After more than two decades of investing...
I believe we’ve found the next big hidden opportunity:


Most LPs exploring venture capital funds as an investment vehicle are concerned with media sentiment.

"Capital at risk"
"Growth at all costs"
"Long-term"

The numbers don't lie. If well managed, venture investing reaps very attractive ROI versus most other alternatives.

And, you won't even need to find the next unicorn to do that.

Today, sustainable, sticky growth is the holy grail for any investment office looking for longevity with attractive returns.

Some years ago my partner, Murli, and I started Tin Men Capital in pursuit of that.

Our fund's unique focus:
- B2B and Enterprise Tech Startups
- With a strong focus in Southeast Asia
- Who are in Series A stage and beyond

Our thesis:
SouthEast Asia's legacy industries are still largely undigitised.
B2B tech in large TAM > High-gross margins > Sticky recurring revenue > Quicker pathway to profitability

We've already proven that these ideas our sound with measured results from our inaugural fund.

Family offices and institutions that work with us appreciate our ethos in running the fund:

⚙️ DISCIPLINED DEAL-SOURCING : 
Carefully scrutinising every deal for the right valuations, founder mix, and expertise. No exceptions.

⚙️ HIGH-CONVICTION: 
We only invest in a handful of teams that apply. Sounds counterintuitive, but It's seeing above-market returns with below-average failure rates.

⚙️ EXPERIENCED B2B OPERATORS AT THE HELM: 
Murli and I bring collectively more than 40 years of experience in investing and management, having sat on boards and brokered large M&As. Our thoughts have also been featured on TechInAsia, Peak Magazine, and more.

Some of our portfolio companies:

🔵 Hubble (Series B)
Resource management platform for parties in the construction value chain to track and optimise processes

🔵  Zipline (Series A)
Australia's #1 workplace management platform for the aged care and health sectors

🔵  GlobalTix (Series A)
Software and marketplace software for tourism attraction operators and travel product distributors 

We’re always on the lookout for new partners and startups to join us.

If keen to chat, shoot me a DM/email or head over to our website to drop us a line.

Jeremy Tan

Raj Goodman Anand

Chief Product

Founder of Goodman Lantern (UK) | CEO at AI-First Mindset (UK) | President of EO BM | AI Speaker | AI Workshops

I grew up believing there was one safe path: study hard, get a good degree, find a stable job, follow the plan. Getting into IIT Delhi felt like proof I could do hard things. But I soon learned that being “qualified” isn’t the same as being “aligned.” I wanted to research computer science, not general engineering, so I chose a different road.In my early twenties I moved to the UK and started my first business at 22. Around the same time I began my PhD thesis in artificial intelligence. That was two decades ago. Since then I’ve watched AI fail, evolve, and restart many times. The lesson that stayed with me was simple: technology only creates value when complex ideas are translated into practical, commercially viable strategies.I later built and exited Spicy Corporation, my first full business cycle, and at 28 became Global Innovation Director—and then CEO for the UK and Asia—at the 700-person Actualize Group, the youngest and only non-Spanish CEO.Over the years I’ve launched and scaled multiple ventures, including GoPinLeads, an AI-powered lead generation platform that helped organizations drive measurable growth and efficiency. I’m also the founder and CEO of Goodman Lantern, a B2B content marketing agency serving innovative businesses across five continents.I remain close to the frontier of AI as an investor in OpenAI, xAI, and Anthropic, and as author of The AI Era: Adapting &amp; Thriving. My work has been recognized with BusinessWeek Europe’s Young Entrepreneur (2007) and Revolution Magazine’s 50 Most Influential People in Digital (2009). I’ve spoken at the Foreign &amp; Commonwealth Office, British Library, and London School of Economics, and been featured in The Telegraph, The Guardian, BusinessWeek, and The Observer.Today I work with leaders of traditional businesses who want results, not hype. That’s why we built AIFM OS — the AI-First Mindset Operating System: a practical framework that integrates AI into real workflows to save time, improve decisions, and reduce manual dependency.Through AI-First Mindset®, we support organisations across the Indian sub-continent, South East Asia, East Africa, and the Middle East with:✅ AI operating model design✅ Workflow transformation✅ Leadership alignment✅ Practical AI adoption✅ Implementation sprintsMy focus is simple: helping traditional businesses become AI-first in practice.🔑 Join us: https://aifirstmindset.ai/agentic-operating-system/

Founder & CEO

Goodman Lantern is an award-winning content marketing agency specialising in content writing, strategy, design, motion-graphic videos, and SEO services for industries such as technology, telecommunications, and financial services.

We're a fast-growing business that serves clients across five continents. We help our clients establish themselves as thought leaders in their industries with storytelling that inspires and converts. Our content allows them to build trust with their audiences to scale their businesses.

