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Pepenode’s presale just passed the $800K mark, following a surge in investor interest shortly after it started.

The project’s appeal comes from its mine-to-earn mechanics, which enable meme coin mining in a customized rig, but that’s not necessarily the innovative part.

The innovative part is that you get to craft your own rig yourself and customize its nodes for higher hashrate, energy, and rewards. It’s also quite advantageous that you don’t have to deal with high energy bills or need to upgrade your system to handle the higher mining throughput.

This makes Pepenode ($PEPENODE) extremely appetizing for investors who prefer to control the rewards they’re getting from a presale.

How Pepenode Changes the Way Crypto Mining Works

Crypto mining is a good way to boost your portfolio without investing in the assets themselves. Instead, you invest in building and refining your mining system to maximize output, lower energy costs, and decrease the wear on the mining rig itself.

Once you’ve figured those factors out, you’d have created a source of passive income.

Unfortunately, the mining business comes with severe limitations and problems which are baked into the system itself. These include the high costs associated with building the rig, the high electricity bills, and, last but not least, the lack of interactivity.

Pepenode addresses all these problems during its presale by turning mining into an engaging and rewarding activity with its mining simulator.

The process is simple: buy the nodes, build your virtual mining facility, upgrade it, and start earning.

The nodes are tiered, so you can upgrade them gradually to boost your facility’s mining output and energy efficiency.

Unlike traditional mining, Pepenode achieves two things: it makes crypto mining engaging and more accessible and drives investor engagement during presale.

You no longer need expensive, premium rigs, expertise, and extra capital to cover for the spicy electricity bills. Pepenode does everything for you, offering a sense of progression and rewarding proficient miners.

Pepenode is compatible with MetaMask, Trust Wallet, and WalletConnect and is currently only accessible via your web browser. The mobile version will release after the public launch.

The mining platform also has a detailed dashboard showcasing the most important stats like hashrate and rewards, allowing you to keep track of your progress and performance.

Pepenode offers plenty of incentive to join the presale early on, including higher staking rewards for holders (1,786% now) and additional rewards in meme coins and other bonuses for top-performing miners.

Pepenode Presale Numbers and Roadmap

The Pepenode ($PEPENODE) presale is at over $800K right now with a token price of $0.0010491 and it’s gaining traction fast.

If you want to join in, now’s the perfect time given the early incentives, including the staking APY of 1,786%, which will drop the more investors join the staking pool.

The four-phase roadmap details a long-term developmental phase, with the Virtual Mining Simulator going live in Phase 3.

Phase 4 is the real kicker, since it introduces meme coin rewards like $PEPE and $FARTCOIN and allows for a more expansive customization process to make your mining rig more effective.

The coming partnerships with influencers and other meme projects will also help increase visibility and potentially drive Pepenode into the mainstream.

Based on Pepenode presale’s growth rate and scope, our price prediction for $PEPENODE considers a price point of $0.0023 by the end of 2025. By 2030, the token could reach $0.0244 with sufficient community support and involvement.

Should You Buy $PEPENODE?

Whether or not you should invest in $PEPENODE depends on your risk tolerance and investment strategy. However, Pepenode shows great long-term potential thanks to its mining simulator, which keeps investors engaged and rewards their loyalty with actual meme coin drops.

If you want to invest, you can read how to buy $PEPENODE right here and finalize your transaction on the official presale page.

But remember do to your own research. This is not financial advice.

Authored by Bogdan Patru, Bitcoinist – https://bitcoinist.com/pepenode-presale-reaches-800k-allows-users-to-mine-meme-coins

Editorial Process for bitcoinist is centered on delivering thoroughly researched, accurate, and unbiased content. We uphold strict sourcing standards, and each page undergoes diligent review by our team of top technology experts and seasoned editors. This process ensures the integrity, relevance, and value of our content for our readers.

This short video of percussionist and sound effects specialist Josh Harmon (who describes his work as “spreading joy through sound and rhythm!”) collaborating with musician, composer, bandleader and all-around national treasure Jon Batiste to create vintage cartoon sound effects, is exactly the joy-filled experience I needed to witness today.

In the background of the video, you can see a vintage cartoon clip from 1934, from an episode of Popeye called “We Aim to Please.” In the clip, Olive Oyl is busy frenetically making sandwiches. Josh marvels that “it’s amazing to think that these animations were all made by hand without computers,” which is what he recreates in his work. Using tools and materials such as drum sticks, fabric, a slide whistle, and an exercise band, Josh creates sound effects that perfectly match Olive Oyl’s cartoon actions of slicing bread, cutting meat, and more. My favorite part is when Olive Oyl assembles the giant sandwich through a kind of playing card-shuffling move, and Josh flip-flaps his hands back and forth quickly to create the perfect sound.

Of course, I also LOVE watching and listening to Jon Batiste perform just about anything, and his rendition of Scott Joplin’s classic piano rag, “The Entertainer,” is as good as it gets, and fits wonderfully with the Popeye cartoon.

Harmon expresses his excitement about working with Batiste in the video’s caption, stating, “Holy moly it’s an honor to welcome musical icon Jon Batiste onto the channel! The way he thinks about music and sound is so inspiring. Joy levels were reaching unprecedented heights in this room! And his new album BIG MONEY is out now!”

Harmon also promises that next week he’ll be releasing “a long” video that details “the whole process of how we made this, and more!” I can’t wait to see a behind-the-scenes demonstration and learn more about the process of creating cool sound effects!

Enjoy the video, below. I hope you love it as much as I do!

See more of Josh Harmon’s amazing sound effects work at his Instagram or YouTube.

Previously:
• Fred Armisen’s 100 Sound Effects album coming soon!
• BBC sound effect archive posted online
• Don Martin’s sound effects (alphabetical order)
• How some old cartoon sound effects were made
• Watch these fascinating demonstrations of sound effect instruments from the silent film era!

