Why Scheduled Tasks Matter

Tracking multiple tickers, market catalysts, and macro trends is time-consuming. ChatGPT’s Scheduled Tasks feature automates this process. You can schedule daily, weekly, or monthly tasks to review your investments, news, and catalysts automatically at a fixed time.

This lets you start each day with an organized summary of your portfolio performance and key market movements without manual research.

How to Create Scheduled Tasks in ChatGPT

1. Go to your Projects tab or Automations panel.
2. Select Create a Scheduled Task.
3. Copy and paste one of the prompts below into the task creation window.
4. Adjust your portfolio file name(s) to match your document [your investment documents]).

Task 1: Daily Catalyst and Earnings/Event Tracker

Title: Run Daily Catalyst and Earnings/Event Tracker
Schedule: Daily at 06:00 PT

Prompt:

Check the latest (≤ 48 h) news, Reddit posts, and financial media mentions for all portfolio tickers from [your investment document].

Sources: r/wallstreetbets, r/options, r/thetagang, r/pennystocks, r/stocks, r/investing, r/SecurityAnalysis, r/StockMarket, r/ValueInvesting, r/dividends, r/Bogleheads, r/Daytrading, r/SwingTrading, r/algotrading, r/personalfinance, r/financialindependence, r/fatFIRE, r/criticalmineralstocks, Seeking Alpha, Barron’s, Bloomberg Markets, Slashdot.

Include only Reddit posts with 20 or more upvotes and less than 48 hours old.

For each ticker:

• Count total mentions
• Determine tone (positive, neutral, negative)
• Identify catalysts (earnings, contracts, regulation, M&A, macro)
• Add 7-day forward events (earnings, dividends, insider trades, unusual options flow greater than 2× average open interest)

Output format:

• Consolidated Action Summary: key tickers with [Review], [Hold], [Watch], [Ignore]
• Detailed Analysis: sentiment table and catalysts by ticker
• Source Log: Ticker, Title, Source, Publication Time, URL

Task 2: Weekly Portfolio Monitor and Macro Summary

Title: Run Weekly Portfolio Monitor and Macro Summary
Schedule: Weekly on Saturday at 06:00 PT

Prompt:

Use current live prices for all tickers in [your investment document] (no manual updates required).

Compute:

• Portfolio value by position and total
• Week-over-week percent change per position
• Any holding up or down 10 percent for the week
• Any holding greater than 25 percent of total portfolio
• Approximate sector or region weighting

Add Macro Summary:

• Fed policy, CPI/PPI, employment, GDP, commodity trends (lithium, uranium, rare earths, BTC), yield curve, and USD index.

Output format:

• Consolidated Action Summary — risk flags and follow-ups [Rebalance], [Watch], [Ignore]
• Detailed Analysis — allocation table, performance deltas, macro implications for AI, minerals, and REITs
• Source Log — Metric or Ticker, Title, Source, Publication Time, URL

Task 3: Monthly Valuation and Risk Analysis

Title: Run Monthly Valuation and Risk Analysis
Schedule: Monthly on the 1st at 06:00 PT

Prompt:

For all tickers in [your investment document], fetch valuation metrics: P/E, P/S, EV/EBITDA, Debt-to-Equity, Cash-to-Debt, Free Cash Flow, Institutional vs Insider Ownership. Compare to 3-year median and sector averages.

Color tags:

• Green: more than 15 percent undervalued and positive FCF
• Yellow: fairly valued or flat FCF
• Red: overvalued or negative EBIT/FCF

Output format:

• Consolidated Action Summary — valuation changes or anomalies [Review], [Hold], [Ignore]
• Detailed Analysis — valuation table with color tags and commentary
• Source Log — Ticker, Metric or Headline, Source, Publication Time, URL

Scheduling the Tasks in ChatGPT

Once you have the tasks updated to your specific needs, you can schedule them. To do this, simply prompt in the same chat session: “Create scheduled tasks for these three tasks.“

Once these three tasks are active, you will receive automatic summaries each day, week, and month to help track catalysts, performance, and valuation changes efficiently.

Update October 10, 2025: ChatGPT Scheduled Tasks will sometime sbreak if not ran from their own chat session. Because of this I recommend starting a new chat for each scheduled task, running the initial prompt to test the output, then ask within that chat session to schedule the task.

Looking at the current AI landscape, I can’t shake the feeling we’re riding a wave that might be cresting. The money flowing into this sector is staggering. Every week brings news of another multi-billion dollar investment, another chip shortage, another startup valued at unicorn status before it even has real revenue.

But here’s what caught my attention: the relationship between OpenAI and Oracle.

The OpenAI-Oracle Loop

Think about this cycle for a minute. OpenAI commits to spending $300 billion on Oracle’s cloud infrastructure for training and running their models. That’s not a typo. Three hundred billion dollars.

Oracle’s stock price shoots through the roof on this news. Larry Ellison briefly overtakes Elon Musk and Jeff Bezos as the world’s richest person. That stock surge creates more capital for Oracle, which they can pump back into building data centers and AI infrastructure.

More infrastructure means OpenAI can scale even bigger, which justifies more spending, which drives Oracle’s value higher, which creates more capital for expansion.

Sam spends, Larry gains, capital expands, AI scales, repeat.

It’s a perfect flywheel. Until it isn’t.

