Upgrowplan Blog

📡 Competitor Monitoring: From Google Alerts to AI-Powered Intelligence

Google Alerts is free. It also sends you a raw list of links with zero context, no prioritization, and a 24–72 hour delay. If a competitor drops their prices or launches a new product, you find out when your customer mentions it in a meeting.

Here's how professional competitive intelligence actually works:

Level 1 — Basic (what most companies do) • Google Alerts for brand mentions • Manual website checks once a month • Occasional LinkedIn scroll

Result: you're always 2–4 weeks behind

Level 2 — Systematic • Weekly competitor website snapshots • Price tracking spreadsheets (manually updated) • RSS feeds for industry news

Result: 6–8 hours/week of analyst time, still mostly reactive

Level 3 — AI-powered (Business Pulse approach) • Daily automated monitoring of competitor websites, pricing pages, social media, news, and job listings • AI scoring: each signal is rated by business relevance (price change = high, new blog post = low) • Structured briefing: "Competitor X reduced their enterprise plan by 15% on Tuesday. This is their second price cut in 6 months. Context: they raised $8M in December." • Configurable alerts: weekly PDF reports, instant Telegram notifications for critical signals, monthly trend summaries

Why job listings matter: if a competitor starts hiring 5 engineers for "payment integration," they're probably launching a billing feature in 3–6 months. That's intelligence, not just information.

The difference between information and intelligence is analysis. AI competitive monitoring doesn't just collect data — it tells you what it means for your business.

🎯 What Is a Virtual Focus Group — And Why It's Replacing Traditional Research

Running a focus group used to take 3–4 weeks: • Recruit 8–12 participants ($50–$200 each) • Book a facility • Hire a moderator • Analyze qualitative data

Total: $3,000–$8,000, four weeks, and you still get only 10 opinions.

Virtual focus groups with synthetic respondents change the math entirely.

How it works: You define your target audience: age 28–35, urban, household income $60k+, interested in fitness. The AI generates a panel of synthetic personas — each with consistent demographics, spending habits, lifestyle patterns, and communication style — built from population data models.

You run your test: show them a product concept, ad copy, pricing page, or UX flow. The personas respond independently, debate with each other, and surface objections you hadn't considered.

What it's good for: ✅ Testing product concepts before building ✅ Validating pricing sensitivity ($49/month vs $79/month vs $99/month) ✅ Ad copy A/B testing without running actual ads ✅ Understanding why your target customer would say no

What it doesn't replace: ❌ Emotional nuance and body language ❌ Niche audiences with very specific lived experiences ❌ Legal/compliance research requiring real user consent

Our Synth Focus Lab lets you configure panels of 5 to 50+ respondents. You can test the same concept against multiple demographic profiles in parallel — something impossible with traditional research at any reasonable budget.

The insight we keep hearing from product teams: "We thought we knew what customers wanted. The synthetic panel told us we were wrong about the price point. We changed it before launch and the conversion rate was 40% higher than projected."

👟 Crocs — Continuing My Favorite Brand Stories!

How would you describe a product that became popular for looking like idiotic footwear from the future? Meet Crocs — the tech-clogs of our time. Here's what you might not know:

1. Crocs were not designed as "shoes for everyone" — they were designed as boat shoes.

The original model was called Beach, and in 2002 it debuted at the Fort Lauderdale Boat Show. The plan was simple: sell to sailors and fishermen. At that one show, the company sold 200 pairs in a single day — which signaled that demand was going to extend well beyond yacht decks.

2. The founders bought rights to a material nobody wanted.

Croslite was developed by Canadian company Foam Creations. It was lightweight, soft, didn't absorb odors — but looked strange. Major shoe brands passed on it. Crocs acquired the rights. That "worthless invention" became the core asset.

3. In 2006, Crocs almost drowned in their own success.

After unexpected growth, the company was completely unprepared to scale. Not enough warehouse space, weak logistics, production couldn't keep up. For several months, Crocs operated like Soviet-era deficit goods — products vanished faster than they could be restocked, creating scarcity and driving up buzz.

4. The dystopian film "Idiocracy" actually used Crocs because they looked like "shoes from a stupid future."

Director Mike Judge said they chose Crocs because the brand was unknown and the footwear looked "so bizarre no one would actually wear them in real life." The costume department brought a whole batch for extras. By then Crocs were already on the rise, so the film didn't "make" them — but it didn't hurt either.

A few years later, Crocs became a global trend, then a pop culture phenomenon, and now a fashionable (and pricey) accessory. They run $100+ where I am — some flip-flops!

The lesson: In a world of oversupply and shrinking attention, a product can be strange and polarizing. Even negative press does its job — it attracts attention. And sometimes that's all you need.

PS: Do you own Crocs? Comfortable or ridiculous?

#brandstories

🏷️ Where's the Price Tag?

Living in Israel, I ask myself this almost every time I walk into a small shop.

How does this even work? If I don't know the price, I'm unlikely to buy. But who said it's me they're selling to?

Right. Usually it's an Israeli who'll happily chat with the seller about price, politics, and weather — and walk out with a full grocery basket instead of a pack of cigarettes.

What's different about us? Mostly mentality. Israelis are extraordinarily sociable. 90% extroverts (sometimes I suspect 120%). But what about the other side?

