Nex AI

Hey LinkedIn! I'm going to be in Vietnam for Nex AI the following week! Would love to meet anyone who is a B2B Operator / Conglomerate who is in or has some experience or connections preferable in manufacturing, verticals such as semiconductors, precision engineering, and aviation. (If your a manufacturer, I can do a LIVE free demo with your data on the spot for immediate value) Would be more than willing to share insights about Singapore or any other market I have experience in. Happy Friday! - Jon

Last week, I had the opportunity to demo live with Rajiv Ayyangar, the CEO of Product Hunt! 🚀 I still remember Dexter Ligot-Gordon being worried since I said my demo was super scrappy prior, but it turned out to be a concise and easy to understand demo! I have no idea how I pulled it off on one-hour of sleep and a shipped untested software update on my flight. Rajiv Ayyangar has been immensely helpful in providing exposure to the things we are doing at Nex, and connecting me directly with Tom Blackman to better navigate the enterprise sales cycle. For context Nex AI is in the unsexy space of AI - manufacturing. We're helping companies transform emails into structured data for ERP integration, saving dozens of hours spent each week on manual data entry and reconciliation. Would love to chat if you would like to find out more! Special thanks to the Swarm Team Ashley Ko Dexter Ligot-Gordon Alexis Collado Chito Lapitan for organizing the enough and another shoutout to the other founders who showcased their product as well: Vishal Parpia Kenneth Lou Kelly An Trung Vu Richard Qi Zhi. Stay scrappy and ship fast!

Welcome to Trump 2.0. Now that Trump has won decisively, Republicans are likely to control both the Senate and the House. Here's what you need to know in 60 seconds: 1. With Republicans likely winning both houses, markets are focused on two main indicators: tax cuts and tariffs. - Likely that US stocks and crypto will grow (Self-Explanatory) - Tariffs will likely affect China, Taiwan, and the broader ASEAN region especially on semiconductors. Trump has proposed 10-20% on all imports and nearly 60% on imports in China. Any level of tariffs could slow global economic growth. - Tax cuts are likely to be introduced for corporations, and while this could increase corporate investment (FDI as well), that would mean lesser budget available. TLDR: The new policies are likely to be inflationary could add a layer of uncertainty. (While stocks are rising in general, indicators such as unemployment signify rising concerns in the labor market, especially with the recent change in the calculation of the indicator) 2. How will tax cuts affect monetary policy and bonds? - Currently it looks like 25 bps rate cuts are expected. Rate cuts lower borrowing costs, which can support stock growth if the economic outlook is positive. - The market has already factored in this inflationary factor, with the 10-year Treasury yield rising from 3.6% in September to 4.4% now, reflecting anticipated policy changes and reaching levels from late 2023. - The Core PCE Index, the Fed's inflation measure, has dropped from 3.5% (Q4 2023) to 2.7% recently, showing inflationary pressures may be easing. - Next year's rate cut will likely be in March, allowing time to assess the economy and effects of new policies. TLDR: Short-term bonds can reduce sensitivity to interest rate changes. 3. How does Trump 2.0 affect tensions with China? - China has already been considered a competitor with the US, so it is likely that tariffs have already been factored into market price. - Tariffs may serve more as leverage than a penalty, especially as China shifts from an export-led to a consumption-led economy. TLDR: Domestic policies may be more important for the Chinese market and is substantial stimulus is introduced, Chinese stocks will likely see even more upside. 4. How does this affect the IPO market? - Strong IPO performance in 2023 has helped revive the market after a sharp downturn from the highs of 2021. - This year, IPO fundraising has surged by 64% and 2025 could continue the momentum if Republican policies, including potential support from Trump, encourage more companies to go public. TLDR: A strong 2024 IPO market could continue, but new tariffs may slow listings, especially from Europe and China.

Hey LinkedIn! I'm going to be in Bangkok for Nex AI the following week! Would love to meet anyone who is a B2B Operator / Investor / Conglomerate who is in or has some experience or connections preferable in manufacturing, verticals such as maritime, semiconductors, precision engineering, and aviation. Would be more than willing to share insights about Singapore or any other market I have experience in. Happy Monday! - Jon (Picture from Songkran Festival)

There's been a big shift towards nuclear energy as Google, Microsoft, & Amazon all make deals to acquire nuclear plants to power existing and new AI infrastructure and data centers Here's what you need to know in 60 seconds: 1. Which tech giants are acquiring? - Google has partnered with Kairos Power to utilize small modular reactors (SMRs). These usually provide clean energy of up to 300 MW per unit. The deal is projected to deliver 500 MW of carbon-free power by 2035. - Amazon has partnered with Energy Northwest to develop 4 SMRs, aiming to generate up to 960 MW in the final phase. They are also partnering with X-Energy to enable future projects to provide nearly 5 GW (1000 Megawatts) of nuclear power. Amazon also had an existing deal with Talen Energy to buy a 960 MW nuclear data center. - Microsoft has restarted the dormant Three Mile Island reactor through a partnership with Constellation Energy, providing 835 MW. Microsoft is also looking to explore fusion energy through a partnership with Helion Energy. 2. Why is there a sudden race to nuclear? - Data centers require a ton of clean energy. Most companies have ESG requirements that need to be completed by 2030 or 2035, but currently renewable energy methods are lackluster. For example, we don't always have wind or solar 24/7. - Our existing infrastructure isn't enough to power super computers or train models. For reference, GPT 3 required nearly 1287 MW/hr to train, about 120 times the amount of power a household uses a year. OpenAI's latest development Stargate, requires nearly the same amount of power consumed regularly of the entire New York. We'll only get more energy-intensive from here, especially with the rise of Quantum Computing and the need for more qubits to stabilise calculations. - We can't afford to divert all power to new data centers. The reality is that we need power for existing processes such as irrigation and residential properties. Chips such as Rubin, set to come out in 2026 will require even more power and more MW(e). 3. What this means for consumers/companies - Consider acquiring nuclear/uranium stocks. They have generally been on a rise, and should hold/grow its value over the next few years. - If your planning to finetune/train models, definitely take into account optimizing your training and inference processes to reduce energy consumption. There's no guarantee that the SMRs will be approved and there aren't a ton of instances of SMRs actually working. Regardless, energy is likely to get more expensive. - Models will definitely improve for better enterprise/consumer applications. Lesser errors, higher accuracy, and more configuration options will probably be available in the coming years.

