“I saved Latin. What did you ever do?”

If Professor John Keating from Dead Poets Society inspired students to challenge traditional education, Rushmore asks a modern question:

What if anyone could become a teacher?

Rushmore is an AI-powered course creation platform designed to help people transform ideas into complete educational experiences.

Instead of spending weeks creating lesson plans, gathering resources, designing materials, and formatting content, users can simply describe what they want to teach.

The AI builds the foundation.

The creator becomes the teacher.

The Magic Schoolbus for Modern Learning

Traditional course creation is difficult.

A creator needs to:

• Choose a curriculum structure
• Write lessons
• Create supporting materials
• Design presentations
• Produce videos
• Organize a learning experience

Rushmore compresses that process.

Users can enter:

• A course title
• Optional subtopics
• The number of topics they want generated
• The desired course format

The platform then creates an AI-generated curriculum.

The result is a personalized learning experience generated from a simple idea.

From Idea to Complete Course

Rushmore supports multiple types of AI-generated courses.

Video and Theory Courses

For creators who want richer learning experiences, Rushmore can generate courses combining:

• Educational concepts
• Structured lessons
• Video-based content

Image and Theory Courses

For visual learners, courses can include:

• Generated educational content
• Supporting imagery
• Written explanations

The goal is flexibility.

Different subjects require different teaching styles.

AI as the Teaching Assistant

Creating content is only part of education.

Students also need support while learning.

Rushmore includes an AI chatbot that allows learners to:

• Ask questions
• Clarify concepts
• Explore topics further

Instead of waiting for an instructor response, students have an always-available learning assistant.

The platform transforms AI from a content generator into an interactive educational companion.

A Complete SaaS Platform

What makes Rushmore interesting is that it is not just an AI demo.

It is structured as a real software business.

The platform includes:

User Accounts

Users can:

• Register with email
• Sign in with Google
• Sign in with Facebook
• Recover forgotten passwords
• Manage profiles

Course Management

Creators can:

• Generate courses
• Browse created courses
• Download course materials
• Track completed learning

Certificates

Learning platforms need proof of achievement.

Rushmore includes:

• Course completion certificates
• Downloadable certificates
• Email delivery

This turns generated content into a structured educational product.

Building the Business Layer

Many AI projects stop at generation.

Rushmore goes further by implementing the systems required for a commercial SaaS product.

The platform includes:

• Subscription tiers
• Recurring billing
• Payment processing
• Receipts
• Account management

Supported payment systems include:

• Stripe
• PayPal
• Paystack
• Flutterwave
• Razorpay

This makes Rushmore capable of supporting users across different regions and payment ecosystems.

The Admin Dashboard

Running a SaaS product requires visibility.

Rushmore includes an administrative dashboard where operators can monitor:

• Total users
• Course creation activity
• Revenue
• Paid subscriptions
• Free users
• Course types

Administrators can also manage:

• Users
• Courses
• Admin accounts
• Contact messages
• Legal pages

The result is not just an application.

It is the foundation of an online education business.

The Future of Personalized Education

Education has historically been constrained by one major limitation:

A teacher can only create so much content.

AI changes that equation.

A single creator can now generate:

• Specialized courses
• Niche training programs
• Personalized learning paths
• Educational products for small audiences

The future classroom may not be one-size-fits-all.

It may be millions of personalized classrooms created by individuals.

From Student to Teacher

The most interesting idea behind Rushmore is not the AI itself.

The interesting idea is democratizing expertise.

Someone with knowledge of:

• Programming
• Cooking
• History
• Business
• Crafts
• Languages
• Professional skills

can transform that knowledge into a structured course.

The barrier between knowing something and teaching something becomes much smaller.

Building the AI Creator Economy

Rushmore represents a larger shift happening across software:

AI is moving from being a feature to becoming a collaborator.

The next generation of SaaS applications will not simply store information or automate workflows.

They will help people create.

They will help people teach.

They will help people turn expertise into businesses.

Rushmore is an experiment in that future:

A platform where anyone can step onto the Magic Schoolbus and build the classroom they always wanted.

The teacher is no longer limited by time.

The curriculum is no longer limited by resources.

The classroom is wherever the learner happens to be.

Every organization faces the same cybersecurity challenge:

More vulnerabilities.
More threats.
More security tools.
More data.

Yet many security teams still struggle with the fundamentals:

• Where are our assets?
• Which vulnerabilities actually matter?
• What indicators of compromise are active?
• How do we track incidents?
• Who owns the response?
• What happened and when?