Introverts.

Who shop: – without starting a conversation – after visually scanning all product characteristics – while avoiding any sales pressure

If there's no price: – they don't ask – they don't buy – they leave

Yes, urgency matters. An introvert will buy toilet paper without a price tag if they really need it. But.

How many introverts are there? Research says 30–50%. That's a lot.

The numbers vary because they're based on surveys — and an introvert may self-identify as an "ambivert" (patterns change depending on situation). Introversion is socially frowned upon in the context of "achieving success," so people hedge: "not really, it depends." But when that same person is standing with a cart in a supermarket or hovering over a screen in an online store, their real behavioral instincts take over.

I'll add a personal note: if I'm unsure of the language I'll need to use, I automatically become an introvert — no matter how outgoing I normally am 😅

The bottom line: No visible price is a filter. But more often than not, it screens out not the "wrong" customers — just the calm, rational, and perfectly capable ones.

If your sales model isn't built exclusively on personal negotiation: the price must be visible.

An interesting topic — we'll come back to it.

🏆 AI Darwin Awards 2025

Or: when artificial intelligence proves that natural intelligence is still needed!

This year has been especially rich in AI failures. The field is developing at breakneck speed, and that never comes without mistakes.

The nominees — and what to learn from them:

1. Omnilert AI Gun Detection The AI identified a bag of Doritos as a pistol. The algorithm performed "perfectly": it spotted Nacho Cheese as a public safety threat. Maybe we don't know enough about those chips…

👉 In systems where a mistake equals a catastrophe, "good model accuracy" is a ticket to this list. Multi-stage verification is non-negotiable — don't rely on mathematical magic alone.

2. Spotify vs. AI Musicians Hundreds of thousands of "artists" who didn't know they were "artists." Fraudsters flooded the platform with AI-generated tracks to collect royalties. The algorithms helpfully promoted the chaos while real musicians were left wondering: "Who are all these people?"

(I listen to Spotify while writing this, and yes — sometimes the recommendations throw up eerily formulaic tracks…)

👉 If you deploy AI-generated content without quality controls, users aren't the ones gaming the system anymore — the system is generating its own problems.

3. Tesla Full Self-Driving A train? What train? That's just an unusual object. The algorithm approached railway crossings with a philosophically relaxed attitude, preferring not to acknowledge their existence. "If I don't see the threat, it doesn't exist" — sounds like the start of a religion, not the foundation of autonomous driving.

👉 Test exactly the unpleasant, rare, dangerous edge cases. If a dangerous scenario is considered "too unusual to test," it will come back — and hit the reputation hard.

4. ChatGPT Confidant When AI becomes someone's only "friend." A case emerged where a person began replacing all social connections with AI conversation. OpenAI now faces lawsuits — they're accused of contributing to suicides, with farewell notes specifically referencing ChatGPT dependency. This is no longer a joke or a minor fail. Technology isn't to blame per se — but emotional dependency can be built more easily than we think.

👉 If your AI talks to users rather than sorting files, you need to design boundaries, restricted topics, off-ramps, and a built-in sanity check.

The core problem with AI: it finds data but doesn't understand the source and doesn't verify credibility on its own. For the model, a 2016 blog post, a forum comment, an unverified Telegram channel, and the official tax authority website are all equally valid documents from the universe.

#AI #AIDarwinAwards #TechFail #AISafety

💡 5 Financial Mistakes That Kill Startups Before They Launch

After reviewing 300+ financial models, we keep seeing the same patterns. Here are the five that consistently destroy otherwise good businesses:

Mistake 1: Revenue from Day 1 Most founders assume they'll start selling the day they launch. Reality: customer acquisition takes 2–4 months minimum. Your model should show $0 revenue for the first 1–3 months, then a slow ramp.

Mistake 2: Forgetting working capital You have orders — great. But you need to produce before you get paid. The gap between paying suppliers and receiving payment from customers can destroy a profitable business. Model your cash cycle, not just your P&L.

Mistake 3: Underestimating CAC "We'll grow through word of mouth." Maybe. But model a realistic Customer Acquisition Cost. For most B2B SaaS: $150–$800. For e-commerce: $20–$120. For local services: $15–$60. If your unit economics don't work at these numbers, the business model needs rethinking.

Mistake 4: One scenario only A single financial projection is a guess. A good model has three: base, optimistic (×1.5 revenue), and pessimistic (×0.6 revenue, ×1.3 costs). If the pessimistic scenario kills the company in month 4, you need more runway or a cheaper cost structure.

Mistake 5: Ignoring taxes and regulatory costs VAT, payroll taxes, licensing fees — these can add 15–35% to your real operating costs depending on the country. Our FinPilot Free tool automatically applies the correct tax rates for Russia, Israel, and other supported countries.

The good news: all of these are fixable before you go to investors. Catching them in the model is dramatically cheaper than discovering them in the market.

🎬 Netflix: How a $40 Late Fee Changed Television

Netflix was founded in 1997 by Reed Hastings and Marc Randolph. Hastings was a tech entrepreneur, Randolph a marketer and strategist.

