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Bio, Work & Ideas

Rick Blalock

Conference affiliation: Agentuity · 2025

Rick Blalock is a co-founder of Agentuity, which builds an agent-native cloud for autonomous software that maintains context, coordinates with other agents, and operates beyond conventional serverless limits. His earlier career included mobile developer infrastructure, founding a fisheries-technology company, product leadership after its acquisition, and building AI systems for qualitative customer research.

From mobile platforms to autonomous agents

Blalock worked on the mobile developer platform Appcelerator alongside future Agentuity co-founder Jeff Haynie, pursued cloud work at IBM, and later became a principal engineer at Pinpoint. His public software projects include Titanium and Node.js tooling and an IBM Watson-powered museum-guide prototype.

In 2011, Blalock and Albrey Arrington founded Fish Rules, a mobile application translating location-specific fishing regulations into practical guidance for anglers. Fishbrain acquired Fish Rules in 2021, and Blalock subsequently served as Fishbrain’s chief product officer. He also co-authored a 2023 fisheries study examining offshore wind development using recreational-fishing application data.

Blalock later co-founded OneStudy with Kincy Clark to develop AI-assisted qualitative research. Its agents exposed a persistent infrastructure problem: synthesizing customer interviews and other extended work could exceed serverless execution windows. In early 2025, he co-founded Agentuity with Haynie, Matthew Congrove, Robin Diddams, and Bobby Christopher; the company launched with $4 million in seed funding.

  • Long-running, stateful agent infrastructure. Blalock treats agents as infrastructure-level entities requiring durable execution, memory, inter-agent communication, independent routing, access controls, and configurable email, API, or scheduled triggers. His deployment demonstration shows Bun, Node.js, and Python interoperability, framework-agnostic development, cost visibility, and a crucial distinction between traces readable by human operators and observability agents can use to assess themselves.
  • Agent-native organizational design. Blalock argues that autonomous systems should participate directly in product development, documentation, marketing, and operations, while people retain judgment, approvals, and consequential decisions. His organizational-design writing connects that model to flatter teams, redesigned onboarding, and hiring for practical AI fluency; Agentuity uses Cognition’s Devin as an external coding product.
  • Persistent engineering context. Blalock wants requirements, design conversations, and implementation decisions to remain available to both engineers and coding agents instead of disappearing between meetings, tickets, and pull requests. His work on conversations and code applies that principle across GitHub, Slack, Linear, automated documentation, and software review.
  • Omakase Agent and verifiable agent craftsmanship. His Omakase Agent framework combines specialized execution, independent critique, documented decisions, project preferences, and explicit verification. Agents can act autonomously within an approved scope, while consequential actions remain subject to human authorization.

Read the topics behind these talks

2 conference talks

Key ideas

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Long-running, stateful agents need more than an HTTP endpoint. Rick Blalock walks through project creation, local tracing, deployment and channel routing—and a deployed invocation that fails.

  • When the agent outgrows its deployment model
    0:25 ↗
  • What the infrastructure needs to provide
    1:59 ↗
  • Create the project and choose its boundaries
    3:52 ↗
  • Run locally and inspect a session
    5:59 ↗
  • A small handler contract connects the infrastructure
    8:07 ↗
  • Deploy the runtime, then attach channels
    10:09 ↗
  • The webhook creates a session, but execution fails
    11:47 ↗
  • From deployment infrastructure to operational agents
    12:34 ↗
  • Tool calls within reasoning and a shared services layer
    13:37 ↗

Key ideas

Scroll to read ↓

When agents do the routine work, employees spend more time directing and reviewing it—and the consequences reach into team structure, hiring, and onboarding.

  • Start the morning with your agents
    0:10 ↗
  • What would happen if you removed the agents?
    2:32 ↗
  • Connect departments through agent handoffs
    6:19 ↗
  • Human conductors and flatter teams
    7:40 ↗
  • Make experimentation compound
    9:05 ↗
  • Morning dispatch, lunchtime review
    10:38 ↗
  • Domain expertise with asynchronous execution
    13:01 ↗
  • Hire for the ability to guide agents
    14:00 ↗
  • Give new hires an agent setup, not just a job description
    16:22 ↗
  • A small team’s infrastructure claim
    17:43 ↗
  • Reconsider the experience you bring
    19:17 ↗

References