Generating My Ideal Portfolio

I am not a financial adviser. This post is for educational and entertainment purposes only and describes my personal journey using AI tools. It does not constitute financial product advice. You should consider seeking independent legal, financial, taxation or other advice to check how this information relates to your unique circumstances. For more information please see the Terms of Service and Privacy Policy.

Step 1: Good Inputs = Good Outputs

First, I considered what makes me, me. This includes my personal values, health, lifestyle, family, occupation/obsolesence, and current finances.¹²

Second, I narrowed what I want from financial advice.³ I want to account for personal dependencies such as my income, expenses, assets, liabilities, and target retirement age.

Third, I wrote a prompt to generate a useful portfolio from AI. I included components from Claude’s “Prompting best practices” to enhance context management, reasoning, and problem solving, and reduce misinterpretation and errors.⁴ For example:

Act as fiduciary financial advisor. Articulate step-by-step instructions to produce a structured **Investment Portfolio and Execution Strategy** documents for amateur investor described by `investor_profile`. MUST satisfy `goals`. MUST comply with `constraints` and `asset_classes`.

Then, execute instructions with:
  jurisdiction: Australia
  investor_profile:
    - autonomous, independent, DIY
    - disciplined, autodidact, "love of learning"
    - age X
    - annual income $X
    - annual expenses $X
    - current assets = $X equities + $X real estate (investment property) + $X cash (held in offset) + $X superannuation
    - current liabilities =  $X mortgage
    - aiming for <X years to retirement
  goals:
    - build long-term wealth
    - "financial independence" as in Financially Independent Retired Early (FIRE)
    - optimise two funds = bridge capital + superannuation capital
  constraints:
    - >50% Australian exposure
    - >50% ethical (ESG) alignment
    - Equities Management Expense Ratio (MER) <0.10%
  asset_classes:
    - Australian Real Estate
    - ASX-listed equities
    - cash

The strategy MUST consider and include:
- evaluation metrics
- thresholds for and actions on success OR failure

Respond with proposed Investment Portfolio, Strategy and Initial Investment Schedule documents.

ALL claims MUST be supported with citations from reputable, current \(2026\), domain-specific sources valid for `jurisdiction`.

Specificity removes ambiguity; it is not enough to ask: “make me rich”.

LLMs work by predicting likely text based on patterns in data. The prompt shapes those probabilities. So, better inputs produce better outputs.⁵

Step 2: Build the Portfolio Blueprint

Asset Allocation

Equities: 65%

Along with risks including variability of returns, low-cost index exchange-traded funds (ETFs) provide diversification, liquidity, and exposure to global growth without active manager risk or high fees.⁶

I want to include ETFs that reflect my values, and have specified that >50% of my total portfolio equities are in ethical (Environmental, Social, and Governance, “ESG”) alignment. This can sometimes mean a higher management fee (to cover research analysis and screening), which for me is less important than the positive impact.

Australian Residential Property: 30%

Property introduces leverage (which amplifies both gains and losses), and combines rental yield with long-term capital growth. It also tends to track inflation via rising construction costs and land values.

Cash: 5%

Not for growth, but for liquidity, stability, and rebalancing. When held in an offset account, cash effectively earns a tax-free return equal to your mortgage rate which can outperform savings accounts.

Overall: 95% growth / 5% defensive

This is aggressive, and I accept that this portfolio will likely capture market volatility with periods of capital loss in return for the opportunity for higher investment performance.⁷ This is currently my preference as I am in the accumulation phase of investing, and plan to dial this back to a more balanced/conservative portfolio over time.

Step 3: Asset Selection

ETFs

The following reflects my personal choices based on the constraints I gave the AI. These are not recommendations for others, but rather a look at how I filtered the ASX universe to meet my specific ESG and cost requirements.

This balances my goals of cost efficiency, ESG exposure, and global diversification.

Property

I am going halves with my partner. Based on our financial situation and goals, we have the following property criteria.

