Vibecoding, AI agents, first attempts, first failures, first win
feels like 2026 will be the turning point where AI literally becomes an irreplaceable tool
letting us build things that previously required at least 10 devs
solo, with almost no money spent
not counting buying credits in Claude Code
just having a concept and a clear understanding of what you want to build
i've been on fire for a long time to build my own product
and i even generated $17k in 5 days building my first app
but also, while doing research, i highlighted for myself 5 best crypto tools you can build with vibecoding right now
this article won't have ready prompts, or something you can just CTRL-C & CTRL-V
but it will have something more valuable, a framework and structure for each idea
exactly what you need to understand to build a really useful app
let's break down each idea step-by-step
and figure out how to extract maximum efficiency from it
for personal use or for selling
P.S in the end i'll reveal the app where i made $17k in 5 days, building it with $0
READ TILL THE END!!!
First steps to building your own app (or so-called preparation)
personally i always looked for competitors first, to understand whether this idea can really function
this is a must-have if you're not a dev and don't understand many technical experience
then i opened existing live products and went through their docs to understand how each of them works
most of the time it's connecting required APIs, structured usage, returning the data we need or specific filters like spread search for potential arbitrage opportunities
once you understand your competitors and the volume they're doing, the potential revenue you can reach becomes obvious
having zero exposure and building the first thing that came to your mind makes no sense
it's like trading the first memecoin you saw on pump.fun, what's the result???
rekt, disappointment, opinion that the niche doesn't work, even though it does, the approach was just wrong
okay, we analyzed competitors, their technical stack, promotion methods, what's next?
next you need to at least minimally structure everything in Notion or any app that's convenient for you
i also often build dashboards in Figma with everything i need, including the visual part
but honestly, you don't even need it
most products can function as a Telegram or Discord bot, so visuals are no sense at this stage
don't waste time on UI/UX if we're talking about crypto products
the audience is already adapted to bad UI/UX
build a working product first
then you can buy proper UI/UX from a designer after you get your first revenue
our focus: build the solid technical stack that executes your functions efficiently
using APIs and other tools you need, depending on what exactly you're building
personally i'll highlight super clear examples here
you definitely heard about them before
but i haven't seen anyone fully break down the technical concept of how it should work (specific promotion methods from marketing & advising perspective)
let's lock in
1: Arbitrage bot between CEX & DEX
the core idea of this product is searching for situations where the price on CEX and DEX differs so much that after all fees / gas / funding rate / delay risks you still stay in profit
but important clarification, it doesn't work like you just track the price, buy on CEX and sell on DEX
most of the time deposits are closed or there's a long waiting time, and the price equalizes before your deposit arrives
most often this strategy works through hedge
for example: buy on DEX, and on CEX instead of selling spot you short the perp (or vice versa)
you lock the spread, and then deliver the asset / rebalance
usually such products look like a Telegram bot that sends you all similar situations, and you manually analyze them
although it's a pretty heavy product, and inside there are a lot of potential problems
Potential problems when building an arbitrage bot between CEX / DEX:
delays in price updates and desync, which will return incorrect data
fees (maker / taker, funding if you hedge with perps, gas, aggregator fee)
slippage: on DEX depends on volume, on CEX depends on orderbook depth
partial fills on CEX and the need to chase the second leg
CEX limits / API ban if you fetch and place orders too aggressively
Withdrawals / deposits: pauses, delays, compliance, fees
MEV / sandwich: if you expose your swap to the public mempool (only relevant if you're a whale, <$1k no one cares, sometimes even <$100k)
Technical architecture of a CEX-DEX arbitrage bot:
let's be objective, let's look at it as a set of modules, what you need for it to function correctly
and even then, all of this still needs to be tested and you'll have to fix issues that will show up
1. Data collectors (data scraping)
basically, you need to always have real-time data from both sides
the CEX collector should connect to the exchange via API and fetch best bid/ask, orderbook depth, funding rate for perps
the DEX collector should run a simulation: if you swap $X right now, how many tokens you really get
and if the result shows a spread, that's what you need
even a 1-5 sec delay can already play a huge role
2. Brain / opportunity calculator
this module should take the numbers and answer one question
"do we stay in profit after all fees, gas, slippage, and delay risk???"