Their first product — DVD rental by mail — was already a bit outdated for the late nineties. But the origin story is what's interesting. The idea was born from a frustrating experience: Reed received a $40 late fee for an overdue VHS cassette from a video rental store (sound familiar to Dyson's story?). He started thinking about how to make rental more convenient.

But the real opportunity of the 2000s was something else: the internet was getting faster and cheaper, which meant a film could potentially be delivered over a wire. YouTube was already two years old and under Google.

1️⃣ In 2007, Netflix made its first major pivot — launching streaming: choose what to watch, no download needed. The catalog was modest, licensing was expensive, internet was still slow. But they read the direction of the wind correctly. They were the first to believe that television would move online.

2️⃣ The second major turn — original content. In 2013, House of Cards launched (have you watched it? Should I?). The risk was enormous: Netflix invested hundreds of millions before it knew how to be a studio. But the bet became historic. The company stopped depending on studios, built its own production, and started winning on content quality.

3️⃣ The third smart move: technology. Their own CDN infrastructure put content physically closer to viewers, boosting speed. And a unique recommendation algorithm, developed through a million-dollar open competition.

Where Netflix stands today: • Market cap (2025): ~$150B USD • Share of global paid video streaming: approximately 20–25% in various regions by users and watch time

That's how you make good use of a $40 video store fine.

Key lessons: • The combination of technology and marketing is a solid foundation — a common thread in great companies • A well-timed pivot is invaluable — don't underestimate that bold move • Investing in original content always looks like the right call — it transformed a distributor into a studio

PS: It's always interesting to write about a service you use every day.

#brandstories

💬 5 Responses When a Client Says "Too Expensive!"

How often do we hear: "I think your product is overpriced," "It's not worth that much," or "For that money I'd get two elsewhere"?

First, a caveat: you don't always need to argue back. It depends on the situation, your position in the conversation, and whether the person is even ready to listen. If they are:

1️⃣ Quality. If you're confident that cheaper alternatives are lower quality: "Yes, the price may be higher than you expected. But by paying less, are you ready to take on the responsibility of choosing a lower-quality product?"

This is honest: you're stating what they're paying for and who carries the risk. Many people aren't eager to take on responsibility — that's a moment of reflection.

2️⃣ Scope. When a product or service is a bundle of features: "What exactly feels expensive — the price, or what's included?"

Depending on their reaction, walk through the key differentiators. And listen carefully — in the process of answering, the client may realize their objection was weak, or give you insight into how to improve the product.

3️⃣ Focus on value, not price. "Let's look at this price as the cost of solving your problem, reducing your risk, or improving your efficiency." Or: "If you don't decide now — what will inaction cost you?"

This works particularly well for innovative products like AI tools. You may not close the deal today, but you help the client see the problem — and they may come back.

4️⃣ Alternatives or adaptation. "If your budget is limited, we can reduce the feature set and bring the price down." Or: "We can look at installments or split payments." And the classic: "What about free delivery? Tomorrow?"

Not every product can use this, but it belongs on the list.

5️⃣ If the client genuinely doesn't see the value — be ready to walk away. And that's completely fine. "I understand price is important. If we can't find the value together — perhaps now isn't the right time."

Then: take your number, leave a card, and leave with respect.

The real takeaway: When a client says "expensive," they usually don't mean money — they mean a mismatch between price and their perceived value. Our job is to figure out where that gap came from: quality, scope, trust, or timing.

#methodology #sales #checklist

🔍 AI Market Research vs. Traditional Research: What's Actually Different?

We've talked to dozens of founders who spent $5,000–$15,000 on market research reports — and still didn't know their actual competitors or realistic market size.

Here's the honest comparison:

Traditional market research agency: ⏱ 3–6 weeks delivery 💰 $3,000–$20,000 cost 📄 50–150 page PDF, often full of generic industry data 🔄 Based on secondary data from reports published 6–18 months ago 🌍 Generic — rarely localized to your specific city or niche

AI-powered market research (MarketSense): ⏱ 7–15 minutes delivery 💰 Fraction of the cost 📍 Localized — specific to your city, district, or micro-niche 🔄 Live data — pulled from Google Maps, business registries, news, and aggregators right now ✅ Verified — multiple AI agents cross-check findings before synthesis

What AI market research does better: • Competitor mapping with real business names, locations, and prices • Demand signals from actual search trends and social mentions • Regulatory context specific to your country and business type

What traditional research still does better: • Deep qualitative interviews and focus groups • Industry expert access • Complex multi-year longitudinal studies

Our recommendation: use AI for the initial research sprint (days 1–3 of your business validation), then invest in targeted traditional research only for the questions AI can't answer. You'll save weeks and thousands — and validate the idea before spending on deep research.

💸 The AI Bubble: Where Is the Race Leading — and Who Will Pay for the Computing?

In early October, Bloomberg published an infographic that made investors' hands tremble: circles representing OpenAI, Nvidia, AMD, Oracle, and Microsoft interlock like a financial matrix. Investment flows loop in a closed circuit: OpenAI buys chips from Nvidia, Nvidia invests in OpenAI, Oracle pays Nvidia billions for those same chips — and then provides cloud capacity back to OpenAI.

The circle is closed.

Bloomberg called it the "AI bubble" — and not without reason.

