Bhanu V.

I have observed two primary ( dangerous ) approaches to building a SaaS product. - Cursor, Replit, Bolt, Lovable, Claude Code - Bootstrapping the system yourself - You paid thousands of $ for an enterprise level CTO. The problem with the first approach: Too many people are shipping MVPs that work partially but look like generic AI slop, and then wonder why users don’t trust them. - Dark gradients everywhere, purple and blue. - Random shadows. - Five fonts. - Ten colors. And the excuse is always the same: Cursor / AI and templates made it like this. And then we have the performance and bottleneck issues, which go like: - It works, but for 20 users - Endless lags - Integration issues - Scalability Issues The failure is not AI. It’s a lack of technical discipline and architectural design. Then the founders come to a point where they say "Oh, I have built 80% of the application and need someone to fix the rest for 500$ and make the product run". The point we need to understand is that the amount of technical debt we create with vibe coding can take, at times, months to resolve. And not only this, at times I have seen that we need to redesign the whole product. The problem with the Second approach: Sometimes the CTOs are obsessed with perfection over survival. The perfection methodology is not for survival, especially at an early stage startup. There has to be a balance, and startups need to ship. If the "CTO" is only focusing on: "Architecture needs to be right first." And blocking product decisions. Then I have seen this exact pattern kill many startups. They think "technical co-founder" means they outrank product. At 3 people startup, you can't afford a CTO who needs an empire. In my opinion, building ground up is the right strategy. You don't need FAANG level engineers yet. You need engineers who know how to survive. What We do: If you are a founder who does not want to get stuck between AI slop and engineering paralysis, this is exactly the gap I work in. I help early-stage teams ship real, disciplined products. Fast enough to survive and robust enough to scale. If you want to build it right without killing momentum, let’s talk.

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🔎 𝗧𝗵𝗲 𝗳𝗼𝘂𝗻𝗱𝗲𝗿 𝘀𝗮𝘆𝘀: “We need Stripe.” 💼 𝗦𝗮𝗹𝗲𝘀 𝘀𝗮𝘆𝘀: “Clients want to pay in USD/EUR and sign with a local entity.” 📊 𝗙𝗶𝗻𝗮𝗻𝗰𝗲 𝘀𝗮𝘆𝘀: “Settlement, refunds, reserves and reconciliation are breaking our process.” They are often describing the 𝘀𝗮𝗺𝗲 𝗰𝗿𝗼𝘀𝘀-𝗯𝗼𝗿𝗱𝗲𝗿 𝗽𝗮𝘆𝗺𝗲𝗻𝘁 𝗽𝗿𝗼𝗯𝗹𝗲𝗺 from three different angles. At 𝗣𝗮𝘆𝗼𝗺𝗮𝘁𝗶𝘅, I see this frequently with Indian SaaS companies, agencies, e-commerce brands and exporters expanding internationally. The payment issue is rarely just one missing account or one unavailable gateway. It is usually a combination of structure, provider fit, evidence and operations. 🧩 A founder may focus on the headline requirement: 𝗨𝗦/𝗨𝗞 𝗲𝗻𝘁𝗶𝘁𝘆, 𝗜𝗕𝗔𝗡, 𝗺𝗲𝗿𝗰𝗵𝗮𝗻𝘁 𝗮𝗰𝗰𝗼𝘂𝗻𝘁 𝗼𝗿 𝗽𝗮𝘆𝗺𝗲𝗻𝘁 𝗴𝗮𝘁𝗲𝘄𝗮𝘆. A sales team may focus on credibility: local contracts, clean invoices, recurring billing, marketplace access or customer payment preferences. 🌍 A finance team may focus on what happens after the sale: settlement timing, chargebacks, reserves, refunds, reporting and month-end reconciliation. 🧾 All three matter. That is why our process starts with 𝗔𝘀𝘀𝗲𝘀𝘀: business model, owners, markets, currencies, risk and goals. Then we review the practical details providers care about: • 🧠 𝗣𝗮𝘆𝗺𝗲𝗻𝘁 𝗿𝗲𝗾𝘂𝗶𝗿𝗲𝗺𝗲𝗻𝘁𝘀: methods, recurring billing, refunds, chargebacks, reserves and settlement • ⚙️ 𝗧𝗲𝗰𝗵𝗻𝗼𝗹𝗼𝗴𝘆 𝘀𝘁𝗮𝗰𝗸: checkout, integrations, webhooks, routing, reporting and controls • 📁 𝗨𝗻𝗱𝗲𝗿𝘄𝗿𝗶𝘁𝗶𝗻𝗴 𝗲𝘃𝗶𝗱𝗲𝗻𝗰𝗲: website, contracts, invoices, product access, fulfilment and customer-support proof Sometimes the right answer is a foreign operating company. Sometimes it is an account and invoicing route. Sometimes it is payment-stack activation for an existing entity. And sometimes, a trustworthy advisor should say: “𝘠𝘰𝘶 𝘥𝘰 𝘯𝘰𝘵 𝘺𝘦𝘵 𝘯𝘦𝘦𝘥 𝘢 𝘧𝘰𝘳𝘦𝘪��𝘯 𝘤𝘰𝘮𝘱𝘢𝘯𝘺.” ✅ Provider approval and account availability remain subject to independent 𝗞𝗬𝗕, 𝘂𝗻𝗱𝗲𝗿𝘄𝗿𝗶𝘁𝗶𝗻𝗴, 𝗲𝗹𝗶𝗴𝗶𝗯𝗶𝗹𝗶𝘁𝘆 𝗮𝗻𝗱 𝗷𝘂𝗿𝗶𝘀𝗱𝗶𝗰𝘁𝗶𝗼𝗻 𝗿𝘂𝗹𝗲𝘀. But a better diagnosis makes the application stronger. 💬 When your business discusses cross-border payments, whose perspective is usually heard first — founder, sales or finance? Toll-Free: 1800-309-0113 support@payomatix.com www.payomatix.com whatsapp : +919560695572