Location criteria:

• Top 25% population growth
• <20km to major employment hub
• Historical growth ~5.5–6.5% p.a. (long-term trend)
• Vacancy rate <2%

Property type:

• Residential, detached house on a decent block of land
• Land >60% of total value
• Rentable on purchase

Financial rules:

• Loan-to-Value Ratio (LVR) <80% (avoid LMI where possible)
• Rental yield >3.5%
• Debt-to-income <6x
• Take out building, contents, and landlord insurance

Strategy:

• Prioritise capital growth over yield
• Minimum 10-year hold

Step 4: Verify

Overall: Simple and diversified portfolio

FIRE investing typically favours equities, specifically low-cost ETFs or index funds, as the primary investment vehicle. Another cornerstone is investment property. Together, these asset classes can provide capital growth and diversification. Ultimately, with good processes, this matches my specification for a fairly easy-to-manage portfolio that is within my risk tolerance.

I also had some constraints that needed to be checked…

Australian exposure (target >50%):

• Property (30%) + ETFs (16%) + cash (5%) = 51% Australian exposure

ESG exposure (target >50%):

• (E200 25% + IWLD 65%) x 65% of total portfolio = 52% ESG exposure
• Note: this can increase to 82% if the property includes energy-efficient features such as solar, insulation, water efficiency

Weighted average MER of ETFs (target <0.10%):

• ETF MER (E200 0.25 x 0.05 + IWLD 0.65 x 0.09 + VEU 0.10 x 0.04) = 0.075% weighted MER

Step 5: Maintenance Protocol

Success involves making a plan, and the effective execution of that plan.

Portfolio Tracking

Rules: Monitor monthly

I use a spreadsheet to:

• Track value ($) of each asset
• Calculate current allocation (%) against target allocation (%)
• Identify drift and target rebalancing

Dollar-Cost Averaging (DCA)

Rules: Invest monthly, minimum $1,000 parcels, maximum 1–2 ETF trades per cycle

I must invest regularly to reduce timing risk while keeping transaction costs low. Trade cost should be <0.5% of trade value. For example, $3 brokerage requires a minimum $600 trade.

Rebalancing

Rules: Target allocations with purchase bias

To rebalance the portfolio, I use new contributions to buy under-weight assets, rather than sell over-weight assets. This avoids unnecessary Capital Gains Tax (CGT).

Cash & Debt Strategy

Rules: Hold 6 months of expenses and property costs in offset account, deploy excess cash via DCA, automatic payments for mortgage and credit card

The cash allocation equates to a minimum of six months of living expenses plus holding costs for the investment property. Holding cash in an offset account reduces the mortgage balance used to calculate interest, effectively delivering a tax-free return equal to the loan rate. Using an interest-free credit card (paid in full monthly) can further maximise time in the offset account.

Maintenance Schedule

Monthly:

• Check cash flow
• Review allocations
• DCA execution

Quarterly:

• Process dividends
• Check property maintenance (1% rule)

Annually:

• Tax optimisation with Chartered Accountant
• Portfolio performance audit
• Property performance audit
• ETF fee/mandate check

Step 6: Verify (Again)

Mistakes compound, just like returns.

AI is a tool, not a fiduciary. Always cross-check assumptions, validate data, and align with your own risk tolerance.

I inputted numerous variations on the above prompt in to multiple AIs. I read output and did my own research and refined with further inputs. I saved markdown files of my frontrunner outputs and had AIs cross analyse and optimise. Then I read that output and did more research.

In the end, my portfolio allocation and execution strategy is less a Frankenstein’s monster of AI outputs and more an AI-assisted education in investment selection.

Design Philosophy

• Simplicity > optimisation
• Low cost > chasing alpha
• Discipline > intelligence
• Systems > emotion
• Leverage: property only

Final Thought

This portfolio is not about wealth at all costs; it is about building a financial system that supports a better life. That means less worry, and more time.

Woof woof.