DEV Community

Cover image for Anthropic: From Pandemic-Era Safety Concerns to a $350B AI Company
Prakash Pawar
Prakash Pawar

Posted on

Anthropic: From Pandemic-Era Safety Concerns to a $350B AI Company

In early 2021, at the height of the COVID-19 pandemic, a small group of former OpenAI researchers made a decision that would quietly reshape the AI industry.

What began as masked, socially distanced backyard meetings would become Anthropic, an AI company valued at over $350 billion by November 2025 — built around a single core belief:

Powerful AI systems must be safe, interpretable, and aligned by design.

This is the story of how that belief evolved from internal disagreement to one of the most influential AI companies in the world.


The Genesis: A Safety-First Vision

Anthropic was founded by seven former OpenAI researchers led by siblings Dario and Daniela Amodei.

The group left OpenAI due to directional disagreements, particularly around how aggressively AI capabilities should be scaled relative to safety research. While OpenAI pushed forward with increasingly powerful models, this group believed safety needed to be more foundational — not an afterthought.

Those early discussions, held during the second wave of COVID-19, laid the groundwork for a new company with a fundamentally different philosophy.


The Founders: A Complementary Partnership

Dario Amodei — Technical Leadership

Dario Amodei brought deep technical credibility to the venture. As OpenAI’s Vice President of Research, he led the development of GPT-2 and GPT-3 and co-invented reinforcement learning from human feedback (RLHF).

His background spans:

  • Physics at Stanford
  • Computational neuroscience at Princeton
  • Research roles at Baidu and Google Brain
  • OpenAI, where he joined in 2016

This mix of theoretical depth and practical AI scaling experience shaped Anthropic’s research direction.


Daniela Amodei — Operations and Policy

Daniela Amodei complemented her brother’s technical focus with operational leadership.

Her background includes:

  • English Literature, Politics, and Music at UC Berkeley
  • Five years at Stripe in operational roles
  • Vice President of Safety and Policy at OpenAI

At Anthropic, she focused on ethical deployment, governance, and institutional design, ensuring safety principles extended beyond model training into company structure.


Constitutional AI: Anthropic’s Core Innovation

Anthropic’s defining breakthrough was Constitutional AI (CAI) — a training approach designed to scale safety without relying exclusively on human moderators.

Unlike traditional RLHF, Constitutional AI introduces explicit, inspectable values into the training process.

Phase 1: Supervised Self-Critique

  • The model generates responses
  • It critiques its own outputs against a written “constitution”
  • It revises and learns from those critiques

The constitution consisted of 75 principles, drawing from sources like the UN Universal Declaration of Human Rights.


Phase 2: Reinforcement Learning from AI Feedback (RLAIF)

  • AI systems, not humans, evaluate responses
  • A preference model is trained on constitutional compliance
  • Harmful behavior is trained out without exposing humans to disturbing content

This made safety scalable — a critical requirement for frontier models.

Importantly, Anthropic made these principles explicit and editable, rather than embedding values opaquely inside model weights.


Claude: From Internal Experiment to Public Model

Anthropic completed training the first version of Claude in summer 2022 but deliberately chose not to release it immediately.

The concern was triggering an AI arms race focused purely on capability.

Three months later, OpenAI released ChatGPT.

Claude finally launched publicly in March 2023, named after Claude Shannon, the founder of information theory. The name was intentionally masculine, contrasting with assistants like Alexa and Siri.

From the beginning, Claude stood out for:

  • A 200,000-token context window
  • Emphasis on being helpful, harmless, and honest

Two versions launched initially:

  • Claude
  • Claude Instant (faster, lighter)

Early Foundations: From Concept to Code

Founding Discussions (2020–2021)

Before infrastructure existed, the team aligned on a key insight: scaling laws.

They recognized that:

  • More compute + more data + simple algorithms
  • Leads to broad cognitive improvements

These insights drove their belief that safety had to scale alongside capability.

After brainstorming names like Aligned AI, Sparrow, and Sloth, they settled on Anthropic — human-centered and available as a domain.


Early Research Focus (2021)

Rather than launching products quickly, Anthropic focused on fundamental research.

The founding team (15–20 people) met weekly, often outdoors, to refine ideas that would later culminate in Constitutional AI, published in December 2022.


