AI Engineer World’s Fair 2025 - Tiny Teams

By AI Engineer

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Key Concepts

  • Tiny Teams: Small, highly effective teams achieving significant results.
  • Generalist vs. Specialist: Hiring individuals with broad skillsets and adaptability versus those with narrow expertise.
  • Player-Coach Model: Leaders who actively contribute to the work while also mentoring and guiding the team.
  • Product-Led Hiring: Attracting talent through the appeal and utility of the product itself.
  • Profit-First Mentality: Prioritizing profitability as a key decision-making metric.
  • Super Tools: Leveraging existing tools in unconventional ways to maximize their utility.
  • Harvester and Cultivator Model: Organizing engineering teams into product-focused (Harvesters) and infrastructure-focused (Cultivators) roles.
  • Benchmarks as Memes: The idea that benchmarks, like memes, spread and influence the development of AI models.
  • Benchmark Saturation: The phenomenon where models become overly optimized for specific benchmarks, diminishing their real-world relevance.
  • High Agency: Individuals who take initiative, ownership, and solve problems independently.

Stack Blitz's Bolt.net: Scaling with a Small Team

The Unexpected Success of Bolt

  • Stack Blitz, after seven years as a company with $0.7 million ARR, launched Bolt.net.
  • The team was less than 20 people at launch.
  • Initial expectations were modest, aiming for $100,000 ARR by year-end.
  • Bolt exceeded expectations, more than doubling ARR in a short period.
  • The growth was remarkably smooth, despite the product being a stripped-down MVP.

Team Structure and Philosophy

  • Small Teams with More Context: Emphasizing a small number of people with broad understanding and agency.
  • Empowerment and Speed: Enabling team members to build and implement without excessive bureaucracy.
  • Low Burn Rate: Maintaining a lean operation to extend runway and increase opportunities for product market fit.
  • Shared Core Values: Prioritizing low ego, high trust, user obsession, and resilience.
  • Analogy to the Movie 300: The feeling of being a small, aligned team surrounded by overwhelming demands.

Prioritization and Firefighting

  • The Fire Truck Analogy: Prioritizing high-impact areas and key infrastructure during periods of intense demand.
  • Hard Decisions: Accepting that some issues will have to be left unresolved.
  • Focus on the Essential: Concentrating on 10% of the tasks that yield the majority of the results.

Independent Thinking and Community Engagement

  • Avoiding Hive Mind: Encouraging independent decision-making and critical evaluation of industry trends.
  • Leading from the Front: Actively engaging with the community to build trust and gather feedback.
  • Weekly Office Hours: Hosting live sessions to showcase progress and address user concerns.
  • Community Building: Creating spaces for users to learn from each other and receive support.
  • Hackathon.dev: Hosting the world's largest hackathon to drive product adoption and gather feedback.

AI-Powered Support

  • Parah Help: Implementing AI-powered support tools to automate ticket resolution.
  • SAM AI Assistant: Using Parah Help's SAM to resolve 90% of support tickets automatically.
  • Custom AI Models: Training internal models to assist users within the product experience.

Key Takeaways

  • Don't hire an army, hire a small number of Spartans.
  • Focus on building a strong, aligned team with shared values.
  • Prioritize ruthlessly and focus on the most impactful tasks.
  • Engage with the community and build trust.
  • Leverage AI to automate support and improve the customer experience.

Alie: The New Lean Startup

The Shift Towards Leanness

  • Companies are becoming smaller, rounds are getting delayed, and profitability is being attained earlier.
  • AI tooling is driving this shift, enabling small teams to generate significant ARR.
  • The age of bloated teams and endless hiring rounds is over.

Alie's Success

  • Building a portfolio of consumer software products.
  • Scaling to $6 million ARR profitably with a team of four.
  • Generating over half a billion views across social media.

Key Milestones

  • January 2023: Launching Quizard AI mobile app with a viral TikTok video.
  • Early Scaling: Utilizing the initial Codex model for AI outputs, cycling through multiple accounts.
  • Fall 2023: Moving to New York City and launching a back-to-school campaign, hitting $1 million ARR and profitability.
  • Spring 2024: Achieving number six in the education charts alongside companies like Dualingo.
  • New Product: Unstuck AI: Reaching a million users in under nine weeks and generating over a quarter billion views.
  • Third Product Launch: Launching a profitable product outside the education domain in three weeks.