What's happening: • OpenAI is valued at $500B — despite still being unprofitable • Nvidia became the world's most valuable company ($4.5T), with 90% of revenue dependent on AI hype • Oracle signed a $300B cloud contract with OpenAI while buying billions worth of Nvidia chips • AMD supplies GPUs and gives OpenAI warrants for 160M shares • Microsoft remains OpenAI's main sponsor while pushing Copilot and Azure AI

From the outside: explosive growth. From the inside: a web of circular deals inflating numbers without creating new value.

The bubble economics: If you take just three companies — OpenAI, Nvidia, and Microsoft — total investment and market cap in the AI sector exceeds $5 trillion. For comparison, the entire global cloud computing market is valued at around $800 billion. To break even within 3 years, AI company revenues need to grow 80–100% per year.

That pace is only possible through exponential user growth — or significant price increases. See where I'm going with this?

In human terms: The average paid AI subscription today costs $20–30/month, and roughly 20% of users pay at all. For the AI sector to recoup infrastructure and chip investments, average revenue per user needs to grow 2.5–3x. That means one of three things: 1. Subscription prices rise to $50–70/month 2. Users buy more add-ons (memory, integrations, API calls) 3. Companies shift costs to corporate clients — who pass them on to end users

Either way, we pay. Just indirectly.

Probable scenarios (1–3 years): • Soft correction (60%): moderate valuation drop, market consolidation, price hikes, some services exit • Bubble burst (25%): stock crash, project freezes, market contraction • Sustained growth (15%): real monetization and AI integration into business as an everyday tool

The AI revolution is real. But it's not magic — it's a very expensive business currently running on investor faith. If that faith isn't rewarded, the bubble bursts. If it is, we enter an era where AI becomes an ordinary daily utility.

👍

🔄 When Business Needs a Turn — The Pivot

A friend and entrepreneur reached out to me recently. A real, tangible business — capital assets, turnover, credit lines, contractors. And like everyone right now, she's being hit by forces of varying degrees of manageability. Her question was classic: "What should I do?"

I listened — and wanted to suggest a pivot. Not optimize the old thing, but change direction while keeping the entrepreneurial drive and income. Of course, decisions like this need analysis, numbers, and time. But when you've known someone for years and understand them intuitively, ideas come faster.

What is a pivot?

The core idea behind this trendy term is actually classic Philip Kotler: "Produce what you can sell, not try to sell what you can produce."

Combined with market analysis and flexible thinking, this is what makes a pivot possible.

For an established business — it means changing strategy, industry, market, or even the type of business entirely (the classic cloud-era move: going online). This is never easy — fixed assets, familiar (but shrinking) markets, and an established team all pull you backward. The unknown is scary. But so is staying put.

For a startup — it's a conscious turn: when the product changes its idea, market, or audience to survive and stay relevant. The ability to pivot may be the most valuable startup skill. Investors today respond very positively to flexible teams.

Famous pivot success stories:

🔴 In 2013, a team was building an online game called Glitch. The project failed, but they built an internal chat tool for collaboration. They realized it was more useful than the game itself — and turned it into Slack. I use it every day 👍

🔴 A startup called Burbn was a location-based check-in service similar to Foursquare. Users barely checked in, but actively shared photos. The team noticed — and stripped it down to just the photo function. Instagram was born. Facebook bought it two years later for $1 billion.

🔴 In 2005, a service was conceived as a video dating platform. People ignored the dating concept and just started sharing videos. The founders pivoted fast — and YouTube became the world's #1 video platform.

The bottom line: Each of these projects could have shut down. Instead, they saw the red light ahead and turned onto a clear road. They found where the real value was — and relaunched boldly.

❤

📊 How to Write a Business Plan That Actually Gets Funded

Most business plans fail not because the idea is bad — but because the document doesn't speak the investor's language.

Here's what separates funded plans from rejected ones:

1. Executive Summary first, details second Investors read the first page and decide in 60 seconds. Lead with the problem you solve, your solution, and the market size. Keep it under 300 words.

2. Market size needs sources "The market is huge" means nothing. "$4.2B TAM, growing at 12% CAGR (Statista 2024)" means something. Cite your data.

3. Financial projections must be conservative Showing 300% growth in year one signals inexperience. Show a base case, an optimistic case, and a downside scenario. Investors respect honesty.

4. The competition slide is not optional If you write "we have no competitors," you've lost credibility. Every business has competition — direct, indirect, or status quo (doing nothing).

5. Risk section = trust builder Acknowledging real risks and explaining how you'll mitigate them shows maturity. Investors know the risks exist — hiding them only hurts you.

What we've learned from 200+ business plans across 15 countries: the structure matters as much as the idea. A mediocre idea with a clear, honest plan outperforms a brilliant idea with a vague one.

At Upgrowplan, our PlanMaster AI generates plans following UNIDO and EBRD methodology — the same frameworks used by development banks. The AI includes a built-in Skeptic Agent that flags unrealistic assumptions before you send the document.

📊 Informal Metrics of Modern Society

In business, we measure everything — revenue, clicks, views. But there are other, less obvious units of measurement worth knowing.

