A deep dive in leaked code of Anthropic

 

Leaked code of Anthropic (March 2026) reveals something remarkable. Conway, a previously unannounced, always-on AI agent. This leak reveals a comprehensive, multi-surface platform strategy that signals the start of intense AI platform wars.

Key Takeaways:

• The Conway Agent: Operating as a persistent, standalone environment within Claude, Conway can monitor emails, track Slack channels, and perform autonomous tasks overnight based on learned user patterns.
• The Platform Play: Anthropic is executing a five-surface strategy including Claude Code (developers), Claude Co-Work (enterprise), Conway (the always-on agent), a marketplace for procurement, and new enforcement mechanisms.
• The "Active Directory" Parallel: Much like Microsoft's strategy in the 90s, Anthropic is attempting to lock in enterprise users by controlling how businesses compute and interact with AI, with Conway serving as the central, sticky "Active Directory" layer.
• Proprietary Lock-In: While Anthropic champions the open Model Context Protocol (MCP), Conway uses a proprietary extension format (CNW.zip) that traps developers into the Anthropic ecosystem.
• Behavioral Lock-In: Conway learns your specific work habits and behavioral patterns over months, switching to a different provider would mean losing that accumulated context - effectively starting from scratch with a "brilliant stranger”.  I am naming it as “intelligence portability issue”.

The competitive landscape is shifting from foundation models to the "persistence layer." Companies and individuals are now facing a crucial choice: stick with a convenient, proprietary platform like Conway (leading to extreme vendor lock-in) or prioritize open, portable memory layers.

The Future of Desire: Understanding Post-Scarcity Black Markets

 

What happens to society when material needs are no longer a concern? I recently sat down with a group of high school students to explore the concept of Post-Scarcity Black Markets - worlds where advanced technology meets every basic physical requirement.

It was a fascinating look into how the next generation perceives civilization. The core takeaway? Even when material items are abundant, black markets will thrive. They won't be driven by a lack of supply, but by restrictions, ethics, novelty, thrill, and the unyielding nature of human desire.

Here is what we discovered about the "shadow commerce" of the future:

Post scarcity does not mean infinite abundance of EVERYTHING, so everything is NOT FREE but abundance of materials.

 

What Gets Trafficked

Since replicators can produce most goods, black markets focus on:

• Autonomy, Privacy and Unfiltered Data: Anonymity and independence from systems – off-grid identities, access to unmonitored spaces, untracked economic transactions, tools to scramble biometrics and telemetry from the central AI.

In this world, privacy itself may become contraband.

• Personal Augmentation: Unregulated human argumentation - Illegal genetic edits (intelligence, aggression, longevity), banned neural implants, memory edit, personality modification.

This is where black markets create superhumans or unstable ones

• Authenticity: Handmade items, pre-technology era collectibles, natural (non-synthetic food, real performances with imperfections, or nostalgic items that represent emotional states rather than utility.

This becomes a world where “handmade” is contraband luxury.

• Restricted Experiences: Access to dangerous, extreme, forbidden experiences – high risk physical experiences, unfiltered virtual realities, “raw” or unmoderated internet layers.

Think of it as adrenaline and taboo becoming the new drugs

• Dangerous Innovations and Unfiltered Tech: Jailbroken or unfiltered artificial intelligences that lack the safety protocols, fabrication labs for prohibited devices, smuggling of off-world tech from less-regulated colonies, bartered restricted resources (e.g., rare elements not fully abundant yet).

Potentially leading to "gray zones" where authorities turn a blind eye to innovation benefits.

• Taboo Computing: Unauthorized AI creation, mind emulations, or illegal brain scanning and memory extraction & plantation.

Taboos are always desirable to a lot of people

• Forbidden Identity: Unregistered personalities or curated emotional experiences extracted from donors (willing as well as forced).

• Scarcity Recreation Market: Simulated “hard mode” environments (no AI help, limited resources), Real-world exclusion zones where automation is banned, Underground “survival economies.”

People will pay to feel what it was like when things mattered more

• Positional Goods and Social Scarcity: "Illegal" access to protected historical sites, nature preserves, or prime real estate that cannot be replicated; a "shadow" reputation market where people trade favors or social credit to gain access to exclusive social circles that cannot be entered through material wealth alone. 

Exclusivity always demands a premium

 Black markets mostly don’t depend on a lack of supply; they depend on restrictions and human desire.

In post-scarcity, the equation shifts:

Black markets = Anything restricted by law, ethics, or system control, not by production limits

The Ecosystem of Shadow Commerce

Instead of traditional street gangs, these markets are run by algorithmic syndicates, rogue AIs, unregulated AI agents acting on behalf of humans, or human enclaves seeking freedom from oversight. Governments often tolerate these markets as a social release valve to prevent greater societal anxiety and as a source of innovation - focusing on containment rather than total eradication.