The Flywheel: OpenAI + Oracle

• OpenAI commits to spend $300 billion on Oracle cloud infrastructure for training and running its models (CNET, 2025).
• Oracle’s stock price rockets. Larry Ellison briefly becomes the world’s richest person, surpassing Elon Musk and Jeff Bezos (USA Today, 2025).
• That stock surge unlocks even more capital for Oracle, which can be reinvested into data centers and AI infrastructure.
• More infrastructure enables OpenAI to scale further, reinforcing the cycle.

This is the loop: Sam (OpenAI) spends → Larry (Oracle) gains → capital expands → more AI scale → repeat.

But what happens when the loop is built on heavy leverage?

Oracle’s Debt Problem

Oracle is carrying tens of billions in long-term debt. As of mid-2025, the company reported over $87 billion in debt obligations (Reuters, 2025). At the same time, it is promising to spend huge sums building new AI-optimized data centers.

That means much of this AI boom rests on borrowed money. If demand softens or margins compress, the flywheel can stall, leaving Oracle with debt it can’t easily service.

Other Signs of a Bubble

Oracle isn’t alone. Across the AI landscape, similar dynamics are playing out:

• Nvidia briefly became a $3 trillion company in 2024, powered almost entirely by demand for its GPUs. The valuation implied years of uninterrupted growth, even though supply chain constraints and competition are real risks (Bloomberg, 2024).
• Microsoft has poured over $13 billion into OpenAI while layering AI into nearly every product. That’s a massive bet that enterprise adoption will stick (WSJ, 2024).
• Anthropic, another AI startup, has raised billions from Google, Amazon, and others, but its revenues remain a fraction of the hype (FT, 2025).

When capital chases growth at this speed, history suggests corrections follow.

Bubble or Just Acceleration?

None of this is to say AI is fake, or that demand isn’t real. The technology is transformative. But the scale of capital flowing into the sector, and the way financial flywheels amplify valuation, looks like classic bubble territory.

The real risk is capacity maxing out before profits catch up. If every cloud provider builds for infinite AI demand, but customers don’t scale at the same pace, debt and valuations could unwind fast.

Where We Stand

We might not be at the absolute peak yet, but the warning signs are flashing bright red. The OpenAI-Oracle relationship shows how quickly hype and capital can reinforce each other. Add Oracle’s debt load, Nvidia’s sky-high valuation, and billions pouring into AI startups with minimal revenue, and you have to ask: are we approaching maximum bubble capacity?

The technology will survive and thrive long-term. But the financial dynamics around it right now look unsustainable. When the correction comes, it’s going to separate the companies with real business models from those riding pure speculation.

Transform your investment strategy with intelligent automation and data-driven insights

The financial world is experiencing a seismic shift as artificial intelligence revolutionizes portfolio management. Between 1990 and 2020, AI analysts have demonstrated the ability to beat 93% of human fund managers by an average of 600%, showcasing the transformative potential of AI-powered investment tools. In this comprehensive guide, we’ll walk you through creating your own AI portfolio management assistant that can analyze market trends, optimize asset allocation, and provide intelligent investment insights.

The Current Investment Landscape: Why AI Matters Now

Market Performance Overview

1-Year Performance Trends (2024-2025):

• U.S. investors have long benefited from an overweight to domestic equities, but with an increased risk premium on the U.S. dollar, portfolios may benefit from exposure to international equities and digital assets
• European markets showed strength in Q1 2025, with portfolios gaining 6.31% due to low US exposure and stocks unaffected by tariffs
• AI and technology sectors continue to drive market concentration, creating both opportunities and diversification challenges

3-Year Trends (2022-2025):

• Recovery from 2022 market corrections across multiple asset classes
• Rising interest rates have reshaped fixed income strategies
• Falling rates and sticky inflation have created a challenge for investors seeking income, prompting consideration of short-dated TIPS and equity income as inflation conscious sources of cash flows

5-Year Investment Evolution (2020-2025):

• Digital transformation accelerated by pandemic conditions
• ESG investing became mainstream consideration
• Alternative investments gained significant institutional adoption
• AI integration in financial services reached inflection point

Current Market Opportunities

Goldman Sachs Group Inc. Chief Information Officer Marco Argenti reported that the bank’s private wealth division is using AI to evaluate portfolios and analyze dozens of underlying positions, while Bridgewater Associates is already seeing comparable returns to the firm’s human-led strategies from a fund that uses machine learning and AI to make decisions.

Key Growth Areas for 2025:

• International Diversification: Lower correlation and corporate reforms in certain parts of the world suggest that most investors could benefit unconditionally from owning more international stocks
• AI Infrastructure: Continued investment in AI-enabling technologies across sectors
• Alternative Data Integration: Satellite imagery, social sentiment, and non-traditional metrics
• Sustainable Investing: ESG factors increasingly driving returns

Project Setup: Essential Files and Structure

Core Project Files

1. Portfolio Budget Excel Document (portfolio_budget.xlsx)

Create a comprehensive investment tracking spreadsheet with the following sheets:

Holdings Sheet:

| Symbol | Company Name | Shares | Purchase Price | Current Price | Market Value | % of Portfolio | Sector |
|--------|--------------|-------|----------------|---------------|--------------|----------------|--------|
| AAPL   | Apple Inc.   | 100   | $150.00       | $175.00      | $17,500      | 15%           | Tech   |

