🤖 AI Engineering - Prompt Engineering | Drishtant Ghosh (Drix10)

🤖 AI Engineering - Prompt Engineering

Prompt engineering is a crucial aspect of reliable AI, but it's not the only factor. Great prompts help, but production-ready AI needs context, retrieval, memory, tools, and evaluation too.

Key Points:

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Contextual Understanding: AI models require context to understand the nuances of human language and provide accurate responses.
Retrieval and Memory: AI models need to be able to retrieve and store information to provide accurate and relevant responses.
Tools and Evaluation: AI models require tools and evaluation metrics to assess their performance and identify areas for improvement.
Actionable Takeaway: Developers and technical founders should focus on building comprehensive AI systems that incorporate multiple factors, including context, retrieval, memory, tools, and evaluation.

🔗 Resources:

📚 Research and Development

I started formally writing up some of the research I've been doing over the last few months. One of my blog posts in the next few days will talk about one aspect of it. I did want to highlight this one paper as during my research I came across it, and I found it illuminating.

Key Points:

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Research and Development: Research and development are essential for advancing knowledge and improving technologies.
Highlighting Papers: Highlighting papers can help others learn from research and development efforts.
Actionable Takeaway: Researchers and developers should share their findings and highlight papers to advance knowledge and improve technologies.

🧬 Proteolytic Activation

One of the answers might be in this paper from 2026: Non-canonical proteolytic activation of RNase L by SARS-CoV-2 3CLpro offsets inactivation of OAS1 p46 antiviral signaling. It turns out these authors showed that SARS-CoV-2's main protease, Mpro, can inadvertently cause RNase.

Key Points:

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Proteolytic Activation: Proteolytic activation is a process by which proteins are activated through the action of enzymes.
RNase L: RNase L is an enzyme that plays a crucial role in the antiviral response.
Actionable Takeaway: Understanding proteolytic activation and its role in antiviral signaling is essential for developing effective treatments for viral infections.

📰 The Hugging Face Hack

From @WSJopinion: The Hugging Face hack wasn’t what it was cracked up to be. Forget the “hive mind” of AI agents “going rogue.” They did what humans programmed them to do, writes Brian Gross.

Key Points:

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The Hugging Face Hack: The Hugging Face hack refers to a series of incidents where AI models were used to generate malicious content.
AI Agents: AI agents are programs that can perform tasks on their own, but they are still controlled by humans.
Actionable Takeaway: Understanding the limitations and capabilities of AI agents is essential for developing effective AI systems.

🚀 Git Platform

A Git platform where agents actually ship. Start an agent in an isolated cloud workspace, assign a task, and it writes code, runs tests, and opens the PR. Run long running tasks directly from your repos. Congrats to @stylessh for launching this.

Key Points:

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Git Platform: A Git platform is a system that allows developers to manage and collaborate on code.
Agents: Agents are programs that can perform tasks on their own, but they are still controlled by humans.
Actionable Takeaway: Understanding the capabilities and limitations of agents is essential for developing effective AI systems.

🤖 Jev vs GLM

Jev vs GLM 5.3 at chess! Results: GLM 5.3 won by checkmate in 29 moves Jev: ~0.3s and <$0.0001 per move GLM 5.3: ~5.8s and ~$0.008 per move The whole game cost 24 cents My main takeaway is that it's often useful to use each one to their strengths: Fast, efficient, and cheap.

Key Points:

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Jev vs GLM: Jev and GLM are two AI models that can play chess.
Chess Game: The chess game was played between Jev and GLM 5.3.
Actionable Takeaway: Understanding the strengths and weaknesses of different AI models is essential for developing effective AI systems.

📱 AsyncImage

iOS 27 gives AsyncImage more control over remote image loading with URLRequest support for custom headers, cache policies, and timeouts, plus the ability to provide a custom URLSession across a SwiftUI view hierarchy:

Key Points:

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AsyncImage: AsyncImage is a feature in iOS that allows for asynchronous image loading.
URLRequest: URLRequest is a class that allows for custom headers, cache policies, and timeouts.
Actionable Takeaway: Understanding the capabilities and limitations of AsyncImage is essential for developing effective iOS apps.

🚀 Flue 2.1

Flue 2.1 is out, coming at you: • Per-tool timeouts • MCP tool annotations • Configurable trace content budgets • React sendMessage() now supports idempotency and returns an admission receipt Changelogs:

Key Points:

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Flue 2.1: Flue 2.1 is a new version of the Flue platform.
Per-tool timeouts: Per-tool timeouts allow for more fine-grained control over tool execution.
Actionable Takeaway: Understanding the capabilities and limitations of Flue 2.1 is essential for developing effective AI systems.