Infrastructure Evolution: From Cloud Rentals to Megascale Compute

Phase 1: Google Cloud (2021–2023)

Anthropic initially relied on standard GPU clusters via Google Cloud, allowing fast iteration without massive capital expenditure.

This phase validated the Constitutional AI approach on smaller models.


Phase 2: Multi-Cloud Strategy (2023–2024)

Amazon invested $4 billion, becoming Anthropic’s primary training partner.

AWS committed to developing custom Trainium chips optimized for Anthropic’s workloads.


Phase 3: Massive Scale-Up (2024–2026)

Anthropic’s compute footprint exploded:

AWS — Project Rainier

  • Hundreds of thousands of Trainium2 chips
  • 1,200-acre campus in Indiana
  • Over 1.3 GW of dedicated IT capacity
  • Custom kernel-level optimizations

Google Cloud

  • Commitment to deploy up to one million TPUs
  • Seventh-generation Ironwood TPUs
  • Tens of billions of dollars in infrastructure
  • Distribution via Vertex AI

Nvidia GPUs

  • Used selectively for specialized workloads
  • Ensured flexibility and avoided vendor lock-in

Software Stack and Training Pipeline

Core Technologies

  • Python (primary language)
  • PyTorch and JAX
  • Distributed training on cloud infrastructure

Training Data

  • Web scrapes
  • Licensed content
  • Contractor-provided examples
  • User interactions (opt-in)

A major initiative involved digitizing millions of books, which later resulted in a $1.5B copyright settlement.


Claude Model Evolution

Claude 1 & 2 (2023)

  • Initial public release
  • Expanded context windows

Claude 3 Family (March 2024)

  • Haiku (fast, small)
  • Sonnet (balanced)
  • Opus (largest, most capable)
  • Multimodal input and massive context

Claude 3.5 Sonnet (June 2024)

  • Introduced Artifacts (live code previews)
  • Launched Computer Use, enabling Claude to operate software directly

Claude 4 Family (May 2025)

  • Hybrid reasoning modes
  • Classified as ASL-3, triggering enhanced safeguards

Claude 4.5 (Late 2025)

  • State-of-the-art coding performance
  • Aggressive pricing reductions
  • Strong agentic and tool-use capabilities

Beyond the Chatbot: Product Ecosystem

Core Products

  • Claude API
  • Claude.ai (consumer interface)
  • Claude Code (developer-focused coding assistant)
  • Claude Enterprise

Platform Innovations

  • Model Context Protocol (MCP)
  • Secure code execution
  • Persistent file context
  • Agent Skills
  • Tool discovery
  • Web search integration

Business Model and Growth

Revenue Streams

  • API usage (70–75%)
  • Subscriptions (10–15%)
  • Enterprise partnerships

Anthropic reached:

  • $5B ARR by mid-2025
  • $500M annualized revenue from Claude Code within 8 weeks

Governance and Safety

Anthropic operates as a Public Benefit Corporation (PBC) with a Long-Term Benefit Trust, embedding safety into corporate governance.

The Anthropic Safety Levels (ASL) framework defines deployment thresholds and safeguards, inspired by biosafety protocols.


Challenges and Controversies

  • Copyright litigation
  • Security incidents involving misuse
  • Political scrutiny around funding sources

Despite this, Anthropic continued to emphasize transparency and controlled scaling.


Looking Ahead: 2026 and Beyond

Anthropic is now focused on:

  • Multi-agent orchestration
  • Digital executive-style agents
  • Deeper OS-level integrations

The question is no longer whether AI can act — but how much autonomy we can safely trust it with.


Conclusion: Safety Without Sacrifice

From masked backyard meetings to global infrastructure spanning millions of AI chips, Anthropic’s journey shows that safety and capability are not mutually exclusive.

Their work on Constitutional AI, ASL, Computer Use, and governance structures has influenced the entire industry.

Whether Anthropic ultimately succeeds in fully aligning powerful AI systems with human values remains uncertain.

But their story proves one thing:

Principled AI development can scale — technically, commercially, and ethically.


Feel free to drop a comment or reach out on
X (Twitter)

Thanks for reading.

Top comments (0)