ZEPSEC was built to explore a different approach:

A centralized security operations platform that brings threat intelligence, vulnerability management, incident response, and security knowledge together in one system.

A Security Command Center for Organizations

At its core, ZEPSEC is designed as a security management platform.

It helps organizations organize their security operations around the things that matter most:

• People
• Infrastructure
• Threats
• Vulnerabilities
• Incidents
• Knowledge

Instead of treating every security event as an isolated alert, ZEPSEC creates a connected picture of an organization’s security posture.

Managing the Security Organization

Security does not happen in a vacuum.

A mature security program requires understanding:

• Which organization owns a system
• Which users are responsible
• Which agreements exist
• Which teams need notifications

ZEPSEC includes organization and user management capabilities to help security teams maintain this operational context.

Incident Response and Investigation

When an incident occurs, speed and organization matter.

ZEPSEC provides incident tracking capabilities for documenting and managing security events.

Security teams can record:

• Incident details
• Related indicators of compromise
• Investigation information
• Response activities

The goal is to transform incident response from scattered notes and chat messages into a structured workflow.

Threat Intelligence and Indicators of Compromise

Modern security operations depend heavily on threat intelligence.

An Indicator of Compromise (IoC) can include:

• Malicious IP addresses
• Domains
• Hashes
• URLs
• Other suspicious artifacts

ZEPSEC allows security professionals to:

• Manually add IoCs during investigations
• Enrich indicators automatically
• Share IoC data through APIs

This creates a central intelligence layer that can feed other security tools.

Vulnerability Management With Context

A vulnerability database can contain thousands of issues.

The challenge is determining what actually matters.

ZEPSEC integrates vulnerability information from the National Vulnerability Database (NVD) and allows organizations to enrich vulnerabilities with custom attributes.

This enables teams to move beyond:

“A vulnerability exists.”

toward:

“This vulnerability affects this system, owned by this team, with this level of risk.”

Context is what turns vulnerability data into actionable security decisions.

Security Scanning Built In

Security visibility starts with knowing what is exposed.

ZEPSEC includes scanning capabilities:

• Port scanning from ZEPSEC infrastructure
• Remote agents for distributed environments

This allows organizations to identify services and infrastructure that may require attention.

For distributed companies, remote agents provide flexibility for scanning environments that are not directly accessible.

A Security Knowledge Base

Security teams accumulate valuable knowledge:

• Investigation procedures
• Internal standards
• Incident lessons learned
• Security guidance

ZEPSEC includes a centralized knowledge base to preserve that information.

A security program becomes stronger when knowledge survives beyond individual employees.

Automation Through Alerts and APIs

Security operations generate constant activity.

ZEPSEC includes automated notifications for:

• New indicators of compromise
• Vulnerability updates
• Knowledge base changes

It also provides REST API integration, allowing security data to move into the broader security ecosystem.

The goal is not to replace every security tool.

The goal is to connect them.

The Open Source Security Model

One interesting aspect of ZEPSEC is its approach to distribution.

The open-source version provides a foundation for security professionals who want to explore and operate the platform themselves.

A commercial version can provide additional features, support, and enhancements.

This follows a proven open-source security model:

• Community adoption
• Professional usage
• Enterprise support

Why Security Platforms Matter

Cybersecurity has traditionally been fragmented.

Organizations often deploy separate tools for:

• Vulnerability scanning
• Threat intelligence
• Incident response
• Asset tracking
• Documentation

The result can be a collection of disconnected dashboards.

ZEPSEC explores a unified approach:

One place where security teams can understand their environment.

One place where incidents become knowledge.

One place where intelligence becomes action.

Building the Future of Security Operations

The future of cybersecurity is not just about detecting more threats.

It is about building systems that help humans make better decisions.

Security professionals need platforms that reduce noise, preserve knowledge, and connect information across the organization.

ZEPSEC represents that vision:

A security operations platform designed around the workflows that defenders actually need.

Because the best security tool is not the one with the most alerts.

It is the one that helps teams respond intelligently.

Clone it at https://github.com/peteralcock/ZEPSEC

Security teams don’t need more alerts. They need better systems.

Before every website depended on Google AdSense, before programmatic advertising became dominated by massive exchanges, publishers controlled their own advertising infrastructure.

They sold banner placements directly.

They managed campaigns.

They negotiated with advertisers.

They owned the relationship.

Aditube is an open-source experiment built around that idea:

What if anyone could clone a repository, install a web server, and run their own digital advertising platform?

Maybe they won’t make billions.

But now they have the tools.