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Where is the post-training infra market still “unsolved”? The best pockets are areas where the stack is still missing a reliable primitive. Here are 4 areas where it might work: 1. Outcome-based evaluation (beyond LLM-as-judge) Enterprises care about “did the agent complete the workflow correctly?” as opposed to “did it look fluent?”. But the big challenge is instrumenting ground truth from business systems (CRM, ticketing, payments) and then turning it into automated evals. Startups that own this interface can become system-of-record for AI quality. 2. Continuous learning for agents (safe retraining loops) A lot of teams want self-improving agents, but they don’t trust the loop. The winning wedge is: gated data collection + audit trails + rollbacks + sandboxed deployments. This could be the next evolution after basic orchestration. 3. Governance + compliance automation as product There are rules in place to push companies to document risk controls, testing, and monitoring. The infra opportunity is software that continuously produces compliance evidence (test coverage, incident trails, red-team results) as a byproduct of normal operation. 4. Data flywheels for post-training (high-quality feedback at scale) Post-training quality is gated by data. Partnerships like Anthropic’s use of Surge AI’s RLHF platform illustrate the demand for scalable human feedback + QC systems. Startups that productize “feedback ops” (tools, QC, workforce routing, privacy) can be critical picks-and-shovels.

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‏١‏ ‏تعليق واحد‏

Sam Altman just said we're 2-3 years away from superintelligence. Not AGI. Not "smart chatbots." Superintelligence. He said this yesterday at the India AI Impact Summit in front of global AI leaders, policymakers, and 100 million Indian ChatGPT users. 𝗛𝗲𝗿𝗲'𝘀 𝘄𝗵𝗮𝘁 𝗵𝗲 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝘀𝗮𝗶𝗱: "By the end of 2028, more of the world's intellectual capacity could reside inside data centers than outside of them." Translation: AI systems will be capable of running companies better than CEOs and conducting research better than top scientists. Not assisting. Outperforming. 𝗔𝗻𝗱 𝘁𝗵𝗲𝗻 𝗵𝗲 𝘀𝗮𝗶𝗱 𝘁𝗵𝗶𝘀: The world urgently needs a global regulatory body for AI. Something modeled after the International Atomic Energy Agency (IAEA). Not to police copyright or deepfakes. To prevent biosecurity threats. His exact warning: "There'll be extremely capable biomodels available open-source that could help people create new pathogens." He's not talking about misinformation or job loss anymore. He's talking about existential risk. 𝗢𝗻 𝗷𝗼𝗯𝘀: Altman admitted the obvious: current jobs will be disrupted. "It'll be very hard to outwork a GPU in many ways." But he stuck to the standard line: technology always disrupts labor, humans adapt, future jobs will rely on empathy and social responsibility. The problem with that answer is it assumes the transition happens smoothly. History suggests otherwise. ChatGPT has 100 million weekly active users in India now. Second only to the US. Over a third of them are students. If Altman's timeline is right, we're not talking about 2035 or 2040. We're talking about 2-3 years. Superintelligence. Open-source biomodels. An IAEA for AI. And if AI can design bioweapons by 2028, imagine what it'll do for your ad campaigns. Follow me Ray Jang for daily posts as I scale Atria, an AI platform for marketers to create killer ads with ease.

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‏١٢٥‏ ‏تعليق‏

🔹 Product Without “Abandon Point Mapping” Is Blind to the Moment It Loses Trust You don’t lose users suddenly , you lose them click by click. Track: • Exit Hotspots by Feature • Drop-Off Moments per Session • Time-to-Abandon vs GMV Curve • NPS After Feature Flow Example: Step 4 → spike in exits → Removed one toggle, simplified form → Drop-off ↓ 61%, GMV ↑ SAR 260K in 30 days Trust doesn’t shatter , it leaks. Find the cracks before your revenue follows. #etman

The recent discussions around “AI-driven compliance” - Delve bring up an important point that many in our industry already know—but don’t always say out loud. I see a striking irony in that event - That company built around compliance allegedly exposes sensitive internal data through a leaked sheet highlights a fundamental truth: compliance is not what is written in reports, but what is practiced daily. In 2019, I had led our #SOC2type2 certification process end-to-end at beqom as the #CTO co-founder. It required months of cross-functional effort—aligning systems, processes, teams, and behaviors, all under strict external audit. It wasn’t about producing a report; it was about building a company that could stand behind it. That experience shaped how I evaluate compliance claims today. So when I later encountered offers promising #SOC2 in days through automation, it raised serious doubts. Not because speed is bad—but because true compliance is not something you can shortcut without compromising substance. At Workiom, we’ve taken a deliberate approach. Over the past months, we’ve focused on building the foundations properly—training teams, defining processes, and embedding controls into how we actually operate. We are now entering the #ISO27001 audit phase with confidence in what sits behind it. What’s happening now is bigger than one company. There is a growing tendency—especially in fast-moving startup environments—to treat compliance as a commercial milestone rather than an operational commitment. Certifications become checkboxes, not reflections of reality. That mindset creates risk—not just for the companies themselves, but for every customer who relies on those certifications to make trust decisions. It’s also too easy to place all the blame on vendors. In reality, leadership teams choose whether to invest in real capability or accept superficial solutions. AI will play a role in improving compliance workflows. But it cannot replace discipline, experience, and accountability. At Workiom, we believe trust is built through substance—not speed. For context, a recent overview of the allegations: https://lnkd.in/dyPqxwaT

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‏٢‏ ‏تعليق‏