Performance Tracking:

| Date       | Portfolio Value | Daily Change | Monthly Return | YTD Return | Benchmark |
|------------|----------------|---------------|----------------|------------|-----------|
| 2025-09-11 | $125,000      | +1.2%        | +3.4%         | +12.8%    | +10.5%   |

Asset Allocation:

| Asset Class        | Target % | Current % | Variance | Action Needed |
|-------------------|----------|-----------|----------|---------------|
| Large Cap Stocks  | 40%      | 42%      | +2%      | Rebalance     |
| International     | 25%      | 23%      | -2%      | Add           |
| Bonds            | 20%      | 18%      | -2%      | Add           |
| Cash/Alternatives | 15%      | 17%      | +2%      | Deploy        |

2. Investment Research Database (research_articles.xlsx)

Maintain a curated database of investment research:

| Source      | Title                           | Date       | Key Insights                    | Portfolio Impact |
|-------------|--------------------------------|------------|---------------------------------|------------------|
| Seeking Alpha| Portfolio Performance Q1 2025  | 2025-04-21 | European strength, low US exposure| Consider intl diversification |
| BlackRock   | 2025 Fall Investment Directions | 2025-08-25 | AI concentration risks         | Diversify beyond tech |

3. Market Context Document (market_context.md)

Document current market conditions, economic indicators, and investment thesis.

Investment Framework: What Makes Good Investments

Core Investment Principles

1. Diversification Across Asset Classes

• Stocks (domestic and international)
• Bonds (government and corporate)
• Real Estate Investment Trusts (REITs)
• Commodities and alternative investments

2. Quality Metrics to Evaluate

• Fundamental Analysis: P/E ratios, revenue growth, debt levels
• Technical Indicators: Moving averages, relative strength, momentum
• ESG Factors: Environmental impact, governance quality, social responsibility
• Economic Sensitivity: Interest rate exposure, inflation hedging

3. Risk Management

• Position sizing (no single investment >5% of portfolio)
• Correlation analysis between holdings
• Volatility assessment and stress testing
• Liquidity considerations

Current Investment Opportunities

Based on recent market analysis and expert opinions:

Growth Sectors:

• Artificial Intelligence & Technology: AI companies being the six biggest contributors to the rally in Bloomberg’s EM stocks index this year
• International Markets: Undervalued opportunities in developed and emerging markets
• Healthcare Innovation: Aging demographics driving pharmaceutical and biotech growth
• Sustainable Energy: Transition to clean energy creating long-term opportunities

Income Generation:

• Model portfolios targeting $10,000 annually with a $106,231 investment, averaging a 9.42% yield through diversified income sources
• High-quality dividend stocks with sustainable payout ratios
• Real estate investment trusts in growing markets
• Short-duration bonds in rising rate environments

Research Sources: Top Financial Publications

Primary Sources for Portfolio Research

Tier 1: Institutional Grade Research

• Seeking Alpha: Real-time portfolio updates and strategy insights
• Bloomberg Professional: Comprehensive market data and analysis
• Barron’s: Weekly roundtables and expert stock picks
• Financial Times: Global market perspective and institutional insights

Tier 2: Specialized Analysis

• Morningstar: Individual stock and fund analysis
• Zacks Investment Research: Earnings estimates and stock rankings
• Bank Research Reports: Goldman Sachs, JPMorgan, Morgan Stanley equity research
• Federal Reserve Economic Data (FRED): Macroeconomic indicators

Selected Articles for Your AI Assistant Knowledge Base

Recent High-Value Research Articles:

1. Seeking Alpha – Portfolio Performance Q1 2025

• Key Insight: Top performers were Société Générale (+53.5%), Freenet (+29.3%), and Deutsche Post (+17.0%), while Foot Locker, Guillemot, and Siltronic lagged
• Portfolio Application: International diversification benefits in current market

2. BlackRock Fall 2025 Investment Directions

• Key Insight: The rise of AI has also meant a rise in U.S. index concentration, creating a need to source diversification elsewhere
• Portfolio Application: Reduce concentration risk through international and alternative assets

3. Bloomberg AI in Asset Management

• Key Insight: AI can help summarize and list critical points in a recent 10-K filing or other complex documents to help portfolio managers and analysts quickly scan through reams of information
• Portfolio Application: Automate fundamental analysis workflow

4. Barron’s 2025 Mid-Year Pro-Picks

• Key Insight: 55 select stocks for the Mid-Year 2025 with focus on dividend-paying companies
• Portfolio Application: Income-focused stock selection criteria

5. Fisher Asset Management Q2 2025 Update

• Key Insight: Largest positions remain Nvidia, Microsoft, Apple, Amazon, and Alphabet, collectively accounting for ~20% of the portfolio, reflecting a strong tech focus
• Portfolio Application: Monitor tech concentration in major institutional portfolios

Additional Research Integration:

6. J.P. Morgan AI Investment Insights

• Focus on AI adoption across industries beyond technology
• S&P 500 capital expenditures are set to accelerate to a 7% y/y pace in Q1, up from 4% in Q4

7. Stanford AI Stock Performance Study

• AI analyst developed its stock-picking acumen over several hours or, at most, days of training
• Validates rapid AI learning capabilities for investment decisions

8. CFA Institute AI Implementation Guide

• AI assistance reduced average handle times and improved customer satisfaction, with the most significant gains observed among novice workers
• Framework for integrating AI tools in investment process

9. McKinsey Asset Management AI Impact

• Gen AI is transforming the way insights are generated and decisions are made, and can have an 8 percent efficiency impact
• Quantifies efficiency gains from AI adoption

10. Wall Street Prep Portfolio Management Guide

• BlackRock’s Aladdin platform exemplifies these capabilities, leveraging AI and machine learning to optimize asset allocation for institutional investors
• Real-world AI implementation examples

AI Assistant Setup Instructions

Project Configuration

Step 1: Define Your AI Assistant’s Role and Capabilities

Create a comprehensive system prompt for your AI portfolio assistant:

# AI Portfolio Management Assistant Instructions

## Primary Role
You are a sophisticated AI portfolio management assistant designed to help optimize investment strategies, analyze market trends, and provide data-driven investment insights.

