AI Engineer Creator Profile

Jack Morris: Stuffing Context is not Memory, Updating Weights is

AI Engineer December 29, 2025

Understanding how memory works in large language models through the lens of weights and activations. This workshop will explore the …

AGI: The Path Forward – Jason Warner & Eiso Kant, Poolside

AI Engineer December 27, 2025

In Poolside's first ever public conference demo, Poolside's CEOs present their vision and roadmap towards achieving AGI-level capabilities for knowledge …

Shipping AI That Works: An Evaluation Framework for PMs – Aman Khan, Arize

AI Engineer December 26, 2025

GenAI is reshaping the product landscape, creating huge opportunities (along with new expectations) for product managers. Yet while prompt engineering …

How Claude Code Works - Jared Zoneraich, PromptLayer

AI Engineer December 26, 2025

Deep dive into what we have independently figured out about the architecture and implementation of Claude's code generation capabilities. Not …

Why Agent Hype can fall short of reality – Joel Becker, METR

AI Engineer December 24, 2025

AI models are crushing benchmarks. SWE-bench scores are climbing, and METR's measured time horizons are rising rapidly. Yet when we …

Small Bets, Big Impact Building GenBI at a Fortune 100 – Asaf Bord, Northwestern Mutual

AI Engineer December 23, 2025

Enterprises don’t usually make moonshots, especially in GenAI. Governance, budgets, and risk aversion make it almost impossible to justify a …

Developer Experience in the Age of AI Coding Agents – Max Kanat-Alexander, Capital One

AI Engineer December 23, 2025

It feels like every two weeks, the world of software engineering is being turned on its head. Are there any …

The Unreasonable Effectiveness of Prompt Learning – Aparna Dhinakaran, Arize

AI Engineer December 23, 2025

Your coding agent writes code—but not like your team. RL has boosted base models, but it’s opaque and hard to …

Making Codebases Agent Ready – Eno Reyes, Factory AI

AI Engineer December 22, 2025

Agents are eating software engineering. Yet teams deploying these tools face mixed results. Agents work great in demos but fail …

Amp Code: Next Generation AI Coding – Beyang Liu, Amp Code

AI Engineer December 22, 2025

Introduction to Amp Code and its approach to AI-powered software development. Speaker: Beyang Liu | Co-founder & CTO, Amp Code …

The 3 Pillars of Autonomy – Michele Catasta, Replit

AI Engineer December 22, 2025

AI agents exhibit vastly different degrees of autonomy. Yet, the ability to accomplish objectives without supervision is the critical north …

From Arc to Dia: Lessons learned building AI Browsers – Samir Mody, The Browser Company of New York

AI Engineer December 19, 2025

What happens when you take a polished, beloved browser and rebuild it from the ground up around AI? In 2024, …

Leadership in AI Assisted Engineering – Justin Reock, DX (acq. Atlassian)

AI Engineer December 19, 2025

To realize meaningful returns on AI investments, leadership must take accountability and ownership of establishing best practices, enabling engineers, measuring …

Dispatch from the Future: building an AI-native Company – Dan Shipper, Every, AI & I

AI Engineer December 18, 2025

The central thesis is that there is a "10x difference" between an organization where 90% of engineers use AI versus …

AI Consulting in Practice – NLW, Superintelligent, @AIDailyBrief⁩

AI Engineer December 18, 2025

Insights from consulting on AI implementation across various organizations. Speaker: NLW | Host, AI Daily Brief & CEO, Super.ai https://x.com/nlw …

Code World Model: Building World Models for Computation – Jacob Kahn, FAIR Meta

AI Engineer December 17, 2025

Today, most neural models for code learn from code itself: sequences of tokens that capture syntax rather than computation. While …

AI Kernel Generation: What's working, what's not, what's next – Natalie Serrino, Gimlet Labs

AI Engineer December 17, 2025

In this talk, we'll talk about how AI generated kernels can meaningfully speed up custom PyTorch code, without any human …

What We Learned Deploying AI within Bloomberg’s Engineering Organization – Lei Zhang, Bloomberg

AI Engineer December 16, 2025

When it comes to using AI for software engineering, much of the spotlight falls on how large language models (LLMs) …

Building in the Gemini Era – Kat Kampf & Ammaar Reshi, Google DeepMind

AI Engineer December 15, 2025

A deep dive into the latest capabilities of Google DeepMind's Gemini 3 and the newly released "Nano Banana Pro" image …

Coding Evals: From Code Snippets to Codebases – Naman Jain, Cursor

AI Engineer December 15, 2025

AI coding capabilities have leapt from generating one-line snippets to competing entire codebases with agentic workflows. I’ll trace that arc …

Minimax M2: Building the #1 Open Model – Olive Song, MiniMax

AI Engineer December 13, 2025

Introducing Minimax's latest AI model and its applications in code generation. Speaker: Olive Song | Senior Researcher, MiniMax https://x.com/olive_jy_song

Hard Won Lessons from Building Effective AI Coding Agents – Nik Pash, Cline

AI Engineer December 12, 2025

Most of what’s written about AI agents sounds great in theory — until you try to make them work in …

The State of AI Code Quality: Hype vs Reality — Itamar Friedman, Qodo

AI Engineer December 11, 2025

AI is making code generation nearly effortless, but the critical question remains: can we trust AI-generated code for software that …

Can you prove AI ROI in Software Eng? (Stanford 120k Devs Study) – Yegor Denisov-Blanch, Stanford

AI Engineer December 11, 2025

You’re investing millions in AI for software engineering. Can you prove it’s paying off? Benchmarks show models can write code, …

AI Engineer

Jack Morris: Stuffing Context is not Memory, Updating Weights is

AGI: The Path Forward – Jason Warner & Eiso Kant, Poolside

Shipping AI That Works: An Evaluation Framework for PMs – Aman Khan, Arize

How Claude Code Works - Jared Zoneraich, PromptLayer

Why Agent Hype can fall short of reality – Joel Becker, METR

Small Bets, Big Impact Building GenBI at a Fortune 100 – Asaf Bord, Northwestern Mutual

Developer Experience in the Age of AI Coding Agents – Max Kanat-Alexander, Capital One

The Unreasonable Effectiveness of Prompt Learning – Aparna Dhinakaran, Arize

Making Codebases Agent Ready – Eno Reyes, Factory AI

Amp Code: Next Generation AI Coding – Beyang Liu, Amp Code

The 3 Pillars of Autonomy – Michele Catasta, Replit

From Arc to Dia: Lessons learned building AI Browsers – Samir Mody, The Browser Company of New York

Leadership in AI Assisted Engineering – Justin Reock, DX (acq. Atlassian)

Dispatch from the Future: building an AI-native Company – Dan Shipper, Every, AI & I

AI Consulting in Practice – NLW, Superintelligent, @AIDailyBrief⁩

Code World Model: Building World Models for Computation – Jacob Kahn, FAIR Meta

AI Kernel Generation: What's working, what's not, what's next – Natalie Serrino, Gimlet Labs

What We Learned Deploying AI within Bloomberg’s Engineering Organization – Lei Zhang, Bloomberg

Building in the Gemini Era – Kat Kampf & Ammaar Reshi, Google DeepMind

Coding Evals: From Code Snippets to Codebases – Naman Jain, Cursor

Minimax M2: Building the #1 Open Model – Olive Song, MiniMax

Hard Won Lessons from Building Effective AI Coding Agents – Nik Pash, Cline

The State of AI Code Quality: Hype vs Reality — Itamar Friedman, Qodo

Can you prove AI ROI in Software Eng? (Stanford 120k Devs Study) – Yegor Denisov-Blanch, Stanford

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