From Infrastructure to Apps: A Deep Dive into the AWS AI Stack

 

Amazon’s AI stack, centered around Amazon Web Services (AWS), is vertically integrated. It spans from raw infrastructure all the way to end-user AI applications. The key idea: AWS doesn’t just give you models; it gives you every layer needed to build, train, deploy, and scale AI systems in production.

 

Let’s break it down cleanly, layer by layer.

Layer 1: Data Layer

Purpose: Enables data collection, storage, processing, and preparation for ML

• Amazon S3: Scalable object storage for datasets and model artifacts
• Amazon Redshift: Data warehousing for analytics and ML training
• AWS Glue: Serverless data integration and ETL (Extract, Transform, Load) service
• Amazon Kinesis: Real-time data streaming for ML applications
• AWS Lake Formation: Build, secure, and manage data lakes for ML

Layer 2: Machine Learning Platform Layer (Bedrock)

Purpose: Hosts Amazon’s in-house Foundation models as well as APIs to access partners’ models

·       Amazon Foundation Models: Amazon has Nova family of Foundation models to cater to a variety of needs

o   Nova Pro: Designed for complex, multi-step tasks, offering top-tier performance for reasoning and understanding

o   Nova Lite: An efficient, fast, and cost-effective model suitable for text, image, and video tasks

o   Nova Micro: An extremely fast and lightweight model focused on high-throughput, low-latency text tasks

o   Nova 2 Omni (Preview): A multimodal reasoning model capable of processing text, images, video, and speech, while natively generating text and images

o   Nova Reel: Dedicated to generating short video content, including the ability to take reference images to guide video creation

o   Nova Canvas: Generates images and offers editing capabilities

o   Nova Act: Foundation model that interacts with UIs: clicks buttons, fills forms, navigates apps - ideal for legacy system automation

• AWS IoT Greengrass: Run ML models locally on edge devices
• AWS Panorama: Computer vision at the edge
• AWS Outposts: Run AWS infrastructure on-premises for low-latency ML

Layer 3a: Tools for Builders’ Layer

Purpose: Tools for building custom ML models and workflows

• SageMaker Studio: Integrated development environment (IDE) for ML
• SageMaker Autopilot: Automated model building
• SageMaker JumpStart: Pre-built models and solutions
• SageMaker Pipelines: Orchestrate ML workflows
• SageMaker Feature Store: Central repository for ML features
• SageMaker Clarify: Detect bias and explain model predictions
• SageMaker Edge Manager: Deploy models to edge devices
• AWS Deep Learning AMIs: Pre-configured environments for deep learning frameworks (TensorFlow, PyTorch, etc.)
• AWS Deep Learning Containers: Docker images for deep learning

Layer 3b: AI Application Layer

Purpose: Provide pre-build plug-n-play AI APIs for ML workloads

• Amazon Rekognition: Image and video analysis (e.g., object detection, facial recognition)
• Amazon Polly: Text-to-speech service
• Amazon Lex: Build conversational interfaces (chatbots, voice assistants)
• Amazon Comprehend: Natural language processing (NLP) for text analysis
• Amazon Forecast: Time-series forecasting
• Amazon Personalize: Real-time personalized recommendations
• Amazon Textract: Extract text and data from documents
• Amazon Transcribe: Automatic speech recognition
• Amazon Translate: Language translation
• Amazon Forecast: Time-series forecasting for demand planning, inventory optimization, etc.
• Amazon Fraud Detector: Fraud prevention for transaction risk scoring, account takeover detection
• Q Developer: Assistant for developers, acts as a pair programmer, helping write, debug, and upgrade code (including complex tasks like migrating legacy Java code). Amongst its capabilities include coding suggestions and security scanning.
• Q Business: Ingests data from 40+ systems like Amazon S3 and Salesforce to help build “Q Apps” for sales, lawyers etc. to perform Q&A to help users get answers to their questions, provide summaries, generate content, and securely complete tasks based on data and information in their enterprise systems.

Users can also use Amazon Q Apps to generate apps in a single step from their conversation with or by describing their requirements.

• Q in QuickSight: Natural language BI for asking questions about data

 

Which Layer Should You Use?

 

Requirement	Layer	Key Service
I want to build a custom LLM from scratch	Tools for Builders’ Layer	SageMaker
I want to build an AI agent for my app	Machine Learning Platform Layer	Bedrock
I need an AI to help my employees work faster	AI Applications Layer	Amazon Q