The Personal Ad Network

Aditube is a self-hosted ad server designed for website owners, publishers, and media companies that want complete control over their advertising operations.

Instead of sending visitors through a third-party advertising network, publishers can run their own infrastructure:

• Upload advertisements
• Create campaigns
• Sell inventory
• Track impressions and clicks
• Manage advertisers
• Rotate banners automatically

The result is a miniature version of the advertising systems that power major publishing companies.

Built for the Independent Publisher

Aditube supports multiple use cases.

Website Owners

A single website owner can:

• Add banner placements
• Sell advertising directly
• Manage campaigns
• Replace external ad networks

For niche websites with dedicated audiences, direct advertising can often provide better relationships and more control than generic ad networks.

Publishers

Publishers operating multiple websites can manage:

• Multiple domains
• Multiple ad positions
• Multiple advertisers
• Campaign performance

Media Companies

Larger organizations can use Aditube as an internal advertising platform:

• Webmasters configure available placements
• Advertisers purchase campaigns
• Administrators manage billing and inventory

Supporting Modern Advertising Formats

Although banner ads are one of the oldest forms of online advertising, Aditube was designed for modern web formats.

Supported creative types include:

• GIF banners
• JPG images
• PNG images
• HTML5 advertisements
• External advertising scripts

HTML5 ads can be uploaded as ZIP packages containing:

• HTML
• CSS
• JavaScript
• Animations
• Video content

This allows advertisers to create richer experiences than traditional static banners.

Automatic Banner Rotation

A core feature of any ad server is deciding what appears and when.

Aditube manages banner positions and automatically rotates campaigns.

Publishers can define:

• Advertising locations
• Available inventory
• Multiple campaigns per position

The system handles delivery.

A website owner can create an advertising slot once and allow the platform to manage the rotation of campaigns over time.

Building a Marketplace for Advertising

Aditube goes beyond simple banner management.

It includes the foundation for a self-service advertising marketplace.

Advertisers can:

1. Create an account
2. Upload a banner
3. Select advertising placement
4. Set a budget
5. Purchase inventory

After payment, campaigns can automatically become active.

Supported payment integrations include:

• PayPal
• Coinbase

The result is a complete advertising workflow:

Advertiser → Payment → Campaign → Banner Delivery → Analytics

The Shortcode System

One of the clever engineering decisions in Aditube is the use of banner shortcodes.

Instead of hardcoding tracking URLs or metadata into every advertisement, banners can contain dynamic placeholders:

[CLICKTAG]
[ID]
[TIMESTAMP]

During delivery, Aditube replaces these values automatically.

This enables:

• Click tracking
• Dynamic campaign information
• Cache-friendly delivery
• Flexible creative management

Why Build an Ad Server?

At first glance, building an ad server might seem unnecessary.

After all, companies like Google and Meta have already solved advertising.

But that misses the point.

The modern internet has become increasingly centralized.

A small publisher often has little control over:

• Who advertises on their site
• How much revenue they receive
• What data is collected
• How relationships with advertisers are managed

Self-hosted tools like Aditube represent another vision:

A web where publishers own their infrastructure.

A Time Capsule of the Open Web

Aditube belongs to a long tradition of independent internet software.

The same philosophy powers:

• Self-hosted blogs
• Independent forums
• Open-source content management systems
• Personal analytics tools
• Independent publishing platforms

The idea is simple:

If you can run your own website, you should be able to run your own business around it.

The Future of Independent Advertising

The advertising industry has evolved dramatically.

Today, many creators rely on platforms they do not control.

But there is renewed interest in:

• Direct sponsorships
• Creator-owned audiences
• Privacy-focused advertising
• Independent publishing infrastructure

Projects like Aditube explore what that future could look like.

Not every website needs its own advertising empire.

But every publisher should have the option.

Maybe you won’t make billions.

But now you can run the server.

What if you could run your own advertising network?

Clone it at https://github.com/peteralcock/aditube

What happens when Warren Buffett, Michael Burry, Cathie Wood, and Charlie Munger all get a seat at the same investment committee?

That was the question behind Gekko — an experimental AI hedge fund platform designed to explore what happens when multiple artificial intelligence agents, each modeled after a different investing philosophy, collaborate on portfolio decisions.

Gekko is not a real trading system. It does not manage money, execute trades, or make investment recommendations.

Instead, it is a sandbox for exploring a fascinating question:

Can the reasoning patterns of legendary investors be translated into autonomous AI systems?

From Investment Legends to AI Agents

Traditional investment firms are built around teams of specialists.

