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Liquidity Pool Mining In Osmosis Zone For Cosmos
February 12, 2023
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(Dinarian Note: I do hope this helps some of you realize the potential that lays within Osmosis Zone.. any questions let me know, I do this regularly to not only make a few 100% APY, but to help support XPRT liquidity..)

 

Getting Started

Before opening the Osmosis AMM App, make sure to install the Keplr Wallet.

Open the App

Go to https://app.osmosis.zone/

 

Connect Wallet

Click Approve. This confirms that you are connecting to the app.osmosis.zone and the chain osmosis-1.

⚠️ Always make sure you are connected "app.osmosis.zone" and network "osmosis-1"

 

Deposit Funds

Click "Assets", Then click on the deposit link next to the asset name. For this example we are            clicking the ATOM deposit link.

Approve connection to cosmoshub-4

Once connected, select how much you would like to deposit, then click the deposit button

 

Approve the transaction

Once the transaction is completed a series if confirmations notifications will be displayed                    including the IBC confirmation.

 

Swapping Tokens

Swapping tokens is as easy as selecting the tokens you wish to swap and selecting the swap button at the bottom of the order window.  Be sure to read the glossary at the bottom of this tutorial to learn about terms such as slippage and impermanent losses.

Adding Liquidity to a Pool

Select a pool from the Pools page. 

Then click Add/Remove Liquidity

 Input a quantity of one of the assets. The quantity of the other asset(s) will auto-complete. (Pools          require assets to be deposited in pre-determined weights.)

⚠️ In order to get your rewards you must bond the liquidity pool tokens.

To remove liquidity, input the percentage amount to withdraw.

Incentivized pools receive OSMO liquidity mining rewards. Rewards are distributed to                    bonded LP tokens in the pools that meet the bonding time requirements. The longer you                provide liquidity to the pool, the more rewards you get.

Bonded Liquidity Pool (LP)Tokens

You can choose to bond your LP tokens after depositing liquidity. LP tokens remain bonded for any amount of time you choose. Remember, bonded LP tokens are eligible for liquidity mining rewards ONLY if they meet the minimum bonding length requirement for that incentive.

Click "Bond Shares" and approve the transaction in your Keplr wallet.

When you want to un-bond an LP token, you need to submit a transaction that begins the                unbonding period. After the end of the pre-determined period (usually 14-21 days), you then will        submit another transaction to withdraw the tokens.

Liquidity Bootstrapping Pools

Osmosis offers a convenient design for Liquidity Bootstrapping Pools (LBPs), a special type of automated market maker designed for token sales. New protocols can use Osmosis’ LBP feature to distribute tokens and achieve initial price discovery.

LBPs differ from other liquidity pools in terms of the ratio of assets within each pool. In LBPs,the ratio changes over time. LBPs involve an initial ratio, a target ratio, and an interval of time over which the ratio adjusts. These weights are customizable before launch. One can create an LBP with an initial ratio of 90-10, with the goal of reaching 50-50 over a month. The ratio continues to gradually adjust until the weights are equal within the pool. Like traditional LPs, the prices of assets within the pool is based on the ratio at the time of trade.

After the LBP period ends or the final ratio is reached, the pool converts into a traditional LP pool.

LBPs facilitate price discovery by demonstrating the acceptable market price of an asset. Ideally, LBPs will have very few buyers at the time of launch. The price slowly declines until traders are willing to step in and buy the asset. Arbitrage maintains this price for the remainder of the LBP. The process is shown by the blue line below

Choosing the correct parameters is very important to price discovery for an LBP. If the initial price is too low, the asset will get bought up as soon as the pool is launched. It is also possible that the targeted final price is too high, creating little demand for the asset. The green line above shows this scenario. 

Osmosis' goal is to provide an easy-to-use LBP design to give protocols the best chances at a  successful pool. The LBP feature facilitates initial price discovery for tokens and allows protocols to fairly distribute token rewards to the pool liquidity providers.

Bonded Liquidity Gauges

Bonded Liquidity Gauges are mechanisms for distributing liquidity incentives to LP token holders that have been bonded for a pre-determined and disclosed amount of time. Close to half of the daily issuance of OSMO gets distributed as liquidity incentives.

For instance, in a Pool 1 LP share, 1-week gauge would distribute rewards to users who have bonded Pool1 LP tokens for one week or longer. The quantity of OSMO that each liquidity provider receives is directly in proportion to the number of their personally bonded tokens.

