Whisperflow

Chat and citations won't save your vertical AI - Atul Ramachandran, Filed Inc

Jul 11, 2026 · 15:12

Atul Ramachandran, CTO and co-founder at Filed, argues that chat interfaces and citation trails fail vertical AI because they shift the verification burden back to users, making every error catastrophic. Drawing from Filed's work building AI data entry for tax firms—where they hit 80%+ accuracy against a 50-60% baseline yet still faced complaints—he explains that the real fix is to design for delegation, not participation. He proposes treating the product as a conveyor belt where users are supervisors, using long-running background agents, automatic skills that capture user quirks, monitoring via traces, and control mechanisms like plan approval before irreversible actions. Ramachandran advocates measuring weekly active sessions instead of weekly active users, aiming for sessions to rise while direct user interaction falls. The episode covers these four pillars and the shift in metrics needed to build successful vertical AI products.

The Agentic AI Engineer - Benedikt Sanftl, Mutagent

Jun 29, 2026 · 34:50

Benedikt Sanftl and Burak of Mutagent introduce the Agentic AI Engineer, an automated loop that builds, evaluates, and optimizes AI agents at scale. They argue the human bottleneck in manually iterating on agent prompts, evaluations, and diagnostics can be removed by using an orchestrator that manages spec-driven development, eval-driven testing, and online monitoring. The offline loop covers spec, build, and eval; the online loop monitors traces, diagnoses failures, and feeds improvements back into the system. They demo two research-preview agents: an evaluator that constructs eval suites and a diagnostics agent that analyzes production traces to suggest targeted fixes. The platform connects to observability tools and target frameworks (e.g., Claude Code, LangChain) and outputs PRs or updated agent definitions. The core claim is that automating this lifecycle enables teams to ship and improve hundreds of agents with faster iteration and less manual effort.

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

Dec 18, 2025 · 17:58

In this episode, Dan Shipper of Every argues that there is a 10x difference between an organization where 90% of engineers use AI and one where 100% do. At Every, 99% of code is written by AI agents, enabling 15 people to run four software products with 7,000 paying subscribers, each built by a single developer. Shipper introduces 'Compounding Engineering', where each feature makes the next easier to build through a loop of plan, delegate, assess, and codify. He describes how this approach allows managers to commit code, enables tacit code sharing across products, and lets new hires be productive on day one. The episode details how Every's shift to agentic workflows (Claude Code, Codex) and a 'demo culture' over 'memo culture' has transformed their engineering velocity and collaboration.