Connect the Electrum client

To connect to an Electrs server, you must use Electrum to point it to the server. ip_address:port syntax. You’ll notice that most default servers in Electrum use it 50002 Port (for SSL connections), while the electric service port 50001 Also, it does not provide SSL from the box.

You must use a web server to provide SSL (see SSL connection (below) or connect without SSL. To tell Electrum to connect to the server without SSL, you need to add it :t After the port (i.e.: localhost:50001:t). Please note that this is not secure and is recommended only for local connections.

Electrs listen by default 127.0.0.1:50001which means serving only clients on the local machine. this is, electrum_rpc_addr If you want to connect from a different machine with the settings, you will need to change it 0.0.0.0:50001. This is not safe and the recommended way to access electricity remotely is to keep listening 127.0.0.1 Tunnel to the server.

The 50-200 Moving Average Crossover is an easy concept to build a trading strategy around because the inputs are simple and the potential optimizations are straightforward.

So it’s perfect if you’re just getting started with trading strategy development.

Many trading websites will give you what they say is the “best” 50-200 crossover strategy.

Interestingly, most of them don’t give you any data to back up that claim.

I’m going to give you information that’s much more useful.

In this tutorial, I’m going to show you how to backtest any Moving Average Crossover trading strategy on the internet to find out for yourself, if it really works or not.

Using this method will also allow you to test your own optimizations to see if you can improve on the strategy.

The best part is that you can use this method to backtest strategies very quickly because the backtests will be 100% automated.

You don’t need to know how to write code to do this, it’s all drag and drop.

I’ll also show you some of my own backtesting results so you know good places to start with building your own strategy, and what to avoid.

Alright, let’s get into it…

What is the 50-200 Moving Average Crossover Strategy?

This trading strategy is also known as a Golden Cross and Death Cross.

That’s way too much drama for me, so I’m just going to call it the 50-200 Moving Average Crossover trading strategy.

As the name suggests, this strategy uses the 50 and 200 Simple Moving Averages (SMA).

Here’s what that looks like on a chart.

The 50 SMA is considered the “fast” SMA because it reacts faster to price changes.

So naturally, the 200 SMA is the “slow” moving average because it takes awhile to react to price.

Basically, traders who use this method buy when the 50 crosses above the 200 and sell when the 50 crosses below the 200.

Sounds pretty easy right?

Well, not quite.

There are a few more things that have to be defined to make this a complete trading plan.

First, I’ll create the trading plan, then I’ll show you how to do an automated backtest of the plan, without writing a single line of code.

The 50-200 Crossover Strategy Trading Plan

Here are the rules for this plan:

• Buy
  • Buy on the close of the candle when the 50 SMA crosses above the 200 SMA
  • Stop Loss at last swing low
  • Risk 1% per trade
  • Take profit at 1R (1 times risk)
• Sell
  • Sell on the close of the candle when the 50 SMA crosses below the 200 SMA
  • Stop Loss at last swing high
  • Risk 1% per trade
  • Take profit at 1R (1 times risk)

Remember that this is just a starting point.

Any of these settings can be changed and retested. 

So do a couple of tests with these settings, then feel free to experiment with your own settings.

Get creative.

You never know, you might just develop a super profitable moving average crossover trading strategy.

How to Build the Automated Strategy

Now let’s get to work.

For this backtest, I’m going to use NakedMarkets.

It’s the easiest way to build automated trading strategies with no-code.

Once you complete these initial setups, you’ll be able to test all of your 50-200 moving average crossover trading strategy ideas easily.

Create the Core Rules

The first step is to create the Core Rules.

This is what will tell NakedMarkets how to identify the initial setup conditions for a trade.

You have to create one Rule for long trades and one for short trades.

This will also be true for most of the other types of Rules.

Here’s how to setup your first Core Rule:

1. Open NakedMarkets and go to: Rules > Rule Manager
2. Click the New Rule button in the lower left corner of the window
3. Name the Rule in this format: [strategy name] Core [long or short]
4. Select Core as the Rule type
5. Click OK

Now it’s time to add conditions to your new Rule.

Long Trade 

Let’s setup a long trade.

To add a criteria, click the (+) symbol in the upper right corner of the screen.

From there, drag the conditions you want to use from the list on the right.

These are the settings for each of the boxes, from left to right:

1. Moving average: Period (50), MA Type (SMA)
2. Greater than
3. Moving average: Period (200), MA Type (SMA)
4. And
5. Moving average: Period (50), MA Type (SMA), Previous Bar (1)
6. Less than
7. Moving average: Period (200), MA Type (SMA), Previous Bar (1)

The reason that I’m putting 2 moving average comparisons in there is because I want to evaluate the position of the 50 SMA relative to the 200 SMA for the current candle and the previous candle.

I want to see the previous candle have the 50 below the 200 and the current candle have the 50 above the 200.

This will give me every situation where the 50 has just crossed above the 200.

If I don’t do this, I will get a signal every time the 50 closes above the 200 and that would not work.

This is what your screen should look like after you’re done.

Click on the Save Rule button in the lower left corner to save your Rule.

Now I’m going to do the same thing for the short side.

Short Trade 

Here’s how to setup the Core Rule for a short trade.

The easiest way to create a new Rule is to clone the long trade and just change the settings that apply to a short trade.

To clone a Rule, right-click on the long Rule in the list on the right side of the screen and select Clone Rule.

Then right-click the cloned Rule and rename it.

Change “long” to “short” in the name.

So in this example, the new name of your short trade will be: “MA Cross Core Short”.

Now it’s time to change the settings of this Rule to look for short trades.

