Jul 08, 2026

What do we build now? — Theo Browne, @t3dotgg

Theo Browne's keynote from AIEWF2026 urges software engineers to fundamentally change product development in response to rapidly evolving AI models (Sonnet 3.5 to Mythos). He advocates for rejecting legacy mental models and tools (skeuomorphism), embracing a new "Markdown tier" for projects, and thinking "wider" instead of just "deeper" by building extensible platforms that can challenge industry giants. The core message is to be more ambitious, as AI has drastically lowered the barrier to entry for complex, broad-reaching solutions.

Jul 08, 2026

Automate Workflows w/ Autonomous Tools Real-Time AI Agents | Aytekin Tank | Founder & CEO | Jotform

Aytekin Tank, Founder and CEO of Jotform, discusses how AI is revolutionizing software development and customer support, highlighting "vibe coding" and Jotform's 80% AI-handled support with zero layoffs. He also shares his "Theory of Constraints" playbook for scaling businesses and explores the potential of ChatGPT apps, all within Jotform's 20-year bootstrapped journey.

Jul 07, 2026

How we taught agents to use good retrieval - Hanna Lichtenberg, Mixedbread AI

Mixedbread AI addresses the "Oracle Gap" – the disparity between LLM reasoning and retrieval capabilities – by developing agents trained to use advanced search tools effectively. They demonstrate how current LLMs generate poor queries due to training biases and introduce a sophisticated agent harness with diverse search tools and a unique training regimen, including supervised fine-tuning and reinforcement learning with custom rewards, to teach agents to form precise semantic queries. This approach significantly improves performance on benchmarks like Oblique Congress and Snowflake's Match QA, closing the gap between theoretical perfect retrieval and real-world agent performance.

Jul 06, 2026

Field Guide to Fable — Thariq Shihipar, Anthropic

Thariq Shihipar from Anthropic introduces Fable, their newest model, as a major leap forward, emphasizing "capability overhang" where tool use unlocks unprecedented intelligence. He provides a "field guide" on working with Fable, discussing evolving prompt engineering, advanced tool interactions (like HTML reports), and strategies for identifying project unknowns. He concludes by challenging the necessity of traditional tradeoffs, advocating for ambitious development that is both good, fast, and cheap, and urging AI engineers to prove the transformative power of AI.

Jul 06, 2026

What Is AI Code Refactoring? Agentic AI & Safe Code Changes

This video explores AI code refactoring, differentiating between inline and autonomous agentic approaches. It highlights how AI can leverage pattern recognition for tasks like improving readability or reducing duplication, thereby addressing technical debt. A key focus is on the safety guardrails, detailing a multi-step, human-in-the-loop process involving planning, searching, reporting, human approval, patching, and verification through testing, ensuring AI-driven changes are safe for production and can integrate into CI/CD pipelines.

Jun 28, 2026

Building an Autonomous Engineering Org - Angie Jones, Agentic AI Foundation

Angie Jones details Block's journey in transforming its engineering organization into an autonomous one using AI agents. She outlines a five-stage AI maturity model, the strategic implementation of an 'AI Champions' program, and the technical steps taken to make repositories AI-ready and enable seamless agent delegation directly within developer workflows. The talk covers challenges in scaling multi-agent parallelism, including code review bottlenecks and resource management, and the development of an orchestrator ('Builder Bot') and 'Company World Model' to achieve full autonomy. It concludes with a critical reflection on the ethical implications of achieving such high levels of AI-driven automation.