May 04, 2026

Anthropic's Boris Cherny: Why Coding Is Solved, and What Comes Next

Boris Cherny, creator of Claude Code, discusses the future of software development at AI Ascent 2026. He argues that coding is effectively a solved problem, detailing his personal workflow of shipping dozens of PRs daily from his phone. Cherny explores the shift from typeahead to autonomous agents, the rise of cross-disciplinary generalist teams, and uses the printing press as an analogy for the coming democratization of software creation for all.

May 04, 2026

Skill Issue: How We Used AI to Make Agents Actually Good at Supabase — Pedro Rodrigues, Supabase

A deep dive into building, testing, and iterating on Agent Skills to improve AI agent performance. This workshop covers the core concepts of progressive disclosure, eval-driven development, and practical application using a real-world Supabase and PostgreSQL security scenario.

May 04, 2026

CLI vs MCP: How AI Agents Choose the Right Tool for the Job

AI agents can interact with the world through either the Command Line Interface (CLI) or the Model Context Protocol (MCP). This summary explores the trade-offs between the two, highlighting CLI's efficiency for tasks the model is trained on, versus MCP's power of abstraction and governance for more complex, high-level operations.

May 03, 2026

Mergeable by default: Building the context engine to save time and tokens — Peter Werry, Unblocked

A practitioner's guide to building a context engine, the reasoning layer that provides AI agents with the necessary organizational context to generate effective and appropriate code. The talk debunks common myths about RAG and large context windows, outlines core requirements for a robust context engine, and shares lessons learned from production.

May 03, 2026

Context Is the New Code — Patrick Debois, Tessl

Patrick Debois argues that as AI coding agents become more capable, the context that drives them—prompts, rules, and memory—needs its own engineering discipline, akin to how we manage code. He introduces the Context Development Lifecycle (Generate, Evaluate, Distribute, and Observe) to make context a shared, repeatable, and improvable part of software delivery, creating a flywheel effect where better context leads to better agent output and continuous improvement.

May 02, 2026

Software Engineering Is Becoming Plan and Review — Louis Knight-Webb, Vibe Kanban

As AI handles more of the coding, the role of a software engineer is shifting from writing code to planning and reviewing the work of AI agents. This talk explores the implications of this shift, the new workflows it demands, and the tools required to manage them effectively.