This is what the short Rule looks like:

Here are the settings for each of the boxes, from left to right:

1. Moving average: Period (50), MA Type (SMA)
2. Less than
3. Moving average: Period (200), MA Type (SMA)
4. And
5. Moving average: Period (50), MA Type (SMA), Previous Bar (1)
6. Greater than
7. Moving average: Period (200), MA Type (SMA), Previous Bar (1)

Click on Save Rule in the lower left corner to save your Rule.

Great work, you just completed the hardest part of this tutorial!

There are 2 more steps that you have to complete before you can start testing this strategy, so let’s keep going.

Create the Entry Rules

Now that you have the Core Rules that will identify the basic criteria of the entry, it’s time to create the Entry Rule that will determine the details of each entry, such as the entry type, stop loss, risk per trade and stop loss.

To do this, go back into the Rule Manager and click the New Rule button in the lower left corner of the screen.

Again, we will start with the long Rule, then clone it to make the short Rule.

Long Rule

Name your long Rule: “MA Cross Entry Long”.

Here’s what your long Entry Rule will look like:

For the order type and lot size, double click on the box to change the settings.

With the other boxes, drag the appropriate Default Rule from the upper box on the right side into the stop loss and take profit boxes.

Here’s how to set that up:

• Instant Order: Buy
• Stop Loss: Last swing low
• Take Profit: 1R
• Lot Size: 1%

Click on the Save Rule button in the lower left corner to save your Rule.

Short Rule 

Now clone the long Rule and use these settings to create the short Rule:

• Instant Order: Sell
• Stop Loss: Last swing high
• Take Profit: 1R
• Lot Size: 1%

Click on the Save Rule button in the lower left corner to save your short Rule.

Create the Setup Rules

Alright, these are the final Rules!

Don’t worry, this step is super easy.

A Setup Rule basically ties everything together and monitors your chart to see if the Core Rule criteria is present.

If it is, then it executes the Entry Rule.

Long Trade 

Go back into the Rule Manager and click the New Rule button in the lower left corner of the screen.

Create a new Setup Rule, then name it: “MA Crossover Setup Long”.

First, drag the Core Rule you created from the User Rules section into the top Setup Condition box.

Under Actions, drag the Entry Rule you created into the Actions box.

Now clone this long Rule and rename it to create the short Rule.

Short Trade

Replace the Setup Condition and Action with the short trade versions of your Rules.

That’s it for Setup Rules!

Run the Backtest in Visual Mode

That was pretty easy right?

Now here’s the fun part, you’re going to actually backtest this strategy.

You should do this step first, before using Fast Backtest because it will allow you to see any errors that you made when creating your Rules. 

Close the Rule Manager and go back to the main NakedMarkets screen.

Start a backtest by going to File > New Backtest.

Name your backtest, then select your starting balance.

Click on Next.

Select the market(s) you want to include in the test, then click on Next.

On the next screen, you can select the timezone you want to use.

I usually use the default settings, so if you aren’t sure about your timezone, just use the default settings.

Click on Next.

Now click and drag both the long and short Setup Rules that you created onto the chart.

You’ll see these Rules that you’re currently using in the upper left corner of the screen.

Select the right timeframe that you want to backtest on.

The timeframe shown above is the daily chart.

Then click on the Play button in the toolbar to start the backtest.

If you setup your Rules correctly, you’ll see the trades automatically execute on your chart.

Watch the trades carefully to be sure that they are executing correctly.

Now if your trades are not executing correctly, see the section below on troubleshooting.

However, if they are working, then congratulations, you have just build your own automated 50-200 Moving Average Crossover trading strategy!

Once the backtest is completed, you can see the detailed stats by doing the following:

• Save the backtest by going to: File > Save Backtest
• Go to: Statistics > Statistics Center
• In Stat Center, go to: Source > Import from backtest
• Select the backtesting file you just saved

This will show you the stats on your backtest.

A word of caution here…

You probably won’t have a super profitable strategy on the first try.

However, remember that this is a process and your results could be significantly better if you use different settings or run it on a different timeframe or market. 

You might get better results on the EURUSD 4-hour chart, or the SP&500 1-hour chart.

The return might be better if you use a different stop loss or change the moving average settings.

Again, don’t get discouraged if your first test doesn’t work out.

Remember that this will require some work and very rarely will even professional traders gets an awesome result on the first try. 

Therefore, be willing to experiment and treat this process like an inventor would.

Many times, inventors have to try many different prototypes before they get something that works well.

It’s been said that Edison tried 10,000 ideas before he invented the light bulb.

Hopefully you won’t have to try that many strategies before you find a good one, but you have to be willing to potentially stick it out for that long.

Regardless of the return on your first test, once your strategy is working in Visual Mode, now it’s time to shift your backtesting into high gear.

Hit “Turbo Boost” and Run a Fast Backtest

Now that you’re confident that everything is working correctly with your moving average crossover strategy, it’s time to take your backtesting to the next level.

In this step, you’re going to unleash “turbo mode” and use the Fast Backtest feature in NakedMarkets.

This will allow you to backtest multiple markets and timeframes, without having to setup each backtest individually.

To do this, go to: Tools > Fast Backtest

Then select the market(s) you want to backtest.

You can test as many as you want.

Click on Next.

Next, choose the timeframe(s) you want to backtest.

Again, you can select multiple timeframes.

Click on Next.

Now select the Setup Rules that you want to backtest.

Select the moving average crossover Rules that you created above, under Setup Rules.

Click on Next.

Then you’ll see the list of Fast Backtests that will be run.

Click on Launch to start the backtest(s).

Once a backtest is finished, you’ll see the basic statistics in this window.

There is also a link to the detailed stats in the [Load stat] link.

Click on the link to open Statistics Center and you’ll see the complete results of each backtest.

As you can see, this test on the daily chart didn’t work well.

But at the same time, it wasn’t completely terrible either.

At least it was profitable for a period of time.

Losing 4.25% from 2006 to 2024 is also essentially breakeven.

So this strategy could be improved by using different settings in the strategy.