it needs to calculate the real net edge:
the difference between CEX price and the DEX swap result
minus maker/taker fee on CEX
minus funding rate (if hedge via perps)
minus gas + aggregator fee on DEX
minus expected slippage
minus safety buffer (in case price moves while you execute)
if the edge is small, ignore it, and it's crucial that it's true
almost all "beautiful spreads" disappear when your bot calculates net edge properly
3. Risk filter (double-check)
even if the trade looks profitable, the bot should re-check everything before sending it to you
check gas, CEX limits, and whether the size is too big for the orderbook / pool
4. Telegram delivery layer
you need to set it up so the deal is sent to you in a user-friendly Telegram format, in real time
ideally with direct links to perps and the DEX, so you don't waste time
also checks of all suspicious moments, so the bot does it instantly and shows it in logs
5. Security
it's important to add a Kill Switch function, so the bot shuts down on errors and sends you logs with what went wrong
and most importantly, on your CEX API keys disable everything except read-only data access, turn off Trade and Withdrawals
so even if someone gets access to your API key, they can't do anything with it
and of course test a lot, while you build it via vibecoding, a ton of issues will appear that you'll need to fix
even when experienced devs built this, they still fixed a lot of problems, be ready for it
Methods to promote this product:
most often it's your real cases where you made profit on arbitrage
build your own community, start growing your personal brand, share your trades
people will get interested in the product themselves if it really works
you literally need $0 to promote a good product, trust my experience
all good products i built were built on <$50k budget or even $0
and only when they started doing their first $100K–$1M revenue
that's when liquidity and paid ads budget were actually needed
2: Prediction markets arbitrage bot
the core idea of this product is to find situations where the same event is priced differently across prediction markets
and you can lock profit by buying "YES" where it's cheaper and "NO" where it's mispriced on another platform (or selling YES where it's overpriced)
but important clarification, this is not classic arbitrage where price equalizes instantly
here inefficiency can hang for hours or even days, and the main difficulty is not "finding the spread"
the main difficulty is understanding whether it's truly the same event by resolution rules
and whether you'll be able to exit properly / or be stuck until final settlement
most often this works in 2 formats:
default arbitrage between two markets that resolve on the exact same event (true arb if settlement is identical)
semi-arb where markets are "almost the same" but wording differs (bigger edge, bigger risk)
usually such product looks like a UI/UX dashboard that shows these spreads
or a Telegram bot that sends you all mispricing situations
and you manually decide whether it's a real edge or just maximized conditions
the product is heavy, just like the previous one
and inside there are many places where you can mess up
Potential problems when building a prediction markets arb bot:
same event ≠ same market: wording, resolution criteria, timezone, volume, who resolves and how – this is #1 reason people get rekt
liquidity is often small, you see huge spread but can only deploy $50-$100 before price moves against you
different mechanics: orderbook vs AMM – on some platforms it's depth-based, on others AMM, and price behaves differently
long waiting time – sometimes you need to wait for resolution, price doesn't move, no buy/sell pressure
fees: trading fees, slippage inside the order-book
manipulation and spoofing – fake depth in order-book so you see an edge that doesn't exist and close on you
Technical architecture of a prediction markets arbitrage bot:
objectively, it's similar to the previous bot, but with a couple of very important clarifications
even then, you'll still need heavy testing, reality will break theory
1. Data scraping
you need real-time data for every market you support
depending on the platform this includes:
orderbook: best bid/ask, depth, recent trades
AMM: price simulation
metadata: rules, resolution source, expiration time
2. Event matching layer
the most important module, it must answer, is this really the same event
basically it should:
group markets by themes (politics, crypto, esports, etc.)