A single bonded LP position may be eligible for multiple gauges. The only thing that effects the guages is the minimum amount of bonding time required for each gauge.

Tux, the Linux mascot

Another incentive is the fact that, the rewards earned from liquidity mining are not subject to unbonding. Rewards can be transferred immediately to use how you see fit. Only the principal bonded shares are subject to the unbonding period.

Allocation Points

Not all of the liquidity pools have incentivization gauges. Staked OSMO hodlers choose which pools to incentivize via on-chain proposals. To incentivize a pool, governance can assign “allocation points” to specific gauges. At the end of every daily epoch, around half of the newly released OSMO (the tokens meant for liquidity incentives) are distributed proportionally to the points that each gauge has. The percent of the OSMO liquidity rewards that each gauge receives is calculated as its number of points divided by the total number of allocation points.

Take, for example, a scenario in which three gauges are incentivized:

  • Gauge #3 – 10 allocation points
  • Gauge #4 – 5 allocation points
  • Gauge #7 – 5 allocation points

20 total allocation points are assigned in this scenario. At the end of the daily epochs, Gauge #3 will receive 50% (10 out of 20) of the liquidity incentives minted. Gauges #4 and #7 will receive 25% each.

Governance can pass an Update Pool Incentives proposal to edit the existing allocation points of any gauge. By setting a gauge’s allocation to zero, it can remove it from the list of incentivized gauges entirely. Proposals can also set the allocation points of new gauges. When a new gauge is added, the total number of allocation points increases, thus diluting all the existing incentivized gauges. Gauge #0 is a special gauge that sends its incentives directly to the chain community pool. Assigning allocation points to gauge #0 allows governance to save some of the current liquidity mining incentives to be spent at a later time.

At genesis, the only gauge that will be incentivized is Gauge #0, (the community pool gauge). However, a governance proposal can come immediately after launch to choose which gauges/pools to incentivize. Governance voting period at launch is only 3 days at launch, so liquidity incentives may be activated as soon as 3 days after genesis.

External Incentives

Osmosis not only allows the community to add incentives to gauges. Anyone is eligable to deposit tokens into a gauge to be distributed. This feature allows outside parties to augment Osmosis’ own liquidity incentive program.

For example, there may be an ATOM/XPRT pool that has a one-day gauge incentivized by governance OSMO rewards. However, PersistenceOne(XPRT), may also choose to add additional incentives to the one-day gauge or even add incentives to a new gauge (such as one-week gauge).

External incentive providers can also set up long-lasting programs that distribute rewards over an extended time period. For example, PersistenceOne can deposit 30,000 XPRT to be distributed over a one-month liquidity program. The program will automatically distribute 1000 XPRT per day to the gauge.

Fees

Osmosis also provides three sources of revenue: transaction fees, swap fees, and exit fees.

TX Fees

Transaction fees are paid by any user to post a transaction on the chain. The fee amount is determined by the computation and storage costs of the transaction. Minimum gas costs are determined by the proposer of a block in which the transaction is included. This transaction fee is distributed to OSMO stakers on the network. Validators can choose which assets to accept for fees in the blocks that they propose. This optionality is a unique feature of Osmosis.

Swap Fees

Swap fees are fees charged for making a swap in an LP pool. The fee is paid by the trader in the form of the input asset. Pool creators specify the swap fee when establishing the pool. The total fee for a particular trade is calculated as percentage of swap size. Fees are added to the pool, effectively resulting in pro-rata distribution to LPs proportional to their share of the total pool.

Exit Fees

Osmosis liquidity providers pay a small fee when withdrawing from any pool. Similar to swap fees, exit fees per pool are set by the pool creator. Exit fees are paid in LP tokens. Users withdraw their tokens, minus a percent for the exit fee. These LP shares are burned, resulting in pro-rata distribution to remaining LPs.

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🔑 2. Ownership & Security: Wallets and Keys

  • Public Key (Address): An alphanumeric string that acts like your bank account number or email address. It is safe to share publicly so others can send you digital assets.
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"Not your keys, not your coins."

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🙏To support my work, Helping to keep the signal high and the noise low:

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AI Is Coming for Your Job Title

Artificial intelligence may or may not take your job, but it has already broken into the human resources department and vandalized the org chart.