Again, this is a process and don’t get discouraged by poor results on your first tries. 

Troubleshooting Your Rules

Even with a simple trading strategy like this, it’s possible to make mistakes in the Rule creation process.

This is especially true when cloning Rules.

I actually made couple of mistakes when creating this tutorial.

So if your strategy isn’t working as you expected, don’t worry.

Just go back through the steps above and double check your Rules.

The most common mistakes are:

• Not changing the greater-than or less-than criteria.
• Having the wrong trade direction (buy or sell)
• Using the wrong settings for an indicator

If you cannot see the error by just looking at the Rules, then there are 2 more things you can to do troubleshoot your strategy.

First, in your Setup Rules, change the Action to Pause Backtest, instead of using the Entry Rule as the Action.

This will take the Entry Rule out of the equation and allow you to only focus on the Core Rule.

Right-click on your chart and select: Detach all Rules.

Then drag your new Setup Rules onto your chart and run the backtest again in Visual Mode.

Every time the trade sets up, the chart will stop.

This will allow you to double check the logic of the Rule.

If your Core Rule is working correctly, then the mistake should be in your Entry Rule.

To test this, simply use the Entry Rule by itself by dragging the Rule from the list on the left of the screen onto the chart.

You can do this at any time, you don’t necessarily have to wait for your entry criteria to be met.

This will open a trade and allow you to see if your Entry Rule is working as expected.

These methods will allow you to debug your trading strategy.

Stay calm and go through your Rules step-by-step.

If you cannot find the problem, head over to the NakedMarkets Forum and ask for help.

Potential Improvements

If you didn’t get the results you were looking for in your backtests, here are a few ideas on how you can potentially improve your results:

• Change the period of the moving averages
• Use different types of moving averages, like an exponential moving average
• Test different timeframes
• Adjust the settings on the last swing high/low indicator
• Test different markets
• Use a different stop loss level
• Use a different take profit level
• Trail your stop loss
• Risk more per trade
• Risk less per trade
• Add another indicator to create a second entry criteria
• Use a strategy across multiple timeframes or markets at the same time to potentially increase profits and diversify risk

But don’t stop there, what else can YOU think of?

Backtesting Results

All of this is great in theory, but how well does this strategy actually work?

That’s what you’re going to find out in the following links.

I’m going to backtest different ideas around this trading strategy, starting with the method described above.

The version above will be version 1 and I’ll create a new version every time I make a change to the original strategy.

Rules for new versions will be available via the links below.

As I do new backtests I’ll add them to the appropriate pages.

You’ll see all of the stats for each backtest.

Even if a backtest doesn’t do incredibly well, it can give you a starting point for creating a strategy of your own.

These tests also show you what to avoid and will save you time in the testing process.

Here are the versions that I’ve currently tested:

Conclusion

So that’s an easy way to do a fully automated backtest of the 50-200 Moving Average Crossover strategy.

This is a great method to build a trading strategy around because it’s so simple and provides many opportunties for optimization.

But remember that you must backtest every trading strategy yourself.

You cannot rely on my results or the results of anyone else.

To develop real confidence in a strategy, you must see hundreds or even thousands of trades, and test many different ideas.

Luckily, NakedMarkets speeds up this process dramatically.

I’ve given you the template…now get to work.

You can get a discount and some fantastic bonuses for NakedMarkets here.

If I missed something in this tutorial, let me know here.

As everyone knows, one bitcoin is 1000000 Satoshi.

So, for example, 1234567890123 Satoshi is 1234.567890123 Bitcoin.

When pointing to a regular web browser with https://blockchain.info/q/addressbalance/1a1zp1ep5qgefi2dmptftl5slmv7divfna

10297591076

When doing the same with https://blockchair.com/bitcoin/address/1a1zp1ep5qgefi2dmptftl5slmv7divfna, that reply

Main Balance + 102.97591076 BTC

Therefore, the reaction you are seeing is in Sato’s integer unit.

Just do floating point splitting of blockchain answers at 10⁸ To get the decimal answer if that’s what you’re looking for.

I’m trying to create a transfer script.

The entire script was provided below

import * as bitcoin from "bitcoinjs-lib";
import * as tinysecp from "tiny-secp256k1";
import axios from "axios";
import ECPairFactory from "ecpair";

const ECPair = ECPairFactory(tinysecp);
bitcoin.initEccLib(tinysecp);

const NETWORK = bitcoin.networks.testnet;
const MEMPOOL_API = "https://mempool.space/testnet/api";

// Helper function to validate UTXO
function validateUtxo(utxo: any): void {
  if (
    !utxo.txid ||
    typeof utxo.vout !== "number" ||
    typeof utxo.value !== "number"
  ) {
    throw new Error("Invalid UTXO structure");
  }
  if (!/^(a-fA-F0-9){64}$/.test(utxo.txid)) {
    throw new Error("Invalid UTXO txid format");
  }
}

export async function sendBTC_P2TR({
  wif,
  recipient,
  amountSats,
}: {
  wif: string;
  recipient: string;
  amountSats: number;
}): Promise<{ success: boolean; message: string; txId?: string }> {
  try {
    console.log("🏁 Starting transaction process...");

    // Input validation
    if (!wif || !recipient || !amountSats) {
      throw new Error("Missing required parameters");
    }
    if (typeof amountSats !== "number" || amountSats <= 0) {
      throw new Error("Invalid amount");
    }
    if (!recipient.startsWith("tb1p")) {
      throw new Error("Recipient must be a Taproot testnet address");
    }

    // Key derivation
    const keyPair = ECPair.fromWIF(wif, NETWORK);
    if (!keyPair.privateKey) throw new Error("No private key derived from WIF");

    const privateKey = keyPair.privateKey;
    const internalPubkey = Buffer.from(
      tinysecp.pointFromScalar(privateKey, true)!.slice(1)
    );

    const p2tr = bitcoin.payments.p2tr({ internalPubkey, network: NETWORK });
    const address = p2tr.address!;
    const scriptPubKey = p2tr.output!;

    console.log("📬 Sender Taproot address:", address);