We've made it our Big Hairy Audacious Goal (BHAG) to create consistent, reliable, and fair income opportunities for women in marketing and tech. And along with our clients, we're already making great strides: 90% of our team members are women. Our ambition, however, is to ultimately make a difference on a global scale.

Are you keen to be a part of our success story? Our highly creative team members are experts at developing valuable content that speaks to target customers' pain points. So let's collaborate and create content that will grow your business.

Stop asking which AI is "the best."

Wrong question.

I use Claude for writing. Perplexity for research. Gemini for long videos. ChatGPT for quick answers. Midjourney for images. Cursor for code.

Different tools. Different jobs.

The people getting results aren't loyal to one AI. They're switching between five or six depending on what they need.

That's the actual skill now—knowing which tool for which moment.
Which ones are you using? Drop your stack below.

#AITools #ChatGPT #ClaudeAI #Perplexity #GeminiAI #ArtificialIntelligence #ProductivityHacks #AIForBeginners #TechTips #FutureOfWork #AIWorkflow #LearnAI

Best AI tools 2025, ChatGPT vs Claude, AI tools comparison, which AI should I use, Perplexity AI, Gemini AI, Claude AI, AI for productivity, AI tools for beginners, best AI for writing, best AI for research, AI workflow, AI tools tutorial, how to use AI, AI tips

Helping organizations build AI operating systems | Founder, AI-First Mindset®

Last quarter, I worked with the MD of a heavy equipment manufacturer who believed AI would make status reports clearer and give leadership better visibility into project progress, but while the dashboards improved and the data looked sharper, the actual profit margins did not improve because delays were still being identified too late to prevent cost overruns.

By the time problems appeared in reports, the financial impact had already occurred, and in 2026, with tighter compliance requirements and thinner operating buffers, that delay between issue and action is no longer affordable.

What has truly changed is not reporting quality but execution speed, because AI systems can now reallocate resources, adjust schedules, and flag bottlenecks immediately instead of waiting for weekly or monthly review cycles; in plant upgrade programs and supplier transitions, I have seen problems addressed at the point of occurrence rather than after escalation.

When corrective action happens closer to where the issue starts, delivery risk declines and cycle times shorten, since decisions are triggered by live data rather than by meetings or manual coordination.

The main weakness I continue to see is governance, because many AI agents operate on fragmented data sources without clear ownership of decision rights, which leads teams to override outputs they do not trust and reintroduce manual controls that slow everything down, creating a false sense of stability where dashboards remain green but margin pressure builds quietly underneath.

Two mistakes appear repeatedly.

The first is treating AI as an advanced reporting layer, because manufacturing projects depend on operational control rather than visibility alone, and insight does not prevent delay unless the system is allowed to act within clearly defined boundaries.

The second is deploying AI without defining who owns the decisions it influences, because manufacturing plants rely on accountability structures, and when escalation paths are unclear, agents can create conflicting actions that slow adoption and reduce confidence across teams.

If you are beginning this journey, start by mapping a single workflow where approvals consistently delay progress, such as change requests during shutdown planning, and introduce AI only where decision rules are already stable and measurable, while avoiding areas that depend on negotiation or human judgment.

 #AIInProjectManagement #AgenticAI #ExecutiveLeadership #FutureOfWork #OperationalExcellence0 #DecisionIntelligence #EnterpriseAI #ProjectGovernance #DigitalTransformation #AIForCEOs #BusinessExecution #AIStrategy

AI in project management now controls outcomes, not task..

₹2 lakh crore vanished from Indian IT yesterday.

Everyone's talking about the crash. Nobody's talking about the companies that are growing right now during the same news cycle.

I've spent the last six months watching this shift happen. The companies panicking are the ones who ignored the signals. The ones thriving? They changed their entire model before they had to.

This isn't about AI killing jobs. It's about business models that refuse to evolve.

Drop a comment if you're in IT or tech. I want to know what you're seeing on the ground.

#IndianIT #AIAutomation #ClaudeAI #TechLayoffs #FutureOfWork #AITransformation #TechIndustry #AIConsulting #DigitalTransformation #AIStrategy

AI adoption slows inside large organizations because leaders mistake ambition for readiness, which wastes capital and weakens trust. Running multiple AI initiatives at the same time raises coordination effort and slows decisions, which reduces real business output. Teams are expected to change how they work while still hitting short-term targets leading to quiet failure. Leaders who overlook this end up with sunk costs and slower core operations.

What is changing is that AI now requires sustained operational focus rather than short pilots because models affect workflows across the organization. This is happening because AI tools evolve faster than companies can adapt their ways of working. The result is fragmented adoption and falling returns when too many initiatives compete for attention.
This means: fewer initiatives executed deeply deliver more value.

