking what does vibe manufacturing really look like. The line I keep thinking about came from a robotics founder: the hardest problems in AI are deployment problems now, not research problems. Their robots work on their own, call a human when they get stuck, and every one of those calls becomes training data.

15. Cybersecurity companies are having a moment and are actually cool companies to build now, especially the ones that clean up after a breach. Every agent with access to your systems is a new door into your company, and a lot of those doors were left open.

16. Some startups are worth more dead than alive now. A shutdown company with 5 years of Slack, email and code can get paid for licensing all of it. I wouldn't be surprised if founders start factoring that into when they shut down.

17. People are starting to talk about monetizing the agent web. It feels really early, but when the most popular user of the internet is an agent, what startups should you be building?

18. I think agent insurance is coming. Once an agent makes an expensive mistake, insurers will want audits before they cover anyone.

19. Several people said the hire they want most is someone with taste who can write evals. The models are getting good at generating ideas, so the hard part is judging which ones are good.

20. New trend I observed: startup raises VC, uses venture dollars to become a creator, startup fails, founder falls back on being a full-time creator and incubates other products bootstrapped.

21. Getting SIGNIFICANT distribution is HARD right now. Founders are sponsoring buses, buying billboards like crazy and throwing parties with famous DJs to get noticed. Kinda feels dotcom era in that sense.

Attention is what's scarce! The growth guy going viral sharing his UGC strategy from Wispr Flow is a good example. It's the sauce everyone wants, and I truly believe there are probably only 50 people on the planet who know how to scale these types of businesses efficiently in this era.

Always good to get that dose of SF. I felt sooo lucky to have such an incredible trip during such an incredible time in building businesses. Surreal in so many ways.

Happy to be home and locked in.

Until next time!

[Arjun Prabhulal @ArjunPrabhulal]

https://t.co/OMwtwdvD8N reader is now open source.

PDFs to Markdown, HTML or JSON on your computer: headings, tables, charts as data, OCR. Use it as a CLI or MCP server.

https://t.co/tEKuw2zGKy: 65.0 (leaderboard PR submitted)
Leaderboard: Azure 59.6 · AWS Textract 47.9

https://t.co/H28Eie0CLQ

[Arjun Prabhulal @ArjunPrabhulal]

@arpit_bhayani I think our cognitive ability to ask questions, and to think will slowly diminish.

[Arjun Prabhulal @ArjunPrabhulal]

@trq212 Love this. I built a public version for AI news that runs itself: every day at 7 PM ET, headless Claude Code picks up what shipped, writes it up with the official source, checks it and deploys. https://t.co/h84f0N0ML1

[Atlanta Developers' Conference @ATLDevCon]

Speaker Spotlight: Arjun Prabhulal, Google Developer Expert!
🎤 From Spec to Shipping: Building AI Agents with Google ADK and Antigravity
Learn a spec-driven approach to building, testing, and shipping AI agents.
📅 Oct 17 | Alpharetta, GA
🎟️ https://t.co/TGho9R8RDY

[Logan Kilpatrick @OfficialLoganK]

Introducing Gemini 4 Argon, our new frontier model, rolling out to cyber defenders starting today, and more widely as soon as possible. I am really excited by the progress we have made here. Argon is priced at $2 in and $10 out during introductory pricing!

[Arjun Prabhulal @ArjunPrabhulal]

Like this new feature from @claudeai Code’s with spawning multiple agents in parallel as background tasks.

May be I am noticing this first time

[Arjun Prabhulal @ArjunPrabhulal]

@Muse Not so great experience with Muse Power $50/month , frequent 429 rate limit within 2 mins of usage

[Google Cloud Tech @GoogleCloudTech]

https://t.co/IFJVYb9Qfm

[Google Cloud Tech @GoogleCloudTech]

https://t.co/K0b9bjXfCr

[Arjun Prabhulal @ArjunPrabhulal]

Productive weekend as I finally attempted to build a full-blown product with 60+ features as side project

@claudeai - Product design, PRDs & feature-gap analysis, Browser Testing & validation loop to DeepSeek Harness
@GeminiApp - Deep research & code reviews
@deepseek_ai Harness - Coding & Implementation

Idea → Design → Build → Test → Product with just less than $100

#AIFactory #Claude #Gemini #DeepSeek

[Arjun Prabhulal @ArjunPrabhulal]

In the next few months, I believe we'll see the AI ecosystem move faster in three areas

Agent Harnesses,
Context Layers ( in Enterprise), and
AI Factories (moving beyond AI-DLC).

Open weights will get better and the shift will be infrastructure around them.

[Andrew Ng @AndrewYNg]

New: A map of the most important skills in AI Engineering. https://t.co/VVkn1Dqp1N

[Nilay Coskun @nlycskn]

Google's official course for vibe coding is live!

You will learn lots of practical AI skills you can actually use day to day..

aaaand receive Google AI Professional Certificate!

Check it out! https://t.co/QHUf3VmkL4

#BuildwithGemini #vibecoding

[Vercel @vercel]

Introducing Agent Plugins, an open standard for extending agents.

Supports Agent Skills and MCP, with more to come.

Built in collaboration with: @awsdevelopers, @code, @cursor_ai, @github, and @openaidevs.

https://t.co/duFCQqigZD

[Agentic AI Foundation @AgenticAIFdn]

A much needed open standard for agent interoperability is here! 🎉

Agent Plugins gives Agent Skills and MCP servers a shared package format, so developers can build once and use the portable parts across compatible agent clients.

The standard was developed by representatives from Amazon, Cursor, Microsoft, OpenAI, and Vercel.

Hear from the Agent Plugins Technical Steering Committee about how the standard works and what it means for the agent ecosystem 👇

https://t.co/s0VPcItcHh

(note that the Agent Plugins is independently governed and is not an AAIF project)

[Aravind @aravind]

34 mins of concentration on what Krishna says can improve your thinking, finances, life and make you a Jaganathan.

[Thariq @trq212]

We removed ~80% of the Claude Code system prompt for our newest models, this is what we've learned about writing system prompts, skills and Claude.MDs for them. https://t.co/6DZwSrZjE9