The Lean Playbook

  • Operating Principles:
    • Hiring: Hiring 10xer generalists with multiple complementary spikes.
    • Profit First Mentality: Prioritizing profits as a key decision-making metric.
    • KPI Ownership: Aligning everyone in the company to a KPI.
    • Continuous Process Refinement: Continuously improving processes based on feedback and failures.
    • Super Tools: Building compounding benefits by investing in technical playbooks and operational blueprints.
  • Organizational Structure:
    • Harvester and Cultivator Model: Organizing engineering teams into product-focused (Harvesters) and infrastructure-focused (Cultivators) roles.
  • AI Tooling Augmentation:
    • Using AI to automate tasks and augment the capabilities of the team.

Super Tools: Launch Darkly

  • Intended Use Case: Feature management platform.
  • Extended Use Cases:
    • Manual Traffic Load Balancer: Rerouting traffic to different LLM providers based on rate limits.
    • On-the-Fly Infrastructure Changes: Changing the prioritization of ingestion processes.
    • UI Modifications and Paywall Experiments: Running experiments without code pushes.

Key Takeaways

  • Hire senior generalists who can work across the stack.
  • Prioritize profits and focus on moving key metrics.
  • Continuously refine processes and leverage super tools.
  • Organize teams into product-focused and infrastructure-focused roles.
  • Use AI to automate tasks and augment the capabilities of the team.

Gum Loop: Scaling Automation with a Small Team

The Gum Loop Journey

  • Founder Max Broer Herbas spent six months building various software projects.
  • Created the first UI for AutoGen, an open-source framework for AI agents.
  • Realized that users needed a way to define complex workflows for AI agents.
  • Pivoted to a workflow automation tool.
  • Joined YC, raised a seed round, and then a series A.
  • Scaled with under 10 people, focusing on hiring exceptional talent.

Hiring Approach

  • Be Super Picky: Only hire candidates that are exceptionally exciting.
  • Product-Led Hiring: Attract talent through the appeal and utility of the product itself.
  • Work Trials: Bring candidates on for several days to assess their fit and skills.

Internal Operations

  • Almost No Meetings: Prioritize deep focus time for building.
  • Let People Build: Empower team members to take ownership and build without excessive oversight.
  • Automate Everything Internally: Use Gum Loop to automate various business processes.

Culture

  • What If We Built It Today?: Encourage rapid iteration and shipping.
  • Make It Fun: Organize retreats and activities to offset the intensity of building.
  • Be Intentional About Company Culture: Document values and expectations in a company handbook.

Key Takeaways

  • Hire exceptional talent and give them the space to build.
  • Automate everything possible to maximize efficiency.
  • Create a fun and supportive culture.
  • Be intentional about company values and expectations.

Benchmarks as Memes

The Power of Benchmarks

  • Benchmarks, like memes, spread and influence the development of AI models.
  • Benchmarks define what model providers are trying to get their models good at.
  • A single person can come up with an idea for a benchmark that shapes the future of AI.

The Problem with Benchmarks

  • Benchmarks are getting saturated.
  • Models are becoming overly optimized for specific benchmarks, diminishing their real-world relevance.
  • Benchmarks can be gamed or manipulated.

The Opportunity

  • Create new benchmarks that are more relevant and meaningful.
  • Shape the future of AI by defining what models should be good at.
  • Empower people by giving them agency in the development of AI.

Characteristics of a Great Benchmark

  • Multifaceted: Allows for a variety of strategies to succeed.
  • Reward Creativity: Encourages innovative solutions.
  • Accessible: Easy to understand for both models and people.
  • Generative: Can be used to train future models.
  • Evolutionary: Gets harder as models improve.
  • Experiential: Mimics real-world situations.

AI Diplomacy: A Case Study

  • A benchmark that uses the board game Diplomacy to assess the social and strategic abilities of AI models.
  • Models must negotiate, form alliances, and betray each other to win.
  • Revealed interesting personality traits of different models.
  • Highlights the need for squishy, non-static benchmarks.

The Importance of Trust

  • Benchmarks can help build trust in AI by showing people how it works and what it can do.
  • People need to feel like they have a role in the development of AI.
  • Benchmarks can empower people by giving them agency in the process.

Key Takeaways

  • Benchmarks are powerful tools that can shape the future of AI.
  • Create benchmarks that are relevant, meaningful, and empowering.
  • Focus on building trust in AI by involving people in the process.

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