Evening network! I’m currently exploring the maritime/shipbuilding space, diving into helping procurement/supply chain teams better manage inventory/part visibility via emails. Specifically, I'm currently transforming messy, unstructured emails into a format your ERP system can recognise, providing end-to-end automation on tasks such as RFQ or purchase order invoicing, saving hundreds of hours each week. If your in this space I'm keen to understand: 1. How do you currently build a ship 2. What are the current pain-points and how do you solve it today 3. What low-hanging use cases provide immediate value Anyone willing to hop on a quick call or grab a coffee in Singapore? Would love to understand your industry better, and potential help you with your issues. Would appreciate a bump in the algorithm or tagging anyone relevant.

Hey LinkedIn! I'm finally back after touching grass for a couple weeks. Here's my TLDR thoughts on the current AI landscape. 1. Major Ecosystem Players & Tech Giants The "political" system at OpenAI has been rather rough with the lack of a clear leadership, mainly due to the concern that OpenAI does not have the best interests of the public in terms of ethical and safe AGI advancement. That said, new talent such as Microsoft's VP of GenAI Research fill these missing spots to compete with major rivals such as Anthropic. The "GenAI" landscape can be classified into mainly existing ecosystem capitalisation or pushing their own internal AI agenda. The key to remember is that its not just the "best" performing model that really matters, but more on the extent of adoption whether B2B or B2C. OpenAI is focusing on a more consumer ecosystem approach, entrenching itself in Microsoft and Apple. Anthropic is pushing its partnership with Amazon to appeal more towards developers developing GenAI applications, which has been especially useful due to Anthropic's large context limit. Google, Meta, Adobe, and many more giants are pushing their own agenda, some with more success than others. In terms of startups, the trend is to focus on developing product for a niche specific audience - in general avoid developing competing models with better benchmarks, but rather focus on practical real-world applications or data-processing layers before the GenAI layer. 2. GenAI Adoption in Companies GenAI at the current stage is more an operational efficiency benefit rather than an increase in revenue. Most companies are rather "confused", with self-appointed GenAI leads that don't quite know what is the right solution to adopt. For example, some medical companies look for some "crazy" good AI solution that would allow them to process private unstructured data. The reality is that they could do it themselves via OpenAI Azure for a fraction of the cost. The main issue is that companies are jumping towards a GenAI driven strategy without even having a digitization strategy at all. It's like learning to run before you can walk. It doesn't really matter if your a "wrapper" or develop your custom model. At the end of the day, the business metric associated with it matters the most. Note that IT-based buyers tend to be the most enthusiastic since they are technology enthusiasts in the first place, but that comes at an inherent cost of long sales cycles due to strict data privacy and governance. 3. Infrastructure Development for AI Infrastructure is moving sooooo fast. The biggest issue is that the more manufacturing giants ship new chips for better performance, the more up to date infrastructure is needed. That means better cooling systems and better voltage management, which is a challenge given 1-2 year sales cycles and lead times. Google has recently turned to nuclear energy to power data centers. I ran out of words, let me know if you want a Part 2!

Over a series of 45 days, my series of documenting Nex AI on a day-to-day basis generated around ~150,000 impressions by posting daily. A lot of people have been asking me to continue my Day _ of reaching $100K MRR with Nex AI as apparently it provides a daily "digestible" that they can read about running an early-stage startup. After testing this for a while, here's why its NOT great unless your in a sales/self-serve/coaching software business. 1. It brings tons of eyeballs, especially investors and potential customers, but not if your client is "old-school". For Nex, our target audience are manufacturing firms that have complicated procurement processes via email. They don't use LinkedIn. 2. Website tracking (i.e. Inbound-Led Outbound via LinkedIn) doesn't quite work for traditional industries. Website tracking we find works best with targeted cold emailing or cold calling, and its much easier to reach them. 3. The digitization process for manufacturing firms is complicated. A ton of the older industries (maritime, industrial engineering) are against tech adoption. Some even use Excel to keep tracking of procurement and sales, and their hesitation means a more "personal" approach is needed i.e. a warm introduction. Thinking of shifting content towards a "thought" leadership approach, let me know what you think! (Would love anyone's thoughts to know what LinkedIn strategies have worked for them especially when targeting the more traditional industries.)

Nothing huge but celebrating the small wins! Nex AI is finally focusing on SEO!

Closing sales is harder than ever in 2024. I don't believe SaaS is dying, but a bloodbath is beginning. B2B SaaS is rapidly evolving with various GTM strategies. (inbound-led outbound, UGC, intent-driven outbound) Businesses are copying everyone's GTM strategies, but the truth is you shouldn't copy them since every product is unique and different. Therefore, I'm launching a new special project with Nex AI. Introducing Project 250. Project 250 is a "blog" and goal to secure 250 B2B contracts for Nex by the end of the year. I've been experimenting with GTM strategies for over a year now, and I'm putting them to the test. How fast can I scale and sell to ICPs quickly and effectively as a single person sales team. If you'd like to see how I do it, critique it, or even offer some suggestions, give me a follow or connect with me!