The evidence is all over LinkedIn, where perfectly serviceable occupations now arrive wearing titles such as “forward-deployed and agentic AI architect.” That person may be building sophisticated software. They may also be helping a chatbot remember what happened three prompts ago. Either way, somebody approved the business cards.

The expanding AI lexicon offers a useful counterpoint to the darker debate about technology and employment. Most discussion centers on how many jobs AI will eliminate. Hiring data presents a more complicated picture that includes a weak overall labor market containing a small but rapidly growing neighborhood of AI-related work.

Indeed Hiring Lab found that the number of postings on Indeed mentioning AI surged 134% from its February 2020 level by the end of 2025, even as total postings stood only 6% above that benchmark. AI appeared in a record 4.2% of Indeed postings in December.

AI, in other words, is not merely changing work. It is adding syllables to it.

The Titles Employers Actually Want

The undisputed champion is AI engineer, which ranked No. 1 on LinkedIn’s 2026 Jobs on the Rise list. The ranking, based on growth during the previous three years, also highlighted AI consultants and strategists, AI and machine-learning researchers and data annotators.

The title is popular partly because it is wonderfully accommodating. An AI engineer might build applications around large language models, connect corporate data to an AI system, improve model performance or spend Thursday afternoon persuading a customer service bot not to offer refunds for products the company doesn’t sell.

Indeed’s data showed the terminology spreading beyond Silicon Valley. Nearly 45% of data and analytics postings contained an AI-related term at the end of 2025, along with roughly 15% of marketing postings and 9% of human resources listings. A more recent Indeed analysis reported by Business Insider found that the number of frequently advertised job titles explicitly referencing AI rose from 264 in 2022 to 822 in the first quarter of 2026. Nearly two-thirds were outside traditional technology fields.

That produces titles such as AI marketing manager, AI learning specialist, responsible AI counsel and AI transformation lead. These are not always new occupations. Frequently, they are familiar jobs that have discovered a highly effective résumé keyword.

LinkedIn data cited by the World Economic Forum estimated that AI investment has supported 1.3 million positions, including AI engineers, data annotators and forward-deployed engineers, plus more than 600,000 AI-enabled data center jobs. The server racks, unlike the chatbots, still need electricians.

The Jobs With the Science-Fiction Salaries

At the upper end, AI has created a compensation market that resembles professional sports, except the competitors wear hoodies and discuss inference latency.

Syracuse University review put chief AI officer compensation between $200,000 and more than $500,000, while specialized roles can exceed $400,000 after bonuses and equity. Frontier research engineers, AI infrastructure specialists and engineers who can train or deploy advanced models command some of the largest packages.

Then there is the forward-deployed engineer, an old Palantir title that the AI boom has placed on a rocket sled. These engineers embed with customers, translating an executive’s desire to “do something with AI” into software that works. The Next Web reported that Indeed postings for the role were about 19 times higher in January than a year earlier.

CTO guide from the blog Signal Through the Noise placed forward-deployed engineer compensation between $238,000 and $700,000, research-engineering packages as high as $1.4 million and chief AI officer compensation above $1 million in some cases. It also made a less flattering observation: Many lavishly differentiated titles describe the same three basic functions. People build AI products, train models or keep the infrastructure from catching fire.

The Department of Unnecessary Titles

AI has created some genuinely new work. Evals engineers design tests to determine whether models perform reliably. AI red teamers try to make systems fail before customers do. Model behavior engineers study why an AI system responds as it does. AI governance leaders manage risks involving data, bias, security and regulation.

Other titles seem to have escaped from a brainstorming retreat.

There is the Claude Evangelist, whose mission apparently combines product education with the traditional duties of an apostle. There are vibe coders, who build software by describing what they want and accepting AI-generated code with varying degrees of supervision. “Vibe engineer” is the more respectable version, roughly equivalent to putting on a blazer before asking the machine to fix the login page.

“Context engineer” is a real discipline involving the data, instructions, memory and tools supplied to AI models. “Prompt engineer,” once advertised as a possible six-figure profession for gifted chatbot whisperers, is increasingly treated as one skill inside a broader AI role.

The CTO guide also identified “builder,” “AI-native developer,” “RAG engineer,” “agentic AI engineer” and “principal agentic GenAI forward-deployed context architect,” the last of which appears to require both technical proficiency and exceptional lung capacity.

