Dillon Mulroy, Rhys Sullivan, and Sunil Pai record The Next Token at AI Engineer World’s Fair. Their central request is simple: let a customer’s existing agent use the product well. The Cloudflare-sponsored episode was recorded June 30, 2026.

Long conversations complicate model comparisons

  • 5:48 — Available alternatives matter. The hosts discuss open-weight models and challenge claims of matching a model customers cannot access for comparison.
  • Their news segment reports restrictions on Fable and GPT-5.6 as part of the recording-time discussion of model access.
  • 8:06 — Compaction gets different reviews. Rhys reports good results after old context is shortened. Dillon sees degradation. Sunil likes Cursor’s handling. Their tool-specific experiences do not establish one universal limit.
  • 10:25 — “Moo” makes instruction loss visible. Dillon describes asking a model to end every reply with the word. Losing it is a simple adherence warning, not a complete intelligence test.
  • 13:17 — Generated types can reveal weak design. Dillon dislikes broad inputs followed by scattered validation. He prefers parsing data at a boundary and carrying a clear domain type afterward.

Make the product useful to the agent people already trust

  • 23:11 — Keep the user’s context together. Dillon prefers one chosen agent connected to services over a separate assistant in every dashboard.
  • 24:45 — The underlying product still needs value. Another agent announcement does little if the service fails to improve a real workflow.
  • 26:14 — Cross-product work needs identities and permissions. Rhys imagines a review bot checking historical observability data to understand a pull request’s impact.
  • 26:45 — Embedded agents still have an audience. Many customers lack a personal agent. A dashboard helper can serve them while the same capabilities remain available externally.

Share tools, skills, and the company’s expertise

  • 28:36 — Expose the complete documented API. An API is the product’s callable interface. Rhys also wants discoverable authentication and user involvement for destructive actions.
  • 29:10 — Package common workflows. A front end often prepares data and chains calls. MCP, a standard connecting agents to tools, can expose that procedural knowledge.
  • 30:17 — Use one source of truth. A company’s agent should use the same tools and skills it gives customers. A polished private shortcut proves little about external usability.
  • 30:36 — Evaluate the product through its own agent. Dillon says Cloudflare watches where its agent struggles, then improves shared documentation and skills. That can benefit every caller.
  • 43:03 — Endpoints are only part of the knowledge. Analytics guidance, search expertise, and product practices should travel with the integration rather than remain trapped in a dashboard.

Stable primitives need good documentation and errors

  • 32:29 — Lenny Pruss’s essay supplies the frame. A few stable capabilities can be easier for agents to compose than a growing collection of prescriptive features.
  • 33:47 — Shipping can reveal the right foundation. Rhys describes getting stuck while trying to design perfect primitives for Executor. Actual use clarified what to build.
  • 37:40 — Put docs where the work happens. Bundled documentation and self-explaining command-line tools reduce guessing about names, options, and versions.
  • 38:53 — Code mode changes the middle layer. Letting an agent write code against an interface may reduce tool-description overhead. The documented API underneath still matters.
  • 40:19 — Errors should explain the next action. Missing context forces more guesses and retries. A useful error helps a human or agent recover.
  • 41:27 — Start with data access patterns. Dillon warns that a weak database foundation can require months of migration even when code changes are cheap.

Agents change the economics of access

  • 14:10 — Security teams face the same choice as developers. Agents can replace staff or help existing staff inspect logs and threats. The hosts’ PlanetScale discussion leaves that organizational choice open.
  • 16:03 — Safety policy needs proportionate boundaries. Rhys considers temporary defensive lead time reasonable. Dillon asks for expert evaluation, transparency, and scientific rigor.
  • 21:08 — Data terms can block adoption. Their spontaneous discussion of zero data retention is uncertain. Enterprises need to check the actual retention and training policies separately.
  • 44:00 — Vendors may resist losing the interface. The user’s agent can weaken branding and lock-in. The hosts expect pricing and access rules to respond.
  • 45:05 — GPUs are only one bottleneck. More API requests also pressure CPUs, storage, and rate limits. Their rough GitHub usage multiplier is not a current measurement.

Extract a loop from a practice that already works

  • 45:33 — A stable harness reduces extra variation. The harness is the software running a model’s tools and context. Dillon values Pi’s small, predictable base.
  • 48:39 — Separate review from an entire software factory. The hosts use Armin Ronacher’s The Coming Loop to ask how humans retain responsibility as automation expands.
  • 50:27 — Encode repeated review feedback. Dillon proposes skills for recurring design mistakes, then a queued first-pass reviewer before his own review. He does not claim the experiment is proven.
  • 52:14 — Small checks can work without a whole-product vision. Rhys’s optimistic-update example shows a bounded rule that a model can inspect. Stacking such checks creates his “house of inference.”
  • 53:35 — IKEA is the tradeoff metaphor. More people may get useful software even when experts dislike its craftsmanship. Technical debt still affects whether the product can keep improving.
  • 58:35 — Start with consistency. Once the same successful correction recurs almost word for word, it becomes a candidate for automation.

Remote agents need runnable environments and sustainable users

  • 59:32 — Moving off laptops is a tooling forecast. It need not mean a new level of autonomy. Local files, login flows, development servers, and previews still have to work.
  • 1:01:32 — Emulation removes a real blocker. Rhys describes an agent making a WorkOS substitute so the app can run without the same environment-variable setup.
  • 1:03:05 — Team roles remain unsettled. Dillon proposes “software gardening”: first-pass implementation followed by senior attention to reliability and design. The others challenge a fixed five-role taxonomy.
  • 1:07:35 — Hosted features could become the lock-in. Dillon predicts providers will move valuable capabilities behind APIs as models become less distinctive. This is his forecast, not an announced roadmap.
  • 1:09:34 — Easier attempts can mean longer days. The hosts describe pushing through exhaustion and wanting to send one more prompt. Rhys compares each attempt to a slot-machine spin.

“Do not start at the position of trying to build an automated software factory.” — Dillon Mulroy, 58:35–58:43.