A value investor might focus on discounted cash flows and margin of safety. A macro investor might analyze interest rates and economic cycles. A growth investor might search for disruptive technologies before the market recognizes their potential.

Gekko takes that human investment committee model and transforms it into a multi-agent AI system.

The platform includes AI personas inspired by some of history’s most recognizable investors:

Agent	Investment Philosophy
Ben Graham	Value investing and margin of safety
Warren Buffett	Quality businesses at reasonable prices
Charlie Munger	Durable competitive advantages
Peter Lynch	Practical growth investing
Michael Burry	Contrarian opportunities
Bill Ackman	Activist investing and high conviction ideas
Cathie Wood	Disruptive technology and innovation
Stan Druckenmiller	Global macro strategy
Phil Fisher	Deep company research

Rather than asking one AI model for an answer, Gekko creates a simulated investment committee where different perspectives can compete.

The AI Investment Committee

A major challenge with AI systems is that they often produce confident answers without showing their reasoning.

Gekko approaches this differently.

Each agent has a specialized role:

• Fundamentals Agent analyzes financial metrics and company performance.
• Technical Agent examines market patterns and indicators.
• Sentiment Agent evaluates market psychology.
• Valuation Agent estimates intrinsic value.
• Portfolio Manager coordinates decisions.
• Risk Manager evaluates exposure and downside.

The result is not a single prediction.

It is a simulated debate.

One agent may argue that a company is undervalued. Another may warn that growth expectations are unrealistic. A third may identify technical weakness despite strong fundamentals.

The final portfolio decision emerges from the interaction between competing viewpoints.

Explainable AI for Investment Decisions

One of the most interesting features of Gekko is its emphasis on explainability.

The platform supports a reasoning mode that exposes the logic behind simulated decisions:

--show-reasoning

Instead of simply displaying:

BUY AAPL

the system can show the chain of thought behind the recommendation:

• Why did the valuation agent think the company was attractive?
• What risks did the risk manager identify?
• Which investor persona influenced the final decision?
• How did sentiment affect confidence?

The goal is not just to create AI decisions.

The goal is to understand them.

A Full AI Trading Laboratory

Under the hood, Gekko combines several technologies:

AI Models

The platform supports multiple LLM providers:

• OpenAI models
• Groq
• Ollama

This allows experimentation with different models and performance characteristics.

React Dashboard

The frontend provides a visual command center for observing:

• Agent decisions
• Portfolio changes
• Trade history
• Market simulations
• Backtesting results

The dashboard turns an abstract AI workflow into something closer to watching a real investment team operate.

Backtesting and Simulation

Real investors do not judge strategies based on a single decision.

They evaluate performance over time.

Gekko includes:

• Historical date ranges
• Simulated trading
• Portfolio tracking
• Trade logs
• Performance visualization

The platform allows researchers and developers to ask questions like:

• Would a value-focused AI committee have avoided certain market crashes?
• Would growth-oriented agents have identified emerging trends earlier?
• How do different AI models behave under the same market conditions?

Why This Matters

The future of AI is likely not a single super-intelligent assistant making every decision.

It may look more like organizations of specialized agents:

• Researchers
• Analysts
• Critics
• Strategists
• Decision makers

Gekko explores that idea in a familiar domain: investing.

The project transforms investing from a single-model prediction problem into a collaboration problem.

Instead of asking:

“What does the AI think?”

Gekko asks:

“What happens when different AI perspectives argue, collaborate, and make decisions together?”

The Future of AI Decision Systems

Investment management is just one example.

The same architecture could apply to:

• Business strategy
• Product planning
• Scientific research
• Security analysis
• Legal review
• Healthcare decision support

Many important decisions benefit from multiple perspectives rather than one answer.

Gekko is an experiment in building those systems.

A virtual hedge fund.

A simulated investment committee.

A laboratory for exploring how AI agents can reason together.

The market may be unpredictable.

But the future of decision-making is increasingly looking collaborative.

Play it at https://burnertrail.com

Brooklyn → Black Rock. 2,900 miles. Zero showers.

What happens when you take one of the most recognizable educational games of all time, replace covered wagons with a 1995 RV named Big Bertha, and send five friends across America toward Burning Man?

You get The Burner Trail — a full-stack Oregon Trail parody built for the modern desert pilgrim.

The original Oregon Trail asked players to survive a brutal journey westward through hunger, disease, bad decisions, and unpredictable weather. The Burner Trail keeps the same spirit of adventure and chaos, but swaps the frontier for a very different American migration: the annual pilgrimage from Brooklyn to Black Rock City.

