Always Bet on the Models: How Tasklet Puts the Agency in Agents, with CEO Andrew Lee

**Stephen Johnson** (0:00)
This podcast is supported by Google. Hey folks, Stephen Johnson here, co-founder of Notebook LM. As an author, I've always been obsessed with how software could help organize ideas and make connections. So we built Notebook LM as an AI-first tool for anyone trying to make sense of complex information. Upload your documents and Notebook LM instantly becomes your personal expert on covering insights and helping you brainstorm. Try it at notebooklm.google.com.

**Nathan Labenz** (0:31)
Hello, and welcome back to The Cognitive Revolution. Today, I'm excited to welcome Andrew Lee back for his third appearance on the podcast. Our last two episodes together were about Andrew's AI email assistant product, Shortwave. And while Shortwave does remain one of the few AI apps that I use daily on both laptop and phone, the occasion for this conversation is the launch of Task Lit, a new AI agent platform that combines the natural language interaction and open-ended nature of chatbot assistance with the goal orientation and tangible output of automation software, and which has Andrew and team even more excited. In practical, user-experienced terms, Task Lit invites you to describe a task or responsibility to automate, and then figures out for itself how to do it. As its boss, you can then review its output or its full step-by-step process and offer feedback to guide its improvement going forward.
I'm honored and grateful to say that Andrew will be sponsoring The Cognitive Revolution to help support Task Lit's launch. And while we will always be transparent about any financial relationship with guests, whether that's sponsorship, investment, or otherwise, I can sincerely say that we are making no compromises on content quality. In fact, Andrew's belief that speed is the only moat for AI startups, and his resulting willingness to share everything he's learned with remarkable transparency and technical depth have made him a consistent favorite guest among AI engineers. What's more, having tested Tasklet myself for a full month before launch, I can honestly say that it's much more like the aging experience that I had expected OpenAI to launch at their Dev Day than what they actually did launch. And because it delivers frontier capabilities in a radically accessible form factor, I recommend it both to people who are just getting started with AI automation, and also to experienced AI engineers who want to experiment with new concepts and are open to the AI's own ideas for how to get the job done. In this conversation, we explore every angle of how Andrew and team are building Task Lit. We discuss Andrew's plan to always bet on the models, and why he believes that open-ended, agentic systems will ultimately prove more reliable than traditional step-by-step automation software. Task Lit's two-tier architecture, which uses high-level agents to maintain instructions and spawn sub-agents for individual runs, and how this enables both recurring automation and ad-hoc assistance. Real-world use cases, ranging from email triage and marketing automation, to commodity trading and venue management. How Task Lit manages context across long-running agent relationships, including sophisticated approaches to memory, context compaction, and the use of SQL databases to store agent state. Their tool integration strategy, which combines more than 3,000 pre-built integrations with the model's own native ability to figure out how to use MCPs and previously unseen APIs, plus computer use as the final fallback. Fascinating technical details on prompt engineering, including why they're moving away from pre-generated instructions and toward just-in-time instructions to avoid conflicting directives. Why Andrew still runs Task Lit on vibes rather than evals for model selection, and why he's confident that Anthropix models remain the best choice for multi-turn agent interactions. And finally, his perspective on AI's overall trajectory, which I'd say represents the mainline view among both Frontier Lab employees and the most connected app builders. Namely, that progress has not faltered and is absolutely expected to continue for some time to come. To me, while the capabilities frontier remains jagged, and today's models can of course only handle a couple hours of work at a time, Task Lit does feel like a preview of the virtual employee future. When you can maintain an ongoing relationship with an agent, give it high-level feedback on its work, and watch it incorporate that feedback into future runs, you start to experience something genuinely new. And Andrew's report that some users are already giving their Task Lit agents their own dedicated email addresses, and in some cases even names, suggests that this paradigm shift is indeed already beginning. If you're intrigued, and certainly if you listen to this episode, I think you will be, Andrew invites you to try Task Lit for free at tasklit.ai. And then, when it's time to upgrade, use code Cogrev to get 50% off of any paid plan. With that, I hope you enjoy this deep dive into the strategic thinking, product management, and technical implementation of a frontier AI agent platform, with Andrew Lee, founder and CEO of Task Lit. Andrew Lee, founder and CEO of Shortwave, and now also founder and CEO of Task Lit. Welcome back to The Cognitive Revolution.