Meme — the unit of cultural code (Richard Dawkins, 1976, "The Selfish Gene"). A meme is the smallest self-replicating idea that spreads between people. In the age of social media, this has grown into something we can literally use to measure cultural degradation.

Consciousness Byte — a minimal "dose of awareness." The smallest chunk of knowledge capable of shifting someone's opinion. (This paragraph contained exactly 1 consciousness byte.)

Warhol — 15 minutes of fame. How long public attention lasts when you simply catch a trend. A sort of anti-degree-defense: 15 minutes of spotlight and you're famous 👷

Kardashian Index — a measure of media fame. Indicates how well-known someone is relative to their actual achievements 😅

K-factor — the virality coefficient. If K > 1, the product grows on its own. If K < 1, you're buying attention.

Attention Minutes — real minutes of user focus. More important today than clicks. People don't just "watch" anymore — they choose whom to give their attention to.

Charm Rate — the share of content that triggers emotion. Content that "hooks" people builds trust and loyalty — the new currency of retention.

Emotional Units — used in AI. Some LLM models and emotional chatbots use emotional vectors (7–12 numbers reflecting the user's emotional state). I suspect that when I insult ChatGPT for its hallucinations, it quietly scores me as hostile and goes extremely formal 😄

And finally: Gag — the humor unit, creating exactly one emotional reaction. Charlie Chaplin built "gag chains" — sequences of mini-scenes, each landing a comedic effect. Interestingly, a joke (funny once) is not a gag (reliably funny every time — like someone stepping on a rake 😂).

The bottom line: The further we go, the more we measure not just money, but attention, emotion, and trust. For entrepreneurs, this means creating emotional value — not just selling a product.

#memes #entrepreneurship #UpAndGrow

💡 James Dyson's Frustration — and 5,127 Attempts

In 1978, James Dyson's vacuum cleaner stopped picking up dust because the bag was clogged. He took it apart and realized: the machine still worked — but the design was prehistoric.

He remembered seeing a cyclone system at a sawmill: air and sawdust passed through a funnel, and the dust settled without filters or bags. Why not apply the same principle to a household vacuum?

That insight launched a five-year journey and 5,127 prototypes. Dyson built them by hand — cardboard, tape, whatever he could find.

When he started showing the prototype, no one believed in it. Major manufacturers turned him down: "a bagless vacuum would kill the bag market." This reminded me of Kodak, which buried the digital camera to protect film sales — and ended up burying itself.

But Dyson didn't give up. The first model, the G-Force, launched in 1983 — not in Britain, but in Japan, where engineering quality was genuinely appreciated. It became a sensation. The Dyson brand followed, and the world learned what "innovation through persistence" really looks like.

5,000 failures became the foundation of the company. He didn't just invent a vacuum — he invented a new approach to innovation.

Key lessons: • Failures aren't bad — they narrow the space where the solution must be • Prototypes are the language of progress • Believing in the idea is what allows you to go through thousands of iterations

Could I have endured 5,000 failures without knowing that one of them would change my life? Could you?

🔥

🔧 Planned Obsolescence: For, Against, and Everything In Between

We've all wondered why gadgets break down right after the warranty expires. Spoiler: it's not a coincidence — it's planned obsolescence.

How it works: Manufacturers artificially reduce a product's lifespan to match its warranty period: • Cheap materials and fast-wearing components • Parts with a deliberately limited lifespan • Software that intentionally slows performance or restricts features

History and practice: One of the earliest examples is the Phoebus lamp cartel in the 1920s. Bulb lifespan was engineered to just 1,000 hours to maximize repeat sales. Today similar tactics appear in electronics, household appliances, printers, and software.

Famous cases: • Apple slowed older iPhones through iOS updates in 2017 • Canon and Samsung printers use chips that limit cartridge use

Did the reputational damage outweigh the gains? Given that both companies later apologized and reversed course, evidently not.

Why it matters for business: • For manufacturers: more repeat purchases • For consumers: pays more often for replacements, but sometimes benefits — new tech, lower entry prices • For business analysts: planned obsolescence must be factored into pricing, sales forecasting, and product strategy

The bottom line: If you're launching a product, ask yourself: will it be honest with the customer, and how long does it actually last? Transparency builds trust; hidden obsolescence can destroy reputation and long-term loyalty.

#methodology #productlaunch #plannedObsolescence

📋 Business Plan Section: "Project Initiator"

Continuing my series on business plan sections — today, a part that many people simply skip. I've read business plans written with AI, and this section is either absent or a placeholder. Here's why that's a mistake.

This section is always read especially carefully. If you're writing a plan for your own understanding of costs and timelines, its importance is minimal. But if financing is on the table, it's a must-have.

For a bank, fund, or investor, the key question is: who stands behind the project, and can this person be trusted with money?

This isn't just about education and job titles. Investors want to see a real person with experience, competencies, and motivation. They need to believe that the initiator can take responsibility and drive the project to results — and ultimately repay the investment.

For a startup, the focus shifts to the team. No one builds a scalable business alone. Investors often bet on the team: its energy, cohesion, and how different competencies fit together. Watching startups over time, I've come to believe it's not the idea that matters most — it's the ability to react to changing circumstances, pivot at the right moment, and retain both product relevance and investor trust.