find candidates that look like "about the same thing"
assign confidence score
deeply compare metadata and catch tricky resolution wording
3. Brain / opportunity calculator
this module calculates real profit after all fees and realistic fills
because prediction markets often show painted orderbooks with low real liquidity
it must calculate net edge:
effective entry price for $X size on market A (after slippage / depth)
effective entry price for $X size on market B
fees + gas + bridge (if needed)
best structure: buy YES here + buy NO there, or sell where overpriced
max size you can realistically deploy without killing the edge
4. Risk filter (double-check)
the most important thing here is max size and settlement risk flags
i've heard many cases where resolution went against reality just because of ambiguous wording
and of course evaluate time expiry, so you don't lock liquidity in one trade too long
interesting approach, sell before resolution if you see price moving in your favor on one of the markets
5. Telegram delivery layer
same as previous, don't build UI/UX at start, just make it a Telegram bot
bot should send:
event name + links to both markets
YES/NO prices on both platforms
net edge after fees
max safe size based on orderbook depth
warnings like low liquidity or ambiguous resolution rules
Methods to promote this product:
best promo case is real examples where you made profit using your own bot
screenshots of both platforms, clear explanation of the strategy, your plan and execution
just look at the reach @the_smart_ape got when he announced his bot, you'll understand...
once you build a community around "market inefficiencies", it becomes easy to even sell the product, if it really works
especially with hype around Polymarket and prediction markets cult
compared to many other products, this one should be much easier to push
3: Aggregator scraping data useful for traders & creators & web3 users
the core idea of this product is scraping data that you constantly have to search manually
basic news digests and other raw info, and delivering it in a clean format into Telegram or a proper UI/UX dashboard
so this is not another news bot, it's an aggregator that brings chaos from all sources into one place
important clarification, scraping is not just parsing websites
if you just pull HTML and forward text, that's literally nothing
real value, where AI shines, is normalization + extracting what actually matters
Technical architecture of a crypto data aggregator:
the main goal is stability + real value for the user
most often it can be digesting channels if one ticker gets pushed many times
or some important news you need to know on time
many trench traders use scraping bots to see who changed avatar first or edited something
it all depends on the source you care about, use case will be different for everyone
you can apply it based on your imagination and what you personally find useful
scraping data has always been alpha, for example parsing specific data and building a dashboard around it
everyone needs it, and this way you also grow your personal brand on X
1. Source connectors (scrapers + APIs)
you'll need a mix of APIs and web scraping
because some websites don't have APIs
official APIs
RSS / public JSON
web scraping (where no API exists)
each connector must be able to:
fetch data at proper intervals
retry on errors
check if the source is down
have fallback secondary sources
2. Normalization layer (bring everything into one format)
everything must be unified into a format that's convenient for you
especially split by event types like listing, unlock, governance, exploit
this makes tracking much easier, also store source + entity id + other metadata
without this layer, it's not an aggregator, it's just forwarding raw text
3. Anti-spam + clustering layer
you need logic that merges identical events from different sources
so in the end you get one clean update, with all collected details
and if new info appears, update the previous message and send an update in the bot
4. Scoring + filtering layer
this is more personal but extremely important, you can assign importance to each update
for example configure priorities inside your bot, based on what you currently trade or focus on
if you're trading new listings or low-liquidity pairs, set them as priority
create simple scoring per update: high / medium / low
scoring can adapt algorithmically based on previous score, add your own manual rating to each update, and fine-tune priority over time
5. Storage + delivery layer
you need clear history + fast search via hashtags or convenient UI/UX
without a proper database, you won't be able to evaluate updates and filter personal preferences
delivery layer should be user-friendly, this is the product where UI/UX actually matters
commands, filters, fast links to original source, short summaries
Methods to promote this product:
best move is to build a dashboard that's actually useful, for example tracking closed airdrop sites, or specific wallet tracking
all of this is scraping / parsing data
the key is to show that your aggregator filters data properly, share real cases you executed using it
pick a niche and sell alerts for that niche, people always paid for fast scraping of relevant data
private alerts, trader stats from platforms without API, everything fits into this structure
finding the use case is on you
4: Agent built on you for cold DMs and outreach
the core idea of this product is to build an agent that finds the right people and writes them cold DMs as if it's you
important clarification: this is not a spam bot
because mass blasting = account ban, reports, negative reputation
real value is building a personalized agent with proper context and clean targeting