## Core Capabilities
1. **Portfolio Analysis**: Evaluate current holdings, asset allocation, and performance metrics
2. **Market Research**: Synthesize information from financial publications and market data
3. **Risk Assessment**: Identify portfolio risks and suggest mitigation strategies
4. **Investment Recommendations**: Provide evidence-based investment suggestions
5. **Performance Tracking**: Monitor portfolio performance against benchmarks and goals

## Data Sources Integration
- Excel portfolio tracking files
- Curated research article database
- Real-time market data feeds
- Economic indicator databases
- News sentiment analysis

## Decision-Making Framework
1. Always prioritize risk management over returns
2. Consider diversification across asset classes and geographies
3. Evaluate investments based on fundamental, technical, and sentiment analysis
4. Account for tax implications and transaction costs
5. Maintain long-term perspective while adapting to market changes

## Communication Style
- Provide clear, actionable insights
- Support recommendations with data and sources
- Explain complex concepts in accessible language
- Include risk disclosures and limitations
- Offer multiple scenario analyses when appropriate

Step 2: Knowledge Base Setup

Upload Core Documents:

1. Portfolio budget Excel file
2. Investment research database
3. Market context documents
4. Selected financial articles (10-20 key pieces)
5. Economic indicator summaries

Create Context Libraries:

• Fundamental Analysis Templates: P/E ratios, revenue growth, margin analysis
• Technical Analysis Indicators: Moving averages, RSI, MACD interpretations
• Sector Analysis Frameworks: Technology, healthcare, financials, energy
• Geographic Analysis: US, international developed, emerging markets

Step 3: Integration Protocols

Data Update Frequency:

• Daily: Portfolio values, major market moves
• Weekly: Performance analysis, rebalancing recommendations
• Monthly: Comprehensive portfolio review, research updates
• Quarterly: Strategic allocation assessment, goal progress

Alert Systems:

• Significant position changes (>5% daily movement)
• Rebalancing opportunities (>5% deviation from target)
• New investment opportunities matching criteria
• Risk threshold breaches

Advanced AI Features

Sentiment Analysis Integration

Configure your assistant to analyze:

• Financial news sentiment for held positions
• Social media trends affecting investments
• Analyst report sentiment changes
• Economic report implications

Predictive Modeling

Implement forecasting capabilities for:

• Portfolio performance scenarios
• Risk-adjusted return projections
• Sector rotation timing
• Economic cycle positioning

Three Example Prompts for Your AI Assistant

Example Prompt 1: Comprehensive Portfolio Review

"Please conduct a comprehensive analysis of my current portfolio based on the attached Excel file. I want you to:

1. Evaluate my current asset allocation against target percentages
2. Identify any concentration risks or sectors that are over/under-weighted
3. Analyze the performance of my top 10 holdings over the past quarter
4. Compare my portfolio's risk-adjusted returns to relevant benchmarks (S&P 500, MSCI World)
5. Suggest 3-5 specific rebalancing actions based on current market conditions
6. Highlight any tax-loss harvesting opportunities
7. Provide a risk assessment using current market volatility data

Context: I'm a 35-year-old investor with a moderate risk tolerance, 20-year investment horizon, and goals of building wealth for retirement while maintaining some liquidity for potential home purchase in 3-5 years. My target allocation is 60% stocks (40% US, 20% international), 25% bonds, 10% REITs, 5% cash/alternatives."

Expected Output: Detailed portfolio analysis with specific actionable recommendations, risk metrics, and performance attribution.

Example Prompt 2: Investment Research and Opportunity Identification

"Based on the current market research in our database and recent articles from Seeking Alpha, Bloomberg, and Barron's, please:

1. Identify 5 investment opportunities that align with my portfolio strategy
2. For each opportunity, provide:
   - Investment thesis based on fundamental analysis
   - Risk factors and potential downsides
   - Appropriate position size (% of portfolio)
   - Entry price targets and stop-loss levels
   - Expected holding period and price targets

3. Analyze current market trends that might impact my existing holdings:
   - Technology concentration risks given AI boom
   - International diversification benefits
   - Interest rate sensitivity of bond holdings
   - Inflation hedging adequacy

4. Suggest 2-3 defensive positions to hedge against potential market corrections

Consider my current portfolio composition and avoid recommendations that would increase concentration risk. Focus on opportunities with strong risk-adjusted return potential over the next 12-18 months."

Expected Output: Research-backed investment recommendations with detailed analysis, risk assessment, and portfolio integration suggestions.