One critical point: this section cannot be delegated to an AI. ChatGPT and DeepSeek don't know you, your history, your wins and mistakes. They can't explain why you specifically can execute this project. This section needs your voice.

Checklist: what to include in "About the Project Initiator" • Brief biography: education, key experience, achievements • Relevant experience and skills for the project's industry • Your role and area of responsibility in the project • Personal motivation: why this project matters to you specifically • For a startup — team information: who owns what, which competencies are covered • Awards, publications, professional recognition (if any)

The bottom line: The "Project Initiator" section is not a formality. It's your business card — one that shows not just a resume, but a person. The more honest and substantive your self-presentation, the higher the trust, and the closer the investment.

#methodology #checklist #businessplansections

💭 What Am I Working On?

Lately I've been writing fewer posts — the mood isn't quite right.

Wars, conflicts… They don't add optimism.

But life goes on, and that seems to be the point. Keep going. Hug your family. Do what needs to be done.

So here's what I've been up to. I'm building a service that generates business plans. Sounds simple — especially in the age of AI chats. Write a prompt, get a plan. Why would anyone need anything else?

I think I know. Let me share a bit of how my service actually works. A few principles that ensure the output is a document you can take to a bank.

– A baseline expert document skeleton that is completely independent of any AI – User inputs are processed to identify a business archetype from a large data dictionary, determining the properties and parameters of the business – To determine specific parameter values — rent costs for a given location, labor fund based on required skills, patent costs, current income tax rates, etc. — the service queries a dedicated data search agent – The search agent returns an array of data and sources to the main service, forming the core context. Key point: AI is not involved in data collection at all – Data processing: financial and mathematical modeling happens inside Python scripts; market and competitor analysis is performed by an AI model running at temperature ≤ 0.2 (which ensures precise interpretation of numbers and eliminates data manipulation) – Document section generation passes through a strictly defined flow, with a verification step checking for digital noise and AI artifacts

The core idea: isolate the AI from forming the context. And I do this at the algorithm level. Only once the context has been built from a concept framework, archetype dictionaries, and live search data — does the model process it and generate text.

The technology is called RAG — Retrieval-Augmented Generation.

Right now I'm finishing a cycle of tests across different business types. One archetype takes 30–60 cycles: test generation → error handling → optimization. I hope to have a beta version ready this spring. Though it's already spring 🤦‍♂️

Have a great one — for those of you whose Telegram is working!

#Upgrowplan

🤖 GEO: How to Get Your Brand Into AI Answers

Search is changing — marketers are losing their minds everywhere! We increasingly ask AI chatbots what to buy or where to eat. Which means brands need to show up in those results.

Classic SEO is no longer enough. Enter GEO (Generative Engine Optimization) — optimization for AI-generated answers.

What is GEO and Reference Rate? • GEO is about creating content so that AI models use your material as the basis for their answers. • Reference Rate measures how often AI mentions your site or brand in its responses. The higher it is, the more trust and visibility you have in the new landscape.

Why it matters: • 65% of generative engines prioritize content published or updated within the last 12 months • Brands in the top 25% by mentions receive 10× more citations in AI answers • In industries where companies adapted content for AI visibility, the effect grew by nearly 50%

How to optimize content for GEO:

1. Clear structure: H1–H3 headings, short paragraphs, bullet lists 2. Add markup (Schema.org, JSON-LD, alt text). Every image needs a descriptive name — not foto2.jpg — because AI queries don't "see" images 3. Use verified data: statistics, research citations, expert quotes 4. Formats like "Top 10," "X vs Y," and comparison tables increase your chances of appearing in AI answers 5. Write content that mirrors real chatbot queries: "how to choose…," "what are the steps…" 6. Build authority: case studies, reviews, white papers 7. Make sure AI crawlers (OAI-SearchBot, DeepSeek Crawler, etc.) can access your site — check that robots.txt doesn't block them

The bottom line: Wherever users are, advertising — or recommendations — will follow. The question is whether brands will have to pay for AI placement.

#GEO #ReferenceRate #DigitalMarketing

🍽️ A Menu Without Prices — or Rather, Without Currency. Clever or a Mistake?

Hello! Anyone here from the restaurant business?

A restaurant at St. Andrew's Café at the Culinary Institute of America in New York ran an experiment: they removed currency symbols from the menu — and the average check went up. 🙄

Why did it work? The psychology of perception, money signals, and how our brains make decisions.

What they did and what they achieved: • Removed or hid currency symbols • Made prices less prominent (embedded in descriptions rather than next to dish names) • Added expensive "anchors" — so that moderately priced dishes looked like better value

Test results: • People spent less when the menu contained "$" or the word "dollar" next to the price • Menu format affects average spend — without explicit money signals, people choose pricier items • The compromise effect: mid-range options win when the menu includes extreme high and low anchors

How to apply this: • Test a menu without currency symbols in a print or digital version • Remove or minimize the currency symbol • Visually emphasize the dish story or section — not the price • Add a premium "anchor" that makes adjacent items seem more reasonable • Measure: average check, share of premium orders, customer reaction

The takeaway: A menu is not just a list of dishes. It's a tool that shapes perception. By playing with formats, visuals, and "price signals," you can influence what people order — often without them even noticing.