Has AI created entirely new jobs? Absolutely. Some occupations, including AI safety, evaluation and model governance, exist because modern generative systems introduced new technical and business problems. However, many job titles are old jobs with fresh vocabulary, higher salary bands and a sudden aversion to the words “software developer.”

That may be the safest prediction about AI and employment. The machines will automate some tasks, generate others and force companies to rethink the division of labor. Before any of that is settled, however, corporate America will form a steering committee, appoint a chief agentic transformation evangelist and schedule a meeting to determine what that person does.

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🤖 Decentralized Intelligence by Design: Unpacking the Bittensor Flywheel

In the legacy tech world, artificial intelligence is governed by corporate monopolies. Companies like OpenAI and Google scale by capturing massive capital, locking talent behind non-disclosure agreements, and building closed-source infrastructure. 🛑

Bittensor flips this paradigm completely on its head. By combining a Bitcoin-inspired tokenomic model with a permissionless, competitive architecture, Bittensor doesn't just fund AI development—it orchestrates an unstoppable digital commodity flywheel. 🌪️

Here is an analysis of how the Bittensor ($TAO$) Flywheel Effect operates, and why its economic design is quietly building the foundation for generalized, open-source intelligence.

1. ⚙️ The Core Engine: The TAO Emission Mechanism

Unlike traditional crypto projects driven by private sales or VC allocations, Bittensor enforces a strict meritocracy. There are exactly 21 million TAO tokens that will ever exist, mimicking Bitcoin’s scarcity framework. 🪙

The network’s core engine releases 7,200 TAO daily across the ecosystem. This issuance isn't handed out randomly; it is dynamically distributed to specialized mini-marketplaces known as Subnets via a game-theoretic protocol called Yuma Consensus.

2. 🔄 The Three Stages of the Flywheel

The Bittensor flywheel works because it directly aligns the local self-interest of developers, miners, validators, and capital providers with the global health of the network. 🎯

🛡️ Phase 1: High-Barrier Subnet Competition

To build on Bittensor, an entrepreneur or developer group must purchase and "burn" or lock up a significant amount of TAO to secure a Subnet slot.

  • The Filter: This entry barrier filters out noise.

  • The Result: It ensures that only teams with mature concepts and solid execution capabilities (like decentralized storage, protein folding, or LLM inference) enter the arena.

💎 Phase 2: Alpha Token Emissions & Talent Attraction

Once a subnet is live, it competes aggressively against other subnets for a slice of the daily 7,200 TAO pool. Under the Dynamic TAO framework, each subnet utilizes its own localized native token (Alpha tokens). 🧪

  • Reward: The subnets that produce the highest utility or most innovative AI products receive a larger allocation of global TAO emissions.

  • Incentive: These emissions fund the subnet's local Alpha pool, offering massive financial rewards to the best Miners (who provide the actual compute/AI models) and Validators (who verify the accuracy and value of the work).

🔒 Phase 3: The Liquidity Loop and Token Scarcity

Because Alpha tokens are inherently priced relative to TAO, external investors or users who want to stake on or utilize a specific high-performing subnet must first acquire TAO. 📈

  • As a subnet's product quality improves, demand for its Alpha token surges.

  • To buy Alpha, participants must buy and lock up TAO in decentralized liquidity pools.

  • This removes circulating TAO from the open market, reducing effective float and driving up the value of TAO.

3. 🚀 Why the Flywheel is Unstoppable

The beauty of this cycle is that it feeds itself:

Higher TAO Price ➡️ More Valuable Subnet Emissions ➡️ Attraction of Higher-Tier Talent/Compute ➡️ Superior AI Products ➡️ Increased Network Demand ➡️ Higher TAO Price📈

Traditional startups spend millions on recruitment and marketing. Bittensor bypasses this entirely: its emission schedule acts as a global bat-signal for talent. 🌍

If a miner in Eastern Europe or a data scientist in Tokyo can optimize an open-source model to solve a specific subnet's prompt better than anyone else, the network automatically and frictionlessly rewards them.

💡 The Takeaway

Bittensor is more than a blockchain; it is an economic computer designed to run incentive structures in massive parallelism. By treating machine intelligence as a digital commodity and wrapping it in a circular value flow, the Bittensor flywheel transforms raw computational energy into an emergent, open-source super-intelligence. 🧠⚡

As subnets mature from raw infrastructure into client-facing enterprise APIs, the velocity of this flywheel is poised to redefine the economics of AI forever.

I hope this was helpful ~Dinarian888♾

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