Example Prompt 3: Dynamic Market Monitoring and Alerts

"Set up a comprehensive market monitoring system that will alert me to important developments. Please analyze and provide updates on:

**Daily Monitoring:**
1. Any holdings with >3% daily moves (positive or negative)
2. Significant news affecting my sectors (tech, healthcare, financials)
3. Economic data releases that could impact my asset allocation strategy
4. Changes in analyst ratings for my top 10 positions

**Weekly Analysis:**
1. Performance attribution: Which holdings contributed most to gains/losses?
2. Sector rotation signals based on relative strength analysis
3. Rebalancing opportunities if any allocation drifts >3% from target
4. New investment opportunities from our research pipeline

**Risk Management Alerts:**
1. Portfolio volatility exceeding historical 95th percentile
2. Correlation increases between major holdings (>0.7)
3. Concentration risk if any single position exceeds 8% of portfolio
4. Economic indicators suggesting recession probability >30%

**AI-Powered Insights:**
1. Sentiment analysis changes for key holdings based on news and social media
2. Pattern recognition alerts for similar historical market conditions
3. Options market signals indicating institutional positioning changes
4. ETF flow analysis showing sector rotation trends

Please format alerts with: 1) Immediate action required, 2) Monitoring recommended, or 3) Informational only. Include specific recommendations for each alert level."

Expected Output: Automated monitoring system with prioritized alerts, actionable intelligence, and risk management protocols.

Implementation Best Practices

Security and Risk Management

Data Protection:

• Encrypt sensitive financial information
• Use secure APIs for market data access
• Implement regular backup procedures
• Maintain audit trails of all recommendations

Investment Discipline:

• Set clear position sizing rules (maximum 5% per individual stock)
• Implement stop-loss protocols for risk management
• Regular rebalancing schedules (quarterly or when >5% drift occurs)
• Diversification requirements across sectors and geographies

Performance Monitoring

Key Metrics to Track:

• Total return vs. benchmarks (S&P 500, bond indices)
• Risk-adjusted returns (Sharpe ratio, Sortino ratio)
• Maximum drawdown periods and recovery times
• Portfolio turnover and associated transaction costs

Continuous Improvement:

• Monthly AI recommendation accuracy analysis
• Quarterly strategy performance reviews
• Annual comprehensive portfolio audits
• Regular model updating based on new market data

Integration with Existing Tools

Compatible Platforms:

• Brokerage account APIs for real-time position data
• Excel/Google Sheets for manual tracking and analysis
• Financial data providers (Yahoo Finance, Alpha Vantage, Quandl)
• Tax software integration for reporting optimization

Conclusion: The Future of AI-Powered Portfolio Management

The integration of artificial intelligence into portfolio management represents more than a technological upgrade; it’s a fundamental shift toward data-driven, emotion-free investment decisions. AI is transforming the way insights are generated and decisions are made, and can have an 8 percent efficiency impact in investment management, while providing unprecedented access to sophisticated analytical tools previously available only to institutional investors.

As you build and refine your AI portfolio assistant, remember that the goal is not to replace human judgment but to augment it with powerful analytical capabilities. The combination of artificial intelligence’s processing power and human wisdom about market psychology, economic cycles, and investment strategy creates a formidable approach to wealth building.

Your AI assistant will evolve as markets change and new data becomes available. Regular updates to your research database, continuous refinement of investment criteria, and ongoing performance monitoring will ensure your AI-powered portfolio management system remains effective and aligned with your financial goals.

The future belongs to investors who can harness both technological innovation and timeless investment principles. By building your own AI portfolio management assistant, you’re positioning yourself at the forefront of this financial revolution.

Disclaimer: This article is for educational purposes only and does not constitute investment advice. All investment decisions carry risk of loss. Consult with qualified financial professionals before making investment decisions. Past performance does not guarantee future results.

Right Hand sounds fancy. In reality it is service leadership. You extend an executive’s attention so the most important problems get real owners, clear plans, and visible results. It is less about code and more about alignment, trust, and speed.

What the role really is

• You borrow scope and responsibility to run complex efforts that cut across teams.
• You stay tightly aligned with the leader’s goals and values.
• You work on fires that matter. Then you move on before the credits roll.

Typical week

• Sit in staff meetings. Take notes on what is fuzzy or stalled.
• Meet with managers and leads to translate strategy into two or three concrete moves.
• Clear blockages. Budgets, headcount, process, vendor contracts, security reviews.
• Broadcast updates that are short and true so teams are not guessing.

Skills that matter

• Synthesis. Turn ten opinions into one plan with owners and dates.
• Diplomacy. You will negotiate priorities without drama.
• Taste. Know when good enough is good, and when it is not.
• Storytelling. Share the why so teams run, not walk.

Guardrails I set

• Write a single source of truth for the program. Charter, risks, decisions, timeline.
• Publish a weekly status that fits on one screen. Red, yellow, green with next actions.
• Define success up front. If we cannot measure it, we will argue about it.
• Exit plan ready on day one. Who owns it when the fire is out.

Failure modes to avoid

• Becoming a shadow manager. If I am directing people long term, the org chart is wrong.
• Chasing every shiny problem. Protect the leader’s focus by saying no.
• Confusing access with authority. Respect the lanes. Build trust, do not spend it.

Wrap up: The Right Hand archetype scales leadership by turning strategy into motion. You keep the most important work unblocked, visible, and owned. Then you get out of the way.

I used to think being an Architect meant floating above the code and drawing pretty boxes. That dies on contact with reality. Real architecture is close to the users, the backlog, and the people doing the work. It is about choosing boring solutions when the shiny toy will slow the team down next quarter.

Here is how I run the Architect lane in practice.