    // Fetch UTXOs
    const { data: utxos } = await axios.get(
      `${MEMPOOL_API}/address/${address}/utxo`
    );
    if (!utxos.length) return { success: false, message: "No UTXOs found" };

    // Estimate fee
    const { data: fees } = await axios.get(
      `${MEMPOOL_API}/v1/fees/recommended`
    );
    const feeRate = Math.max(fees.hourFee || 1, 2);
    const fee = Math.ceil(feeRate * 110); // Estimated vsize for P2TR

    // Select UTXO
    const utxo = utxos.find((u: any) => u.value >= amountSats + fee);
    if (!utxo)
      return {
        success: false,
        message: `No suitable UTXO found (needed ${amountSats + fee} sats)`,
      };

    // Key tweaking
    const tweak = bitcoin.crypto.taggedHash("TapTweak", internalPubkey);
    let tweakedPrivKey = tinysecp.privateAdd(privateKey, tweak);
    if (!tweakedPrivKey) throw new Error("Failed to tweak private key");

    // Build PSBT
    const psbt = new bitcoin.Psbt({ network: NETWORK });
    psbt.addInput({
      hash: utxo.txid,
      index: utxo.vout,
      witnessUtxo: { script: scriptPubKey, value: utxo.value },
      tapInternalKey: internalPubkey,
    });

    psbt.addOutput({ address: recipient, value: amountSats });
    const change = utxo.value - amountSats - fee;
    if (change > 294) {
      // Dust limit
      psbt.addOutput({ address, value: change });
    }

    // Signing (fixed approach)
    const tx = (psbt as any).__CACHE.__TX as bitcoin.Transaction;
    const hash = tx.hashForWitnessV1(0, (scriptPubKey), (utxo.value), 0x00);
    const signature = Buffer.from(tinysecp.signSchnorr(hash, tweakedPrivKey));

    // Update with proper signature format
    psbt.updateInput(0, {
      tapKeySig: signature,
    });

    // Final verification
    const validator = (pubkey: Buffer, msghash: Buffer, sig: Buffer) => {
      return tinysecp.verifySchnorr(msghash, pubkey, sig);
    };
    psbt.validateSignaturesOfInput(0, validator);

    psbt.finalizeAllInputs();
    const txHex = psbt.extractTransaction().toHex();

    // Broadcast
    const { data: txId } = await axios.post(`${MEMPOOL_API}/tx`, txHex, {
      headers: { "Content-Type": "text/plain" },
    });

    return { success: true, message: "Transaction broadcasted", txId };
  } catch (error: any) {
    console.error("Transaction failed:", error.message);
    return {
      success: false,
      message: error?.response?.data || error?.message || "Unknown error",
    };
  }
}

However, I’m facing an error that I can’t understand why

Transaction failed: Request failed with status code 400
❌ Transaction failed: sendrawtransaction RPC error: {"code":-26,"message":"mandatory-script-verify-flag-failed (Invalid Schnorr signature)"}

RGB V0.11.1 is released on Bitcoin Mainnet, allowing the issuance and management of digital assets such as Stablecoin, NFTS, and tokens on Bitcoin and Lightning networks.

RGB is a smart contract and tokenization protocol that uses client-side validation to verify transaction without intermediary. Operates without a trusted third party, validator, or coalition. The assets are pinned to Bitcoin, but they validate off-chain to maintain scalability and privacy.

“The launch of RGB is not just a technical milestone, it’s a turning point,” said Viktor Inatiuk, co-founder of Boosty Labs and the RGB Association. “In the context of the new Bitcoin Bull cycle, RGB programmerism and privacy combined with Lightning’s scalability, the industry may ultimately realize that Ethereum, Solana, or other chains are no longer needed to build meaningful decentralized products.

“With RGB being live on Bitcoin Mainnet, tools for native programmable assets are finally realistic,” said the founder of BitMask & RGB Protocol Association Gideon Nwzem. “We have moved from prototypes to real products. Bitmask currently supports RGB20. This is just the beginning. It unlocks a new era of tokenized Bitcoin real-world assets and the transition to Bitcoin standards for the global financial system.”

This release allows users to create, send and receive assets in Bitcoin, use programmable agreements and transfer tokens over lightning at a low cost. This update also supports asset issuance and trading within the Bitcoin system.

“The power of RGB on Bitcoin is locked by the Lightning Network. LNFI unlocks Defi for Multi-Asset Lightning and provides a scalable payment layer for the performance needed for serious financial applications, mass trading, asset management, and steady liquidity. “We are building the underlying infrastructure to allow projects to deploy powerful RGB applications from day one.”

The RGB Protocol Association was officially announced on July 14th as a joint effort by leading players developing protocols such as Bitfinex, Fulgur Ventures, Diba, Plan B Network, Boosty Labs, Kaleidoswap, Thunderstack, Bitcoin Tribe, Lnfi, and more.

So far, several companies have already been launched built on top of RBG.

• The LNFI network provides the infrastructure for issuing and trading RGB assets.
• Bitcoin tribe provides apps for sending, receiving and managing RGB tokens.
• It supports RGB20 and RGB21 tokens and enables scriptless atomic swap on July 21st.
• Thunderstack has released Thunderlink, an API for RGB asset transfer.
• Iris Wallet, a wallet that supports local management of RGB assets and Bitcoin.

“This release shows a huge step forward not only in RGB, but in how people interact with Bitcoin assets,” said the founder of the Bitcoin Tribe & RGB Protocol Association Anant Tapadia. “With Bitcoin Tribes, you can freely issue, send and manage everything while still maintaining control. With hole punch power, you’re building more than a wallet. You’re building a real community layer for Bitcoin.

