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In this issue:

  • 🤿Deep Dive: Amazon is putting $1 billion behind a team that embeds directly with enterprise clients

  • 🤝Powered by: What's next for audience growth?

  • 🤿Deep Dive: Cognition releases a multi-model coding harness that cuts costs by 35% without losing frontier-level performance

  • Tool Snapshots: Tools for AI, no-code, and productivity

  • 🖼AI Art: Examples of great and trending AI art

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🤿 DEEP DIVE

Amazon Joins OpenAI and Anthropic in the Race to Put Its Own Engineers Inside Enterprise Clients

Intelligence: AWS is standing up a dedicated team of forward-deployed engineers who will embed directly inside companies to build and deploy AI agents, committing $1 billion in internal resources to the effort.

  • The idea is that these engineers do not just build a system and leave. Companies walk away with the agents running in their own AWS environment and enough internal knowledge to keep improving things on their own.

  • This model was popularized by Palantir and has been picking up steam across the AI industry. OpenAI and Anthropic both launched their own versions in recent months, valued at $4 billion and $1.5 billion respectively, both backed by private equity partners.

  • The appeal for enterprise clients is that someone else takes on primary responsibility for making the deployment actually work, and the technology can be reused and adapted across different companies without starting from scratch each time.

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🤿 DEEP DIVE

Cognition's Devin Fusion Uses a Sidekick Approach to Route Between AI Models Mid-Task, Keeping Quality High While Spending Less

Intelligence: Cognition released Devin Fusion, a multi-model coding system that runs a powerful frontier model alongside a cheaper sidekick model, cutting costs by 35% while keeping code quality at the same level as using a frontier model alone.

  • The core idea is two agents running in parallel. The frontier model handles the high-stakes decisions like planning, resolving ambiguity, and final review, while the sidekick handles most of the actual execution work at a fraction of the cost.

  • Rather than picking one model at the start and sticking with it, Devin Fusion uses lightweight classifiers during the session to detect when the task needs a smarter model or when the sidekick can take back over, switching models at natural break points to avoid extra costs.

  • When tested with Fable 5 specifically, the cost savings jumped to 41%, and Cognition believes that gap will keep growing as frontier models get better at delegating work intelligently.

  • In internal testing, 88% of merged pull requests were driven entirely by the automated Fusion router, which is a fairly strong signal that the system holds up in real engineering work and not just on benchmarks.

TOOL SNAPSHOTS

Futuristic tools within AI, no-code, and productivity

  • 📅 Akiflow - Organize tasks, calendars, and time blocks in one productivity hub.

  • 📧 Supafax - Let AI organize your inbox, draft replies, and schedule meetings for you.

  • 🧠 PMB - Give your AI coding tools persistent project memory that stays local.

  • 📊 Skills Marketplace by Databox - Turn live business data into ready-to-share reports in minutes.

  • 🔤 Tinkerfont - Preview and test fonts on any website without changing the code.

🖼 AI ART

Examples of great and trending AI art

Image by NaturalCrits

ℹ️ ABOUT US

The Intelligent Worker helps you to be more productive at work with AI, automation, no-code, and other technologies.

We like real, practical, and tangible use-cases and hate hand-wavy, theoretical, and abstract concepts that don’t drive real-world outcomes.

Our mission is to empower individuals, boost their productivity, and future-proof their careers.

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