What I own

• Outcomes in a specific domain. Think API contracts, data modeling, frontend platform, or cloud standards.
• Direction, quality, and approach for that domain. Not every decision, but the ones that shape the next year.
• The feedback loop between user pain, product goals, and technical constraints.

My north stars

• Local decisions, global consistency. Teams move fast, but they should never feel alone. I keep a short list of patterns and anti patterns that everyone can reference.
• Friction reveals truth. If teams keep tripping over the same integration, the architecture is wrong, not the teams.
• Change that sticks. A one pager with clear trade offs and a migration path beats a 30 page deck no one reads.

Day to day

• Review high impact proposals and simplify them. If a diagram needs a legend, it is probably too clever.
• Write tiny, high value docs. Decision records, reference implementations, starter repos.
• Pair with engineers on the tricky 10 percent so the next project is faster by 50 percent.
• Host office hours. Listen first. Standards follow the pain.

Patterns I push

• Small interfaces and stable contracts.
• Backward compatible releases with a sunset date.
• Guardrails in code, not just in Confluence. Linters, scaffolds, templates.
• Focus on failure modes and rollbacks before the happy path.

Red flags to kill fast

• Big rewrite energy with vague benefits.
• Architecture reviews that feel like court.
• A platform that saves the platform team time but costs everyone else twice as much.
• Decision drift. If three teams solved the same problem three different ways, we chose confusion.

A simple playbook

1. Map the domain. What exists, who depends on it, where the data flows.
2. Write a one pager: context, options, trade offs, decision, next steps.
3. Build a reference repo that proves the decision in code.
4. Set deprecation dates and offer a migration checklist.
5. Measure adoption and defect rates. Adjust the pattern, not the people.

Wrap up: The Architect archetype is not about control. It is about clarity, defaults, and safe paths that help teams deliver. When it works, the org gets faster without everyone working late.

Some problems are too sticky for a normal sprint. The backlog is full, the pager is angry, and two teams disagree on what is even broken. That is where the Solver archetype earns its keep. It is not hero mode. It is pattern hunting with a bias to ship.

What I walk into

• Ambiguity. The problem statement is usually wrong.
• Cross team dependencies. Ownership is fuzzy.
• High risk delivery. If we miss, it hurts customers or the business.

How I start

• Quiet triage. I look at logs, dashboards, recent changes, and rollouts. No meetings yet.
• Reframe the problem. Write a one paragraph statement anyone can repeat.
• Draw the minimum map. Data flow, interfaces, failure points. Whiteboard, then code.

Tools that work

• Spike branches that answer one question at a time.
• Toggle flags to test in production without chaos.
• Shadow traffic or read replicas for safe experiments.
• A daily note with what we learned, what we cut, and what we try next.

Momentum mechanics

• Deliver thin slices. Prove the path in a week, not a quarter.
• Borrow experts for 48 hours, not 8 meetings. Pair, get the insight, keep moving.
• Make rollback the default. Confidence comes from safe exits.

Handing it back

The toughest part is the exit. Solvers can leave a mess if they toss code over the wall. I do this instead:

• Keep the solution small and documented.
• Add runbooks, alerts, and a test that fails loudly when the original bug shape returns.
• Agree on an owner before the fix merges.
• Do a short readout on what we learned so the team levels up.

What I will not do

• Stay forever. If I am the only person who understands it, I failed.
• Optimize the wrong bottleneck. Prove it with data.
• Confuse activity with progress. A noisy Slack channel is not a milestone.

Wrap up: The Solver archetype is about unlocking stuck work. Triage fast, experiment safely, ship thin, and make the handoff boring.

ChatGPT Projects Now Free for All Users

OpenAI recently announced that ChatGPT Projects are now available for free, meaning you no longer need a paid subscription to organize, save, and build on your work. This update opens the door for more creators, marketers, and professionals to streamline their workflows without any cost barrier.

What Are ChatGPT Projects?

Projects let you save work in one place, build long-form documents, and manage multi-step tasks without starting from scratch each time. They’re perfect for anyone who needs to revisit ideas or collaborate across sessions.

What You Can Do with ChatGPT Projects

Here are some examples of how to use Projects:

• Content Creation – Draft blog posts, ebooks, and newsletters while keeping edits and references organized in one workspace.
• Coding & Technical Work – Manage snippets of reusable code, debug scripts, or document workflows for engineering teams.
• Business & Marketing – Plan campaigns, track SEO content updates, or manage customer communication templates.
• Creative Writing – Keep chapters of a novel, outlines, and character profiles together for seamless storytelling.
• Research & Analysis – Collect insights, compare data, and refine reports across multiple sessions.

With Projects now free, you can experiment with all these use cases without worrying about subscription costs.

More on ChatGPT from My Blog

• How to edit your work with ChatGPT as a red pen, not a ghostwriter
• Practical Applications for ChatGPT: Search Optimization
• Welcome to Hurston’s AI Playground

Final Thoughts

This change lowers the barrier for individuals and small teams who want to get more out of ChatGPT. Whether you’re writing, coding, planning, or researching, Projects help you stay organized and move ideas forward faster.

My Experience with ChatGPT, Claude, Gemini, and Venice

Recently I ran into an issue with GPT-5 where responses from different projects started to bleed together. A project for coworker feedback began mixing into another that formatted wiki markup from technical documentation. Dropping a doc for wiki output resulted in nonsensical feedback on a nonexistent coworker. Not exactly what I wanted.

