How I AI

A product manager describes using GPT-5.6 with Codex to automate video editing for social media clips. By simply dragging a file and providing natural language instructions, the AI generated five polished, fast-paced hype videos from a long conference talk recording, dramatically reducing the time-intensive manual clipping process.

An executive contrasts two AI models (Fable and Soul/GPT-5.6 Sol), arguing that Soul is superior for product work because it prioritizes practical effectiveness over theoretical intelligence. The speaker values the ability to ship products to customers and understand end-user goals over theoretical sophistication.

Building a harness for repetitive workflows allows you to be more prescriptive about job execution, resulting in greater efficiency, consistency, and better outcomes. Rather than explaining requirements to an AI agent each time, a harness lets you use a simpler interface like pasting a link while the agent already understands the intended task.

Claire Vo compares OpenAI's new GPT 5.6 models (Soul, Terra, Luna) against Claude's Fable using her custom "How I AI" benchmark, finding that GPT 5.6 Soul excels at practical product work, prototyping, and natural communication, while Fable is theoretically intelligent but pedantic and difficult to collaborate with.

The speaker highlights context offloading as an underrated AI use case, where AI serves as a safety net for routine cognitive tasks like email management and personal finances. Rather than adding new capabilities, AI reduces anxiety about missing important information or making mistakes by handling monitoring tasks, thereby freeing up mental bandwidth.

A harness is code that wraps around an AI agent to make it more effective. The speaker demonstrates how a harness can automatically investigate production issues by analyzing Sentry warnings, identifying root causes, determining impact, and recommending whether to create tickets or apply fixes.

The speaker discusses the shift from traditional agent prompting to agent management, highlighting the limitations of local Kanban board approaches and advocating for cloud-based VPS solutions with multiple communication channels to effectively manage autonomous AI agents across projects.

A custom AI harness is code wrapped around an AI agent to make it more effective for specific workflows. The speaker demonstrates building a Sentry bug-debugging harness using Claude SDK with a terminal UI, showing how structured constraints, custom prompts, and specific tool adapters enable agents to handle complex tasks more efficiently than general-purpose AI tools.

Alessio Finelli demonstrates how he uses OpenAI's Symphony framework combined with Linear and Codex to run autonomous coding agents from his phone, managing both software engineering tasks and a Pokémon card trading business through cloud-based VPS infrastructure instead of local machines.

The speaker discusses discrepancies between their subjective evaluation of model performance and automated benchmark results, noting that different judges (Opus, 4A, 5.5) show varying levels of generosity and bias. They conclude that personal judgment matters significantly and plan to incorporate more subjective taste into evaluation metrics while retiring saturated benchmark tasks.

The speaker provides task-specific model recommendations across different use cases, suggesting GPT 5.5 for PRDs, Sonnet 4.6 for prototyping and casual interaction, and Opus 4.8 or Sonnet 5 for codebase work. Model selection varies based on complexity, with Opus 4.8 excelling at dense UI design and Sonnet suitable for simpler implementations.

The speaker introduces 'The How I AI Bench,' a new set of human and AI-graded benchmarks designed to evaluate language models on practical tasks like writing PRDs, solving bugs, and designing systems. They test Claude Sonnet 3.5 against these benchmarks and note that while it scores lower than some specialized benchmarks (69% on Agentic Coding SweetBench Pro, 82% on Terminal Bench 2.1), the difference may not be noticeable in real-world usage.

Katie transitioned from designer to top-performing engineer, ranking in the 94th percentile for code throughput across the entire R&D organization. Her success stemmed from technical curiosity combined with supportive engineer mentors who reviewed her code and helped her improve her craft.

A team successfully shipped a project in 10 weeks by eliminating traditional project management structures entirely—no meetings, Jira, documentation, or text communication. Instead, they relied solely on a 24/7 Zoom room where team members could work synchronously and asynchronously as needed.

The speaker discusses how Claude's Co-worker feature helps parents automate tedious online administrative tasks, freeing up time for more meaningful interactions with their children. By handling tasks like returns and help emails, AI removes low-value busywork rather than replacing genuine human experiences.

A parent describes using Claude as a household management and shopping assistant to find high-quality, naturally-made products from reputable brands. They created a project in Claude with specific brand criteria and used it to organize notes and vet brands. A key benefit highlighted was Claude surfacing that a previously reputable brand had declined in quality after a corporate takeover.

Nicole Ruiz demonstrates how she built a Claude project to automate high-quality shopping decisions for her family, using curated brand lists and purchasing criteria to filter out cheap, poorly-made products. She also shows how Claude Computer Use helps her draft return emails by pulling order details directly from her Gmail. The system is designed to reduce the mental overhead of conscious consumption so she can spend more time with her children.

The host demonstrates using Google Flow, a generative AI creative suite, to create a hype video for the 'How I AI' podcast. Using a fish-eye lens avatar of themselves, they generate a storyboard with cinematic shots including keyboard close-ups, office wide shots, and a humorous chair spin with a digital heads-up display overlay.

A person recounts shipping an app to the app store without learning to code, relying primarily on basic computer skills like copying, pasting, and file labeling. She candidly admits she still doesn't understand the underlying software infrastructure, including the deployment platform Railway, even after successfully completing the project.

A creator demonstrates using Google Omni to generate a hype/promo video for their podcast 'How I AI' in under 15 minutes. The resulting video includes music, narration, and a polished promotional script. The creator expresses genuine amazement at the output quality.