The mission is simple:

Get five people, one aging RV, and enough supplies across 2,900 miles of highway before the playa market begins.

The reality is much harder.

Meet Big Bertha: Your 30-Year-Old Mechanical Liability

Every great road trip starts with a questionable vehicle.

In The Burner Trail, players take control of Big Bertha, a 1995 RV whose condition determines whether the journey becomes a triumphant arrival or a roadside disaster.

The RV has a condition meter that changes throughout the trip:

• Push too hard and breakdown risks increase.
• Ignore maintenance and repairs become inevitable.
• Run the vehicle into the ground and you may face a $300 repair bill and a two-day delay.

The game turns the classic Oregon Trail resource-management formula into something instantly familiar to anyone who has ever attempted a cross-country adventure with unreliable transportation.

A Modern Oregon Trail Built for 2026

While The Burner Trail is a parody, it is also a serious technical project.

The game was built as a complete full-stack application:

• Frontend: React 18 + Vite
• Backend: Express
• Database: SQLite with persistent Docker volumes
• Infrastructure: Terraform deployments for DigitalOcean and AWS
• Deployment: One-command cloud provisioning

A player can launch the game locally with Docker or deploy the entire application to the cloud with a single command.

The goal was not just to make a browser game, but to build a production-ready platform capable of supporting real players.

The Hall of Dust: Everyone Leaves a Mark

Death is inevitable on the trail.

But in The Burner Trail, your failure becomes part of the story.

When a player meets their fate, they can leave behind a tombstone — a digital epitaph that future travelers may discover along the route.

The game creates a shared history between players:

• Your friends can discover where you failed.
• Future travelers encounter your grave.
• Every run contributes to the growing mythology of the trail.

The leaderboard, appropriately called the HALL OF DUST, ranks every journey and immediately tells players where they stand after completing a run.

Every Choice Has Consequences

Like the original Oregon Trail, success depends on managing limited resources.

Players must balance:

• Water consumption
• Cargo weight
• RV condition
• Weather patterns
• Morale
• Travel speed
• Market timing

Even departure date matters.

Leave earlier and you have more schedule flexibility. Leave later and you risk more extreme conditions. The game forces players to make the same kind of uncomfortable tradeoffs that define real adventures.

The Fork in the Road

No road trip is complete without questionable navigation decisions.

At Chicago, players choose their route:

• The classic I-80 path
• A southern route through Denver and Moab
• A northern shortcut with greater risk

Each route changes the landmarks, weather challenges, and encounters along the way.

The game transforms interstate geography into a strategic decision rather than a background map.

From Jersey to the Playa

The journey is not just about surviving the highway.

Along the way, players encounter:

• Regional weather systems
• Scavenge opportunities
• Gift-economy caravans
• Sound-camp defections
• Supply shortages
• Random events

The final destination introduces a six-day playa market where survival continues after arrival.

Even reaching Burning Man does not mean the challenge is over.

A Retro Experience With Modern Features

Visually, The Burner Trail embraces nostalgia.

The interface features:

• CRT phosphor-inspired styling
• Typewriter text effects
• Canvas-based dust storms
• Animated environmental effects
• A shifting green-to-amber color palette as conditions deteriorate

But underneath the retro aesthetic is modern engineering.

Players can:

• Save progress through email-linked magic links
• Resume games across devices
• Share scores socially
• View rankings
• Leave persistent messages for future travelers

A Small Game With a Real Product Mindset

One of the most interesting aspects of The Burner Trail is that it was designed not only as a game, but as a potential sustainable project.

Optional monetization features include:

• Curated affiliate links for real camping gear
• Contextual recommendations based on gameplay situations
• A real-world packing list connected to in-game supplies
• Analytics designed around anonymous usage patterns

The philosophy is simple: if a player runs out of water in the game, perhaps they are interested in learning about real-world water storage. If their RV breaks down, perhaps they need camping or repair equipment.

The commercial layer stays optional and secondary to the experience.

The Spirit of the Trail

At its core, The Burner Trail is about something bigger than parody.

It captures the absurdity of modern adventure:

• Spending thousands of dollars to live without basic comforts for a week
• Driving unreliable vehicles into remote deserts
• Building elaborate temporary communities
• Trading convenience for experience

The original Oregon Trail reflected the challenges of American expansion.

The Burner Trail reflects a different kind of migration — one where people leave cities behind, chase temporary communities, and willingly trade comfort for chaos.

The destination may be Black Rock.

But the real game has always been the journey.

Welcome to the trail. Pack water. Check Big Bertha. And try not to become another name in the Hall of Dust.