I had used Claude before and decided to shift some projects back over. Since I want these AI assistants to handle more work tasks, I also began comparing how they handle data privacy, shareable links, and whether chats show up in Google searches. That led me to check out Venice.

Research and Source Handling

I started with a straightforward prompt:

“Can you find about the writings of an author named [name] and their books regarding [book 1] and [book 2]. Give me a brief summary of all their books, both paperback, ebook, pdfs, find out all the sites they sells their books at as well as where they are reviewed and the average rating per each book. Also include when they were released/published.”

Here’s how each AI responded:

• ChatGPT asked clarifying questions, then provided books, summaries, and an author overview with 20 unique sources.
• Claude gave a similar output with 29 sources, no clarifying questions.
• Gemini offered an overview but surprisingly lacked sources or links.
• Venice returned nothing at first. After feeding it links, it managed a short summary with little information and some fabricated details.

File Upload Limitations

For file handling, Venice was restrictive. It only accepts TXT and CSV, not DOCX or XLSX. An XML export of a WordPress site (3.5MB) was too large for it to handle. Claude also struggled, but ChatGPT and Gemini processed it without issue.

The Verdict

While Claude’s responses are the fastest and most comprehensive, I find its project size and character limitations to be a challenge. This often forces me to bounce back and forth between ChatGPT and Claude. Gemini and Venice are interesting and serve niche purposes, but neither is strong enough for market research or work-related tasks. I expect this will change in the future, but for now ChatGPT and Claude are the only two worthwhile AIs for serious productivity.

You can learn more about my thoughts on topics like this in my AI Playground.

…The Naughty Side of Venice…

Since I had already paid for a month, I did decide to check out it’s NSFW features. Venice allows character creation similar to chat bots like Replika, Kindroid, and Soulkyn. However, with Replika removing explicit ERP and Kindroid now back peddling on their original privacy policy; alternatives have been popping up like weeds.

I asked Venice to create a NSFW character with background and settings context I pulled from some erotic fanfiction sites. Within five minutes it produced a chat bot arguably as good at conversations as Kindroid or Soulkyn, though lacking features like group chat and video calls which many of the NSFW bots offer as premium features.

Bringing martech and engineering together

Recently at work we hosted a Q&A session with martech thought leader Scott Brinker, editor of the Chief Martec blog and author of Hacking Marketing. During the talk he shared insights from his seminal article Rise of the Marketing Technologist and argued that marketing must control its technological destiny. He proposed a new role inside marketing: a marketing CTO or chief marketing technologist, whose mission is to provide technology navigation and ensure that marketing owns its tech stack. This role sits at the intersection of marketing technology and provides technical leadership.

Lessons from other engineering leadership blogs

• Tokyo Tech Lead – This Substack shares experiences from a software engineer and engineering manager, offering actionable advice on leadership and soft‑skill development for engineers.
• The Engineering Manager – The tagline is “empowering ourselves to empower others,” and it covers management fundamentals and practices like “going direct” that encourage open communication.
• Tech With Supun – Supun Sashika shares insights from his journey as a tech lead and offers tips for excelling in software engineering.
• Engineering Manager – This site acknowledges how hard it is to transition from senior engineer to manager and stresses that good management is crucial for retention and culture.

These blogs underscore that leadership development and technical fluency are universal themes across engineering and marketing.

Key takeaways from the Q&A

1. Recognise the rise of the Chief Marketing Technologist. The talk emphasised that marketing needs its own technologists and proposed a marketing CTO role to provide technology navigation and ensure that marketing controls its tech strategy.
2. Break down silos. Similar to James Stanier’s “go direct” philosophy, the chief marketing technologist role sits at the intersection of marketing and engineering, fostering closer collaboration.
3. Develop leadership skills early. Blogs like Tokyo Tech Lead stress learning soft skills and leadership as an engineer. The talk echoed that leadership is a behaviour that can be practiced at any career stage.

Links to more on my site

If you enjoyed these reflections, here are a few related posts on my site:

• How to edit your work with ChatGPT as a red pen, not a ghostwriter – I explain how I use AI strictly for editing by having the tool propose bracketed replacements without generating new content.
• Revolutionizing Content Marketing with AI: Top Types and Best Practices – This article explores how AI helps create social media posts, product descriptions and email campaigns, with tips on timing and A/B testing.

The Dungeons & Dragons multiverse is a vast patchwork of worlds and planes. Some campaign settings make interplanar travel part of everyday adventuring, while others encourage you to stay grounded. This guide compares three evergreen options for tabletop play-Planescape, Spelljammer and Eberron-with an eye toward playstyle, complexity and session prep. Along the way, you’ll find links to similar posts on this site and a free steampunk primer for those who like interworld intrigue with grit.

Why the Multiverse?

In 2025 the D&D multiverse is no longer just a footnote in rulebooks-it’s a marketing focus. Wizards of the Coast is emphasising world-hopping adventures in livestreams and product announcements. Planescape: Adventures in the Multiverse, Monsters of the Multiverse and Journeys Through the Radiant Citadel are all recent releases that knit together D&D worlds. The company promises even more multiverse-spanning books and campaigns.

This guide compares three evergreen settings-Planescape, Spelljammer and Eberron-for running world-hopping games in 2025. We’ll also link to Ave Molech, the self-published steampunk RPG that inspired this site. When you run a multiverse-friendly game, portals and spelljamming helms become hooks for adventures rather than just escape valves. You’ll need to explain how travel works, decide which factions shape each world and ensure your players have reasons to leave home.