Two takeaways for legacy business leaders

Parallel AI rollouts fail because organizations can only absorb one major workflow change at a time. This creates hidden capacity limits that stall execution.

Strong vendors do not fix weak integration because success depends on how work actually happens, not on the quality of the tool.

Start with one revenue-critical or cost-critical workflow and map decision handoffs before introducing AI, because clarity lowers the risk of failure. Avoid deploying AI where ownership is unclear or metrics are disputed, because automation amplifies confusion.

Using AI for appearances destroys value, while operating with AI requires focus and discipline.

#AIAdoption #AIReadiness #EnterpriseAI #OperatingModel #LeadershipExecution #DigitalStrategy #ChangeCapacity #WorkflowDesign #AIGovernance #BusinessOutcomes #AIReality #FoundersPerspective

This month, I’m heading back to Makati for EO Philippines to deliver the next session in their AI series: AI for Business Growth and Innovation.

We’ll explore how to use AI to find new market opportunities and redesign business models with intelligence at their core.

I am looking forward to helping our leaders in the Philippines, who have been so engaged and eager in every session so far, turn AI into measurable business growth. Growth backed by stronger decision-making, ready to respond agilely to any market shift.

I am also looking forward to reconnecting with the vibrant EO Philippines community and closing out this session with practical, hands-on execution that shifts AI from “another productivity tool” to a real competitive advantage.

To reserve a seat, or to connect while I’m in the area, leave a comment or message me directly.

#EOPhilippines #LeadershipDevelopment #AIForGrowth #AIWorkshop #AIFirstMindset

Three weeks ago, I had dinner with the COO of a forty-year-old industrial manufacturer. They were running five AI agent pilots in planning and procurement. None were live and yet plant managers were still responsible if something went wrong.

That’s the tension.

AI agents are starting to execute decisions, not just recommend them. Once they touch live operations, gaps in accountability show up fast, usually as margin loss.

Work is changing because cost pressure and speed expectations are pushing automation directly into shop-floor and supply-chain workflows. Agents don’t wait for approval at every step. Where delays once caused downtime, decisions now move instantly.

Ownership is changing too. When agents influence outcomes, fragmented governance slows everything down. I’ve seen security, IT, and operations debate boundaries while plants absorb the disruption. Companies with clear, unified control move faster and with less friction.

Durability matters. Unmanaged agents create spend spikes and inconsistent results. What works in a demo often fails when connected to ERP or MES systems. Discipline in deployment leads to predictable outcomes.

Responsibility also shifts. Once agents act on behalf of the company, they reflect its intent. That forces clearer escalation paths and supervision built into daily operations.

Identity risk is often ignored. In large enterprises, machine identities already far outnumber human users. Agents rely on these identities. Poor visibility here becomes a security and uptime risk.

Two common mistakes stand out.

First, treating agentic AI as an IT project. Plants run on operational ownership. If plant leaders carry production risk without control, adoption will stall.

Second, scaling agents before fixing data. Automation amplifies whatever it touches. Fragmented data leads to unstable outcomes.

If you’re starting, pick one decision-heavy workflow where delays clearly cost money. For example, maintenance prioritisation on a single line. Use AI where data exists but decisions stall. Avoid using it where safety or material judgment is the constraint.

#AgenticAI #AILeadership #DigitalOperations #EnterpriseAI #AIGovernance #FutureOfWork #CIO #CTO #BusinessTransformation #AIInfrastructure #CyberRisk #ExecutiveStrategy

AI regulation in the U.S. is entering a phase where state laws are active while federal preemption remains unresolved, which increases execution risk for operating businesses. This matters because AI already influences pricing, hiring, customer communication and clinical decisions, all of which carry direct legal exposure. Waiting for regulatory clarity will deploy AI under overlapping obligations that conflict with actual workflows. 

State AI laws are becoming prescriptive because they regulate disclosures and internal controls rather than abstract principles. This is happening because states are regulating where visible harm intersects with deployed systems. That directly affects how models are trained and monitored inside revenue-critical operations.
This means: AI systems without documented controls will slow execution.

Federal efforts to override state rules are accelerating because fragmented regulation increases cost and litigation risk at scale. This is happening because national competitiveness now depends on AI throughput rather than experimentation.
This means: rigid compliance strategies will increase rework and delay returns.

To make good on AI investments companies need to operate AI safely instead of reacting to regulation.

#AIStrategy #Cybersecurity #DigitalTransformation #EnterpriseAI #TechLeadership #AIGovernance #ZeroTrust #CIOInsights #SecurityArchitecture #AIRisk

AI Search Engine Optimization (AISEO)

I’m happy to share that I’m starting a new position as Investor – Anthropic at Confidential Investment Vehicle!

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Jeremy Tan

Raj Goodman Anand

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The Battle

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Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Raj Goodman Anand's LinkedIn Performance

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