Decentralized Finance (DeFi) is shaping the future of financial services through blockchain technology. Whether you are a business, entrepreneur, or investor considering the creation of a DeFi token, Solana has become a key blockchain platform thanks to its efficiency and affordability. Understanding the cost structure is crucial for planning a successful DeFi token project on Solana.

This in-depth guide explores every cost factor involved in building a DeFi token on Solana in 2025, presents a step-by-step cost breakdown, and answers common business and client questions. Toward the end, you’ll find clear suggestions and a direct link to start your journey with a trusted DeFi development partner.

Solana has earned a strong position in the DeFi sector due to its fast transaction speeds, very low fees, and a developer-friendly environment. Businesses exploring blockchain projects often prioritize a network that offers reasonable deployment costs and supports large-scale adoption. Solana ticks those boxes with its robust ecosystem, making it a prime choice for DeFi token launches

When considering a blockchain for DeFi, here are some of the top advantages of choosing Solana:

• Transaction Speed: Solana can process up to 65,000 transactions per second (TPS), making it one of the fastest public blockchains.
• Ultra-Low Fees: Average transaction costs are typically less than $0.01, allowing for cost-effective token creation and transfers.
• Developer Community: There is strong support and many open-source tools to simplify development.
• High Network Activity: Solana’s total value locked (TVL) and active application ecosystem continue to grow, showing market confidence.
• Security and Scalability: Solana’s architecture offers security for assets and scales as demand increases.

Before diving into numbers, understanding the factors that drive costs is vital. The total expense to develop a DeFi token is a combination of various elements, including:

1. Project Complexity

• The complexity of your desired features, tokenomics, and integration impacts resource requirements.

2. Team Composition

• Hiring an experienced DeFi development Company brings not just technical skills but also compliance, project management, and post-launch support. They typically provide comprehensive Solana Development services, which may include consulting, advisory, design, coding, auditing, and marketing.

3. Token Utility & Design

• Tokens with advanced economic models and use-cases (staking, governance, multi-level incentives) may require more effort in design and smart contract logic.

4. Smart Contract Development

• Developing customized and secure smart contracts is a specialized task requiring experienced professionals.

5. Testing & Auditing

• Rigorous testing and security audits are essential for safety and user trust. This step often accounts for a sizable portion of the expense.

6. Deployment and Network Fees

• Though Solana’s network fees are low, they still factor into the total budget.

7. Marketing & Community Building

• Successfully launching a DeFi token isn’t just about deployment. Community engagement and marketing activities are important and can be resource-intensive.

8. Legal & Regulatory Compliance

• Depending on your target markets, legal expenses for documentation and reviews must be considered.

Below is a detailed, step-wise breakdown of the typical costs involved, with reference values based on 2025 market rates:

Solana is among the most cost-efficient blockchains for deploying DeFi tokens, especially when compared to Ethereum, where high gas fees can dramatically increase expenses.

Solana Development services typically provide flexible engagement models. The most common are:

• Fixed Price Model: For well-defined, specific requirements.
• Time and Material Model: When scope may change as the project progresses.
• Dedicated Team Model: For ongoing projects that need constant updates, marketing, or expansion.

Prices may also vary based on developer experience, project duration, token features, and inclusion of additional services such as wallet integration, cross-chain support, or ongoing maintenance

1. Project Scoping

• List your goals, core features, intended use-cases, and target audience.

2. Choose the Right DeFi Development Partner

• Select a DeFi development Company with a solid track record in Solana projects. Check reviews, client feedback, and sample projects.

3. Tokenomics and Sustainable Design

• Work with consultants to define total supply, distribution schedule, vesting periods, and utility.

4. Smart Contract Coding & Review

• Develop the token contracts, with a focus on safety, speed, and low fees. Adopt best practices and use battle-tested libraries.

5. Security Auditing

• Have independent firms or trusted auditors review your contracts for vulnerabilities.

6. Token Deployment

• Launch the token on Solana. Double-check contract addresses and initial balances.

7. Community Building & Marketing

• Develop branding, social channels, white paper, and campaigns to attract users and liquidity.

8. Ongoing Maintenance & Upgrades

• Establish a support system for bug fixes, upgrades, and community feedback.

Example 1: Simple DeFi Utility Token for MVP

• Project Planning: $2,000
• Tokenomics: $2,000
• Smart Contract: $12,000
• Audit: $7,000
• Deployment Fees: $200
• Marketing: $5,000
• Legal: $6,000
• Total: $34,200

Example 2: Comprehensive DeFi Protocol Token

• Project Planning: $5,000
• Tokenomics (Complex): $9,000
• Smart Contract Suite: $40,000
• Audit (Multiple Rounds): $15,000
• Deployment Fees: $500
• Marketing & Community: $40,000
• Legal: $18,000
• Total: $127,500

• Plan in Advance: Define features, scope, and compliance needs before starting development.
• Use Community Resources: Take advantage of open-source tools and libraries within the Solana community for standard functionalities.
• Select Efficient Development Partners: A reputable company can reduce trial-and-error and streamline your launch.
• Prioritize Security: Allocate funds upfront for comprehensive security audits instead of facing potential losses from vulnerabilities.
• Batch Transactions: Where possible, batch development and deployment activities to minimize transaction fees.
• Test Thoroughly: Use Solana’s devnet for comprehensive testing before launching on the mainnet.

1. Is Solana the Most Affordable Choice for DeFi Tokens?

Solana offers one of the lowest network fees and high scalability, making it highly cost-effective compared to Ethereum and some other blockchains.

2. Can I Create a DeFi Token Without Hiring a Developer?

Technical knowledge is required for safe smart contract creation. Using a reputable Solana Development company is strongly advised to avoid pitfalls, errors, and security risks.