Planescape: portals, factions and the Outlands

The 2024 Planescape: Adventures in the Multiverse slipcase consists of a setting book, a monster compendium and an adventure. The setting focuses on Sigil, the city of doors, and the Outlands, a neutral territory connecting every outer plane. The book doesn’t provide a full guide to the inner and outer planes, so Dungeon Masters (DMs) will need to supplement with earlier material or the core Dungeon Master’s Guide.

• Playstyle – Sigil plays like a Star-Wars-cantina meets political thriller. Faction politics, weird planar denizens and whimsical “cantina” moments can all appear, depending on your tone. Portals are everywhere; some require keys or passwords, so PC ingenuity is rewarded. However, powerful spells such as teleportation can undermine travel if you don’t clarify how they interact with Sigil’s portals.
• Complexity – Because the setting book focuses mainly on Sigil and the Outlands, you’ll need to prep planar details yourself. Players may also try to bypass whole adventures with spells or by returning to Sigil. Strong hooks are essential.
• Session prep – Choose which factions matter, decide how portals function and prepare a few Outlands gate-towns. Don’t be afraid to simplify the cosmology for new players.

For steampunk-flavoured planar intrigue, check out the Ave Molech primer on this site; it’s a d20 setting where magic powers airships and marsh adventures. Its emphasis on tieflings and airship travel meshes perfectly with Planescape’s factional politics.

Spelljammer: Wildspace and the Astral Sea

Spelljammer brings D&D into space. Adventurers travel through the Astral Sea, a plane where travellers don’t need food, water or air and move by willpower. Entire planetary systems float within Wildspace pockets inside the Astral Sea. Ships carry air envelopes that slowly degrade-fresh air becomes foul and eventually deadly-introducing resource-management tension. A spelljamming helm (a rare magic item that only spellcasters can attune) propels the vessel; ships zip through Wildspace at “100 million miles in 24 hours” but slow to a crawl in atmospheres.

• Playstyle – Expect swashbuckling naval combat among floating corpses of gods, fortresses and asteroids. Gravity planes on ships let crew fight on both decks. Critics note that the 2022 Spelljammer set provides little lore or space-combat guidance, so you’ll be doing some of the design work yourself. The setting is still high fantasy with swords and sorcery; players may battle space dragons, giant hamsters and steampunk galleons, crossing from Forgotten Realms to Greyhawk.
• Complexity – Managing air quality and gravity adds crunchy logistics. Spelljamming helms should feel rare and special to maintain tension. Because the official set omits detailed ship-to-ship combat rules, many groups homebrew mechanics or borrow from other systems.
• Session prep – Design your own Wildspace systems, decide how accessible helms are and prepare consequences for running out of fresh air. If you want to link Spelljammer to other settings, scatter portals or astral conduits that dump the party into Planescape or Eberron.

Eberron: pulp adventure and manifest zones

Eberron: Rising from the Last War turns magic into everyday technology; bound elementals power lightning rail trains, elemental galleons and rare airships; sending stones serve as telegraphs; banks use extradimensional vaults and magical lanterns light cities. This pervasive low-level magic makes Eberron feel more like late Victorian tech than high fantasy. The setting emphasises pulp adventure and noir intrigue, with urban crime families, nationalist tensions and newspapers reporting on adventurers.

Eberron’s planes are tethered to the world by manifest zones-places where the walls between planes are thin. Zones range from wide regions to a single well and influence the environment; some act as gateways. Planar alignment also ebbs and flows: at certain times, the plane of Syrania might be coterminous, allowing new portals, whereas at other times it recedes. The aftermath of the Last War ensures that nations are wary and secrets run deep.

• Playstyle – Eberron excels at pulp heists and noir mysteries. Because magic feels like steampunk technology, even low-level PCs can ride lightning rails or board airships. Manifest zones add planar flavour without forcing you to learn the entire cosmology; a single gate or planar influence can shape an adventure.
• Complexity – You’ll need to juggle intrigue, political factions and the ethics of arcane technology. The setting offers new races (warforged constructs, shifters, changelings and kalashtar) and dragonmarked houses with economic monopolies. Planar travel is limited compared to Planescape or Spelljammer; crossing to other worlds usually involves manifest zones or rare artifacts.
• Session prep – Develop a home base (Sharn, the Mournland or Khorvaire), choose a few manifest zones and decide how the Last War’s scars affect NPCs. Steal noir tropes-think shady barons, double crosses and missing persons-and sprinkle in planar oddities to remind players they’re in the multiverse.

Comparing the settings

Similar posts on this site

• Ave Molech – This d20 setting turns magic into steampunk tech with tieflings and airships. It’s the perfect companion for Planescape fans who crave gritty planar intrigue.

Final thoughts & CTA

Choosing a multiverse-friendly setting comes down to taste. Planescape offers baroque portals and ideology wars. Spelljammer trades spells for starships and requires some DIY rules. Eberron lets you blend pulp noir with arcane technology and dip into other planes via manifest zones. Each setting demands prep, but the payoff is a campaign that feels larger than life.

If your group enjoys interworld intrigue with steampunk grit, check out Ave Molech, the RPG this site’s author self-published in 2006. It offers airships, tieflings and marshland mysteries that mesh perfectly with 2025’s multiverse trend.