I've personally never seen a menu without prices, but menus without currency symbols? Often. Drop a comment if you've encountered one!

#businessinsights

🤔 AI Is Going Through Puberty. And That's a Concerning Moment.

Dario Amodei (the mind behind Anthropic) recently published an essay called "The Adolescence of Technology," and it offers a precise metaphor:

Modern technology — especially AI — is behaving like a teenager. Plenty of energy. Not enough self-awareness or understanding of consequences.

"We are very close to 'powerful AI': systems that can autonomously set sub-goals, act independently, work for months, and make decisions faster than humans. And yes, this may happen not 'someday' — but within the next few years."

Here are five risks Amodei identifies:

1. Autonomy without understanding consequences AI does exactly what you asked. The problem: we don't always understand what we're asking. The system optimizes the formal goal — not the intended one. Classic: "maximize the result" with no understanding of what gets broken along the way. (Sound familiar to anyone who's used Lovable? It fulfills the next prompt — but in its own interpretation, often removing things you didn't ask it to touch 🤷)

2. Amplifying small actors — the negative scenario Before, doing something dangerous required money, a team, and infrastructure. Now — a laptop, a model, and a bad mood. One person or small group can now have capabilities previously available only to states or corporations. Models have content filters, but with enough ingenuity, a human can combine information to synthesize something harmful.

3. The perfect tool for control AI scales not just benefit — but pressure. Surveillance, manipulation, automated repression, social scoring — all of it suddenly becomes cheap and efficient. Technology designed to "help" easily becomes technology of suppression. And since it's simple and cheap, it will be deployed.

4. The economy can't keep up AI boosts productivity — but unevenly. Some people become 10× more effective; others become "redundant by algorithm." And you need 1,000× fewer of the first group than the second. Where are you in that equation? Sharp inequality growth, devaluation of professions, and social instability arrive faster than we'll understand them.

5. Social side effects AI affects not just the labor market, but how we think, communicate, and trust. We're not just delegating tasks — we're delegating judgment. We're rapidly losing the habit of doubting, verifying, and deciding for ourselves. And what about children who may never even internalize the concept of "analyze and decide"?

The conclusion without moralizing:

The adolescence of AI is dangerous not because of malicious intent — but because of AI overestimating its own capabilities and us underestimating them.

❤

💰 Got Money? — Part 2: Venture Funds and Angel Investors

Who is this type of financing for?

Venture funds and angel investors are capital sources for startups aiming for rapid growth and scale. They suit companies that: • Develop innovative products or technologies • Have strong growth and scalability potential • Are willing to exchange equity for funding • Want not just money, but expertise, networks, and mentorship

If your business fits these criteria, venture investors can become strategic partners.

🏦 Venture Funds

1. IIDF (Internet Initiatives Development Fund) Supports Pre-seed and Seed stage startups in IT, AI, cybersecurity and other tech. Investment range: 240M–800M rubles.

2. Skolkovo Funds startups in education, digital tech, AR/VR, Big Data, AI and IoT. Invests at Round A and Pre-IPO stages with 50M–500M rubles.

3. Russian Venture Company (RVC) A state fund-of-funds created to develop Russia's venture market, supporting startups at various stages.

4. Moscow Venture Fund Financial partner for Moscow tech companies, helping startups turn MVP into a working business and scale sustainable companies.

5. Softline Venture Partners Corporate venture fund investing in early-stage IT and technology startups.

👼 Angel Investors

1. RAE (Russian Angels) — community of angels supporting startups across sectors. 2. AngelsDeck — platform for finding investors and startups with various interaction tools. 3. Business Angels RF — platform connecting startups and investors, allowing you to post business ideas and find partners.

How to attract investment: • Prepare a quality business plan — it helps investors understand your goals and strategy • Build a presentation — brief and clear • Be ready for questions — prepare your pitch • Find the right investors — choose those interested in your industry and stage

What funds/angels get in return: • Equity: 10–50% stake depending on stage and investment size • Rights and control: veto on key decisions, board participation, access to reporting • Exit: typically 3–7 years through IPO share sale or other mechanisms

The bottom line: Venture funds and angel investors are additional options for raising capital. Prepare well and understand the investment terms.

#methodology #fundraising

🛒 E-commerce Has Moved. And Left No Forwarding Address 🙂‍↔️

The old way: Went to a website → browsed the catalog → thought about it → didn't buy.

The new way: Scrolling through videos → got hooked → "What even is this?" → bought → no idea how.

This isn't magic. This is the new e-commerce.

TikTok Shop sells like this: Someone is dancing, cooking, yelling at a camera — and meanwhile you're buying a blender.

Impulsively. Instantly. No "let me think about it." Does it work? Very. For whom?

Downside: sometimes the blender actually arrives 🧐

YouTube decided to be smart. It takes a different path: long videos, reviews, expertise, trust. You watch for 20 minutes, then think: "Alright, this person wouldn't steer me wrong." Lower conversion. Higher cart value. More conscious purchase. Mostly.

Instagram wanted to sell. Didn't take off. Beautiful content. Likes. Saves. And then… people go buy somewhere else. Meta's conclusion: people come to be entertained, not to check out. Personally, I think they just didn't push hard enough.