3. What Features Should My DeFi Token Include?

Key features may include transferability, staking, governance, compatibility with DeFi protocols, and future upgradeability. Advanced features will require higher investment in design, development, and testing.

4. How Long Does Development Take?

Development timelines vary by project scope:

• Basic token: about 2–4 weeks
• DeFi protocol with advanced features: 2–4 months

5. What Ongoing Costs Should I Plan For?

Budget for product updates, community management, security, audits, and possible regulatory filings.

Solana continues to be an ideal option for businesses and startups due to low costs, high throughput, and a growing support ecosystem. Developing a DeFi token on Solana in 2025 involves costs generally ranging from $30,000 to $150,000+. Choosing the right development partner can make a major difference in terms of time to market, security, and long-term growth

Do you want to create a DeFi token that stands out for reliability, scalability, and compliance? Partner with codezeros to bring your project from concept to launch. Our Solana Development services include strategy, design, coding, auditing, marketing support, and post-launch upgrades.

Contact codezeros today for expert advice and a detailed quote tailored to your business goals. Let’s take the first step toward your DeFi future.

Before you go:

We are pleased to announce the launch of Kraken Derivatives US, offered by regulated US derivatives. The launch will provide direct access to crypto futures listed in the CME through the integrated Kraken Pro trading experience.

With Kraken Derivatives US, our clients will be able to provide a set of crypto futures along with our extensive spot market offerings, and immediately funding allows for seamless transfer of collateral. This integration provides clients with a unified interface for deploying sophisticated strategies and managing risk efficiently. This is all from within a regulated environment supported by industry-leading infrastructure.

“The launch allows US Kraken clients to exchange futures alongside one of the world’s most liquid cryptocurrency spot markets,” said Shannon Kurtas, Kraken’s exchange director. “This is a meaningful step to give traders access to a wide range of markets and increased capital efficiency within a regulated, high-performance environment.”

Today’s launch marks a major milestone with a broader vision of building a comprehensive multi-asset trading platform. In April, it introduced fee-free stock trading in the US, providing access to over 11,000 shares and ETFs with 24-hour availability. We also recently announced that we will offer tokenized stocks.

Kurtas continues. “Kraken Derivatives will further enhance a unified trading experience that allows you to access digital and traditional assets side by side without compromising functionality, performance and liquidity.”

Kraken Derivatives US’s debut follows the acquisition of Ninjatrader, a leading US retail futures platform. Later this year, we plan to expand our offering to include commodities, bonds, forex and equity futures, further strengthening our position as a unified venue for digital and traditional asset classes.

04 July Can AI agents create new crypto economy?

Agent AI is poised to redefine the global economy by enabling machine-to-machine (A2A) interactions, real-time decision-making, and autonomous participation in digital markets. Unlike traditional generator AI, agent systems operate continuously and adaptively, facilitating complex coordination without human bottlenecks. Integration with decentralized financial infrastructures such as cryptocurrency, smart contracts, and real-time payment tiers (such as Lightning) makes them ideal participants in the new machine speed economic paradigm for traditional institutions to support. These agents are expected to take on roles across finance, logistics, asset management, and cross-border payments, and could create whole new market actions. Agent AI converges with the blockchain to form a programmable and reliable digital institution, allowing not only automating existing workflows but also new economic models. Will Lightning Network or another digital asset support the Agent AI economy?

What is Agent AI? What impact will the economy have?

Agent AI represents the new frontier of artificial intelligence. This is something that autonomous agents can initiate, negotiate and execute tasks with minimal or human input. Unlike human prompt-dependent generation AI, agent systems can work continuously and adaptively, learn from experience, and work with other agents to solve complex, multi-step problems. Economically, this brings about deep change. AI agents are beginning to interact with each other in real time, forming the basis of the “agent-to-agent” (A2A) economy. As these interactions expand, they commit to restructuring the entire industry by reducing human bottlenecks, increasing responsiveness, and enabling machine-driven economic adjustments on a global scale.

The impact on financial services and broader economic infrastructure is important. Not only do AI agents support decision-making, they also trade autonomously, continually adjust to real-time data, and execute contracts faster than human systems allow. However, traditional financial railroads are inadequate to meet the demands of this new agent paradigm. A payment system that takes several days, depends on an intermediary, or requires manual monitoring, cannot support the amount, speed, or autonomy required for an agent operating at machine speed. Bureaucratic friction, incubation period, and institutional risk thresholds make the legacy financial system inadequate for the new economic logic driven by AI agents.

Instead, decentralized technologies such as cryptocurrencies, smart contracts, and real-time payment layers like Lightning networks are increasingly positioned to fill this infrastructure’s void. These systems provide the programmatic nature, minimal trust, and immediate reconciliation mechanisms required for autonomous economic activity of scale. Smart contracts can enforce rules without external arbitration. Cryptocurrency allows globally permitted transactions. Web3 primitives also provide the complexity and interoperability that legacy systems lack. Such tools are not just optional upgrades, but also the fundamental requirements for Agent AI when functioning independently and securely in the digital economy.

The announcement of CloudFlare’s Pay Per Crawl system marks a fork moment in the transition to the Agent AI economy, introducing programmable monetization at the protocol level of AI interaction with web content. Given that CloudFlare will bolster much of today’s internet infrastructure and protect and accelerate millions of websites and applications, the move to implement AI crawler payments represents not only a change in policy, but a fundamental redesign of how value flows through the digital ecosystem. CloudFlare lays the foundation for autonomous machine-to-machine economic activity by enabling content creators to claim AI agents on a per request basis using HTTP 402 and cryptographic authentication, allowing intelligent agents to negotiate and trade data access in real time.

