Ryan Frederick @ryanfrederick

AI Advisor, Speaker, and Investor ryanfrederick.biz at a cabin Joined March 2009

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Ryan Frederick @ryanfrederick

2 months ago

AI brain rot, maybe? But if you actually pay attention to how AI thinks through a problem, you can learn a lot about to do it better yourself.

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The more enterprises I talk to about AI agent transformation, the more it’s clear that there is going to be a new type of role in most enterprises going forward. The job is to be the agent deployer and manager in teams. Here’s the rough JD: This person will need to figure out what are the highest leverage set of workflows on a team are (either existing or new ones) where agents can actually drive significantly more value for the team and company. In general, it’s going to be in areas where if you threw compute (in the form of agents) at a task you could either execute it 100X faster or do it 100X more times than before. Examples would be processing orders of magnitude more leads to hand them off to reps with extra customer signal, automating a contracting review and intake process, streamlining a client onboarding process to reduce as many straps as possible, setting up knowledge bases than the whole company taps into, and so on. This person’s job is to figure out what the future state workflow needs to look like to drive this new form of automation, and how to connect up the various existing or new systems in such a way that this can be fulfilled. The gnarly part of the work is mapping structured and unstructured data flows, figuring out the ideal workflow, getting the agent the context it needs to do the work properly, figuring out where the human interfaces with the agent and at what steps, manages evals and reviews after any major model or data change, and runs and manages the agents on an ongoing basis tracking KPIs, and so on. The person must be good at mapping the process and understanding where the value could be unlocked and be relatively technical, and has full autonomy to connect up business systems and drive automation. This means they’re comfortable with skills, MCP, CLIs, and so on, and the company believes it’s safe for them to do so. But also great operationally and at business. It may be an existing person repositioned, or a totally net new person in the company. There will likely need to be one or more of these people on every team, so it’s not a centralized role per se. It may rile up into IT or an AI team, or live in the function and just have checkpoints with a central function. This would also be a fantastic job for next gen hires who are leaning into AI, and are technical, to be able to go into. And for anyone concerned about engineers in the future, this will be an obvious area for these skills as well.

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Ryan Frederick @ryanfrederick

2 months ago

Founders, stop bragging about being a founder and the related grind/hustle. You chose to be a founder. It was a choice. No one forced you.

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Ryan Frederick @ryanfrederick

2 months ago

I will be speaking twice @DBTADataSummit if you are around and want to chat about anything AI.

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Ryan Frederick @ryanfrederick

2 months ago

Successful companies will have these three things: 1. intimate problem understanding and capability to convert it to customer value, 2. an AI operating system to operate intelligently and quickly, and 3. customer feedback loop back to 1.

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a16z @a16z

2 months ago

Aaron Levie on 1000x more agents than people and the ultimate manifestation of agent-native software: "If you start to imagine that we all have to build software for agents… we spend as much time now thinking about the agent interface to our tool as we do the human interface." "If you have a hundred or a thousand times more agents than people, then your software has to be built for agents… it's going to be through an API or a CLI or MCP or whatever… What if you give a coding agent access to your SaaS tools and a coding agent access to your knowledge work, workflows and context?… It can actually code its way or use APIs through whatever task it's trying to achieve." "That appears to be like a paradigm that is starting to compound… and I actually think it kind of makes sense as the ultimate manifestation of this stuff." @levie

a16z @a16z

2 months ago

Box CEO Aaron Levie on the AI Adoption Gap Aaron Levie joins Steven Sinofsky, Martin Casado, and Erik Torenberg to discuss how AI agents will revolutionize work, the growing pains of building software for the agent economy, what Wall Street gets wrong about AI, and more. 00:00

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Hurley @Johnsjawn

2 months ago

This will become the default way teams use Notion + Claude. > Run your teams roadmaps and task boards inside of Notion (with agents handling a lot of the manual stuff like triage, tagging data, drafting plans/PRDs, updating everything based on a meeting note) > Assign out tasks to Claude Agents (and in the near future other agents) > Collaborate with your agents and team to review the work from inside of Notion all the way thru to merged PRs in GitHub.

Notion @NotionHQ

2 months ago

Introducing @claudeai agents in Notion. Your task board is Claude’s to-do list. @AnthropicAI runs the model and the agent harness. Notion is the orchestration layer: context, UI, and a shared place for teams to review and ship, and kick off Claude workflows. Join the waitlist: