Prompt engineering

Aug 28, 2026

How to Get Your Org to Adopt Coding Agents (Without Shipping Garbage) — Eyal Blum, Figma

Figma's internal AI agent adoption journey faces challenges like reduced developer agency, skepticism from senior engineers, and communication inefficiency. Solutions include investing in verification, using a testing pyramid for agent review, prioritizing detailed planning over prompting, engaging skeptics to build AI safety roadmaps, and implementing attention-aware communication by clearly marking AI-generated content.

Aug 28, 2026

CLAUDE.md, AGENTS.md, Skills, Hooks and Subagents: A Field Guide to Steering AI Agents (Ep. 1022)

Episode 1022 dissects the crucial aspect of effectively steering AI agents by determining the optimal placement of instructions to ensure reliability and cost-efficiency. It explores seven distinct methods for instruction delivery, contrasting instructions as probabilities with hooks as guarantees, and highlights the industry-wide adoption of standards like `agents.md` and the importance of human-crafted guidance for superior agent performance.

Aug 25, 2026

⏭️ Forward Deployed: Voice AI on what works in 2026

This podcast episode delves into the pragmatic realities of building and deploying voice agents in enterprise. Featuring leaders from Decagon, Vapi, Retell, Daily, and Smallest AI, the discussion uncovers why the current state-of-the-art relies on cascaded pipelines (STT -> LLM -> TTS) instead of direct voice-to-voice models. Key challenges explored include managing latency versus intelligence, ensuring system reliability through fallback models, the complexities of turn-taking, and architectural strategies to overcome LLM context limitations and optimize costs. The experts also touch upon the differences between inbound and outbound use cases, multilingual considerations, and the potential future of hybrid voice agent architectures.

Aug 22, 2026

FinOps for AI Agents: Who Spent All the Tokens? — Tisha Chawla & Susheem Koul, Microsoft

TokenOps introduces a novel control plane for managing AI agent costs, shifting from simple throttling to proactive steering. By integrating an out-of-band system that annotates agent methods and provides a policy-driven governor, TokenOps can dynamically modify agent behavior—like making outputs more succinct—to reduce token consumption and prevent runaway loops. This approach significantly cuts average spend (78%) and dramatically improves run completion rates (from 67% to 96%) compared to traditional halting mechanisms, offering granular, attributable cost control for the agentic era.

Aug 21, 2026

Building Agents Is Trivial Now, Context Is the Next Frontier — Jeff Ng, Unblocked

Building AI agents is now easier than ever, but they frequently make confident yet incorrect decisions. This is because agents often lack critical context that humans provide, such as historical discussions, postmortems, and tribal knowledge. The solution proposed is a 'context engine' that synthesizes and grounds information from across an organization's documents, code, tickets, and conversations, providing agents with a holistic and reconciled view, thus bridging the 'context gap' that current LLMs often miss.

Aug 20, 2026

Prototyping as Leadership: How a CTO Ships with AI Agents — Hursh Agrawal, The Browser Company

Hursh Agrawal, CTO of The Browser Company, argues that AI agents have transformed the manager's schedule into usable building time. He outlines how leaders, leveraging their deep business context, can utilize an overnight loop with AI coding agents to ship features, optimize AI models, and even train custom classifiers, which is critical for staying calibrated with rapidly evolving frontier models and effectively communicating new product possibilities.