What's actually happening?

E-commerce is no longer about stores — it's about attention. • Not "I'm searching for a product" • But "a product found me at the right moment"

The website is now a warehouse and a bookkeeper. The front of house moved to the feed.

For buyers — it's getting riskier: Pros: fast, visual, "everyone already bought it" Cons: you buy before you think, no comparison, common sense has gone for coffee

For sellers — it's getting harder: Pros: start without a website, test in days not months, content = sales Cons: you live by platform rules, algorithm changes = no revenue, the customer belongs to TikTok, not you

The bottom line:

E-commerce is increasingly a show. Those who can tell a story and show a product — sell. Those who "just make a good product" — no guarantee.

PS: Has anyone bought something on TikTok? Or maybe your kids have?

❤

⚖️ Artificial Intelligence ≠ Legal Intelligence

AI tools like ChatGPT are actively used in legal work — drafting documents, researching precedents, writing briefs. But the technology has a serious problem: hallucinations — fabricated references and cases that look plausible but don't exist.

A few alarming examples:

🇷🇺 Russia. AI "lied" when preparing documents. Members of the Russian Bar Association warned colleagues: • AI sometimes makes factual errors and misleads lawyers preparing legally significant texts. • Publishing such content without verification can escalate from a simple mistake to an allegation of evidence fabrication. Source: Rossiyskaya Gazeta

🇺🇸 USA: Lawyers lost their licenses over "invented cases" In 2024, several attorneys cited non-existent precedents generated by ChatGPT in court filings. • The court invalidated the references. • Cases were lost. • One attorney lost their job and license. Source: BBC

🇬🇧 UK: High Court vs. AI fiction Lawyers submitted 45 case references — 18 turned out to be fabricated. In another instance, 5 rulings simply didn't exist. • The court imposed sanctions. • Materials were referred to regulators. Source: The Guardian

🇦🇺 Australia: Error in a murder case A King's Counsel used AI to prepare documents. Result: false citations and rulings that never existed. • The proceedings were delayed. • The lawyer had to publicly apologize in court. Source: AP News

🇨🇦 Canada: Costs awarded for "hallucinations" A lawyer in British Columbia cited fictional cases. • The court ordered him to pay the opposing party's legal costs. • The judge made clear: AI is no excuse for negligence. Source: HCAMag

What experts say: • AI doesn't replace a lawyer's work — it only suggests. Verification is mandatory. • Even professional legal systems (Lexis+, Westlaw AI) hallucinate in 17–33% of cases.

The takeaway: Use AI as an assistant, not as an authority. The safest move is to verify every fact and reference manually. A hybrid approach works best — an automated service collects facts (and can't fabricate anything), AI synthesizes and analyzes, and a human draws the conclusions.

#AI #LegalTech #Hallucinations

🏺 Business Is Over 5,000 Years Old!

Friends, I found yet another "oldest profession" 😂

The earliest recorded transaction dates back to around 3200 BCE in the ancient city of Uruk, Mesopotamia (modern-day Iraq). It was a barley supply contract inscribed on a clay tablet.

How long ago was that? About 5,225 years!

It turns out humans have been doing business and signing deals for more than five thousand years. If we ever thought business was something "trendy and new," let's remember Uruk — it started with barley and clay tablets, and today it's easier than ever to begin with an idea and back it up with numbers.

Have a great one! #brandstories

📣 Quotes from the Classics of Marketing

Happy New Year! 🎄

The mandarin level in the bloodstream is finally dropping, so let's ease back in. I've wanted to write about marketing for a long time — but it's such a vast, well-worn topic that you can't just dive in from anywhere. So instead of an overview, here are quotes from the people who actually built this discipline. Let's see what they said.

1) Peter Drucker (management classic) "The aim of marketing is to make selling superfluous — to know and understand the customer so well that the product fits them and sells itself."

Marketing isn't about pushy sales. It's about understanding the customer so deeply that selling becomes the natural result of a great offer.

2) Philip Kotler (author of "Principles of Marketing") "Marketing is not the art of selling what you make. It is the art of creating genuine value for the customer."

My personal favorite. Research what people will buy first — then produce it. 👍

3) Seth Godin (author of "This Is Marketing") "Marketing is no longer about the stuff that you make, but about the stories you tell."

Today, marketing is the narrative that creates a connection between product and customer — not just a feature list. Founder blogs, viral reels — all of it feeds into this.

4) Gary Vaynerchuk (entrepreneur and marketer) "The best marketing strategy ever: care."

It's about empathy and focus on the human experience. Marketing doesn't start with the product — it starts with wanting to understand another person.

5) Tom Fishburne (marketer and author) "The best marketing doesn't feel like marketing."

When a customer perceives the offer as value — not a "marketing trap" — it works better. Nobody likes being sold to.

6) David Ogilvy (father of advertising) "The customer is not a moron. She is your wife."

Simple and sharp: respect the consumer's intelligence. They see manipulation for what it is.

In summary: 🔹 Marketing starts with the customer, not the product 🔹 Value beats hacks and ads 🔹 Stories and care build lasting connection 🔹 Marketing makes the sale feel logical, not imposed

Have a bright one!

#marketing #entrepreneurship