Software engineering

From coding to Knowledge work agents — Karan Vaidya, Composio

From coding to Knowledge work agents — Karan Vaidya, Composio

Karan Vaidya of Composio explains why AI agents have excelled in software engineering but struggle in other knowledge work domains. He identifies six critical primitives—centralization, history, context, verification, governance, and reversibility—that coding inherently provides but are largely absent in general knowledge work, hindering agent effectiveness and trust. The current bottleneck for AI agents is not the models, but the missing infrastructure around them.

Why Your Agent Evals Are Missing the Real Failures (with Aishwarya Srinivasan)

Why Your Agent Evals Are Missing the Real Failures (with Aishwarya Srinivasan)

Aishwarya Srinivasan, co-founder of The Gen Academy, discusses the shift in AI and software engineering, highlighting how "cheap code" necessitates strong engineering judgment and a "whole-system eval" approach for agentic AI. She explains the resurgence of reinforcement learning for fine-tuning, the evolution from prompt to loop engineering, and introduces her MIND framework for living with AI. Srinivasan emphasizes experimentation as the most critical career skill and offers insights into what differentiates successful AI startups in today's competitive landscape.

How Anthropic Builds: Lessons from Labs — Mike Krieger, Anthropic

How Anthropic Builds: Lessons from Labs — Mike Krieger, Anthropic

Mike Krieger, a former CPO at Anthropic, details his transition to an IC role to build directly with AI, advocating for "unreasonable" asks like porting entire codebases. He shares lessons from Instagram on scaling and highlights Anthropic's internal use of Claude as a proactive teammate, flexible lab structure, and critical insights on AI product design, vertical applications, and mental health in the fast-paced AI industry.

How to build an AI-Native Health Company — Dan Feng, Maven Clinic

How to build an AI-Native Health Company — Dan Feng, Maven Clinic

Dan Feng outlines Maven Clinic's transformation into an AI-native company, driven by the realization that "building is cheap and arguing is expensive" in the AI era. This shift has reshaped planning to short, iterative sprints, revolutionized software development with AI coding tools, forced adaptive changes in code review processes, and necessitated a nuanced, multi-layered approach to ensuring reliability in generative AI systems.

How to Kill the Code Review — Ankit Jain, Aviator

How to Kill the Code Review — Ankit Jain, Aviator

Ankit Jain argues that traditional line-by-line code review is defunct, with AI reviewing code that humans no longer read. He asserts that code review's vital, often overlooked, purpose is 'alignment'—knowledge sharing, mentorship, and architectural feedback—which current AI-driven workflows fail to capture. His proposal involves capturing user-AI interaction prompts as acceptance criteria, generating test plans with an 'AI Slop Registry' (codified recurring review comments), and verifying changes against live previews. The new review surface becomes the 'intent and evidence' rather than the code diff, preserving collaboration and ensuring semantic accuracy.

Circleback CEO Ali Haghani: Recording Company Meetings Will Become The Norm

Circleback CEO Ali Haghani: Recording Company Meetings Will Become The Norm

Ali Haghani, co-founder of CircleBack, shares his unique hardware setup and delves into how his AI notetaker streamlines business operations, from interview tracking to customer support. He discusses the shift from manual coding to AI-orchestrated development, the nuances of prompt engineering, and his vision for why recording meetings with AI is becoming essential for leveraging LLMs and agents effectively in enterprises, ultimately reshaping the future of software engineering.