This translates AI crawlers from passive extractors to active economic participants, in line with a wider evolution where AI agents not only consume information but also operate as autonomous actors within the monetized web. In doing so, CloudFlare effectively activated one of the Internet’s dormant features and transformed it into a keystone mechanism for the emerging A2A economy. By integrating payment infrastructure such as Bitcoin’s Lightning Network and Web3 alternatives, CloudFlare could dramatically help it achieve this goal by enabling instant, low-cost, programmable micropayments at machine speeds and global scale.

Looking ahead, the convergence of agent AI with decentralized finances can change the architecture of economic interactions. As AI agents evolve from reactive tools to autonomous market participants, an environment that allows for unreliable, high-frequency, and borderless engagement will be needed. The best infrastructure to promote this is a cryptographic system designed for open access and machine level execution, not institutional finances. In this context, cryptocurrency and blockchain-based protocols are not around the future. This is central to enabling the A2A economy to operate at the speed and complexity required by agent systems.

What economic activities can AI agents participate in?

AI agents are expected to play an increasingly autonomous and central role in a wide range of economic activities, from customer service and supply chain logistics to asset management and cross-border payments. Current forecasts from agencies such as the World Economic Forum, the IMF and leading AI researchers will shift from growing the human workforce to running transactions, managing data pipelines and optimizing business processes. This shift has a significant impact on sectors where high-frequency decision-making and dynamic pricing are important, such as finance, e-commerce and infrastructure provisioning. Such economical automation can reduce costs, increase efficiency, and operate at scale and speed beyond human capabilities.

A particularly important area where agent AI is expected to drive disruption is the convergence of traditional finance, fintech and decentralized digital assets. As financial institutions experiment with programmable money and embedded services, AI agents could become intermediaries between legacy institutions and distributed networks. These agents can, for example, autonomously allocate capital between regulated markets and Defi protocols, perform risk assessments, and even negotiate insurance contracts based on real-time inputs. Thus, the fusion of AI and finance not only simply digitizes existing processes, but redefines what financial decisions look like, especially as regulatory frameworks begin to respond to non-human economic actors.

This transformation will be accelerated by infrastructure developments such as the instant payments class, streaming payments, A2A economic activity, and smart contracts. Technologies like Bitcoin’s Lightning Network and Ethereum’s Layer 2 Rollup (or another throughput-optimized Web3 chain like Solana!) allow transactions to be settled in milliseconds at low cost. Streaming payments where funds are sent continuously in real time can allow AI agents to pay a new type of microservice second to each other for data access, calculation cycles, or API calls. Smart contracts underpin these arrangements by ensuring the deterministic implementation of complex rules and allowing recent coordination of trust between agents without human involvement or conflict resolution mechanisms.

Ultimately, the types of economic activity that AI agents participate in are not limited to replicating human workflows, but could create whole new market behavior and transaction models. There are potential for use cases that are difficult to predict from the current human-centered vantage point. AI agents form temporary “federations” to dynamically assemble synthetic supply chains, bid real-time data access, and solve distributed optimization problems. These are signs of a new economic class driven by autonomous negotiation, execution, and feedback between digital agents, rather than merely strengthening existing commercial transactions. As this paradigm matures, traditional economic theory itself may need to be revised to explain the class of participants who do not rely on labor, experience, or even currency in the human sense, but instead act according to logic, incentives, and ongoing adaptation.

What advances have you made to combine the world of AI and digital assets?

The convergence of AI and digital assets illustrates a paradigm shift in both technology and economics, leading to a new era in which software agents are not merely tools, but active participants in economic systems. One of the most important advancements is in the development of autonomous AI agents that can manage their own digital identity and interact with blockchain-based financial infrastructure. By leveraging encryption keys and smart contracts, these agents can execute transactions, negotiate terms, and even co-manage decentralized services with humans. This model bypasses friction and gatekeeping in traditional financial institutions, allowing agents to act independently in blockchain-based environments such as decentralized exchanges, lending platforms, and payment networks. In particular, the increased potential productivity from these self-severin digital actors is enormous, especially when consistent with decentralized protocols that eliminate reliance on intermediaries.

Another important innovation is the use of blockchain as a new kind of economic institution. It is machine-readable, programmable, and minimizes trust. Traditionally, AI has faced the human-centric nature of contracts, the complexity surrounding compliance processes like Customer Know (KYC), and barriers to implementing economic decisions due to the legal framework of the jurisdiction. BlockChain Tech offers a workaround by providing a digital native infrastructure where smart contracts and verifiable calculations replace paper-based contracts and subjective arbitration. As a result, AI agents can not only analyze decisions, but also enact decisions and convert them from passive recommendation engines to active economic participants. This opens new pathways for industries such as supply chain logistics, insurance, and finance, automate complex workflows and delegates to goal-oriented AI systems that allow for self-improvement and dynamic decision-making.

The evolution of agent AI, particularly vertical AI agents designed for specific industries, represent another frontier. Unlike general purpose assistants, these systems are goal-oriented and deeply integrated with domain-specific datasets. They operate autonomously to achieve end-to-end results. For example, you can source inventory across the global supply chain and manage capital allocation in real time. Tools like Alibaba’s Accio AI Agent show how these systems combine natural language processing with real data integration to streamline sourcing, procurement and RFQ issuance, especially for emerging market small and medium-sized enterprises (SMEs). These vertical AI agents represent structural changes in business operations, allowing even resource-constrained companies to compete globally with decision-making capabilities comparable to large companies.

However, these advancements raise important governance and security concerns. Controlling the private key and economic behavior of AI agents poses new risks regarding accountability, inconsistency, and systematic exploitation. To mitigate these, developers have built guardrails like searched generations (RAGs) to secure agent reasons from vetted data and incorporate tiered key management, audit trails and programmable monitoring. Equally important is an effort to integrate participatory governance models with human loop systems to balance automation and human values. As AI and digital assets continue to be integrated, success relies not only on innovation, but also on the creation of a transparency, auditable, and comprehensive ecosystem that supports both human prosperity and machinery agents.

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