i understand the value myself, as a founder of accelerator @arcane_hq this would save me tons of time and money
because often i hire BDs just to send cold DMs in my tone-of-voice
Potential problems when building a cold DM agent:
spam risk, if messages are generic and without context
bad targeting, if the agent writes to the wrong people
no memory / no state, if the agent doesn't remember who it contacted and who replied
data privacy, since your agent will store full database of cases, clients, scripts
platform restrictions on AI agents, like X did
so right now this idea is realistically for LinkedIn
maybe X will allow AI agents in future, but currently it's restricted
Technical architecture of a cold DM agent:
let's be objective, this seems simple for everyone, no complex math or algorithms
but certain points make this bot heavy to execute
1. "You model" (your style and brain)
everything that makes you "you" must go here, if this foundation is weak, nothing works
you need to feed the agent everything:
your tone-of-voice
your offers (what you sell, for who, what result)
your cases, numbers, proof
forbidden phrases (what never to say)
what to do in uncertain situations
in this way DMs becomes grounded context
2. Targeting (ICP + rules engine)
extremely important to define who you write to
niche, role, geo, stage, partnership potential
and add safety rules:
don't message competitors, clients, toxic categories
don't send more than N per day
don't resend after rejection
3. Lead sourcing (no just scraping)
define the source of potential clients, give it database, community, structured search logic
focus on fewer but more relevant leads
interesting part, even lead sourcing alone can be a sellable product
4. Enrichment (human context)
agent must gather at least 3-5 facts about the person
difference between spam and real DM = context
automate research:
what they worked on
what they recently launched or posted
who they hired
what product / audience they have
this builds trust that you're human (p.s lol ironic when we're building an AI agent)
5. Message generator (DM drafts)
final stage: generate actual messages (generator takes your style + lead context + offer)
and produces 2-3 DM variants
6. Safety / compliance filter
must add module that checks for hallucinated facts
over-aggressive selling
personal data misuse
AI loves to invent things
especially promises, filter this
7. Human-in-the-loop (approve first)
connect minimal UI/UX or Telegram bot
agent sends drafts, you approve, MVP must work this way
so you understand how it behaves, and adjust prompts / filters / sourcing
8. Follow-up engine (most profitable)
90% of money is in follow-ups, not first message
as someone who worked in sales, this is must have
no reply after N days → follow-up #1 → #2 → then stop
each follow-up must add micro-value, not just "ping"
9. CRM + analytics
store who you contacted
what message
status
responses
tags
rejection reasons
and most important test prompts and collect analytics:
reply rate
positive rate
booked calls
ban/risk signals
which intro works
which CTA converts
Methods to promote this product:
best marketing is using it yourself, sales and connecting can be your own work
you can help others find the right people, this system fits any marketing agency
not only web3, agent saves 2+ hours daily, and generates consistent leads
almost like setting up a sales flow for Wall Street brokers back in the day haha
5: you really believed i made $17k in 5 days???
yes, there won't be a 5th idea here
but there will be something way more valuable than what you were hoping for
false expectations are the scariest thing you'll face on your path
it's LITERALLY UNREAL to build an app in 5 days that generates profit
and consider this, if you have 0 technical background, 0 understanding of building, even 6 months will be hard
and you're reading till the end hoping to hear some cheat code just because i'm Ronin?
i'm Ronin because for last 5 years i've been working 12/7/365, sometimes even more
i started learning programming at 12, it was my hobby, i won multiple math olympiads
and even then, trust me, real understanding only started forming recently, and it's STILL hard for me to build apps
this is not simple, even with connections, experience in building, advising, marketing
the desire for fast money is one of the biggest problems of this generation
and those who don't get rid of it will earn less in the long run, than those who moved slower but consistently
what do you feel when you fail after 5 days? disappointment?
most successful founders launched their real businesses at 30-40
most of my audience isn't even 25 yet, why the rush?
who's stopping you from joining a company and gaining experience first?
and no, i'm not discouraging you from vibecoding, do it 24/7, chase your goal, but it won't happen in 5 days
it won't happen in a week, or two, it will take at least 3–6 months
and then you'll face marketing, you might realize you built something nobody needs
no competitor research, no promotion analysis, no idea where to start, $0 budget
what's next?
burnout, apathy, disappointment...
i can test products for free because i have my audience, and i'm insanely grateful for that
social capital is one of the most valuable assets in the 21st century
AI evolves faster than humans build real relationships
don't set unrealistic expectations, don't demand from yourself like you're a 40-year-old entrepreneur
focus on quality, on gaining experience, on building strong connections
people stay with you if you're ambitious and honest, after first, second, even third attempt
just stay honest, stay consistent, keep trying, stay open to new connections
maybe this was a better conclusion than any other in my articles
gl ❤️
