Kevin Simback 🍷 @KSimback
COO @codos_ai | Investing @Delphi_Ventures Prev: @delphi_labs, @IBM, @HPE, @McKinsey, @CarnegieMellon, reformed CFA kevinsimback.com Joined March 2015-
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The productivity jump from personal agents come from giving it the keys to everything It's the same thing you'd eventually give a great human assistant, once there's history and trust: your passwords, your calendar, the keys to the house Most people stop short of this and are then underwhelmed with what agents can do Reminds me of when people in the early dotcom era were afraid to buy online with a credit card Curious where people draw the line with sharing info with agents? What have you actually handed over, and what won't you?
@SwitchesBoard Model routing is a definite element of the stack
To be relevant in the AI/SI era, companies need two things: 1. Shared context layer 2. Agent control plane Once those are in place, everything builds and compounds on top Just don’t get locked into a vendor that owns and controls all of it
@ADLXBT When agents are deployed, they have the shared context as their starting point instead of being just dumb agents with no context, they then sync to it with artifacts they produce
@NKLinhzk Agreed, the question is who has the right solution 🤔
@calebrebelo_ It's pretty essential, otherwise you don't get the compounding effect across the company
Agree the Jensen / Gerstner pod was a great listen and these are some good notes below But just remember, they're both talking their book, so do your own independent thinking on how the scenarios and numbers may play out
Just finished listening to Jensen Huang with Brad Gerstner on the BG2 podcast Probably one of the best things you can spend 90 minutes of your time listening to this weekend. Highly recommend. Some of my takeaways from the conversation 1. The demand for compute will continue
@vasuman I think it's easier to teach a business consultant AI than it is to teach a pure engineer how to be a business consultant
@verrsane Here's my simple version of an FDE x.com/KSimback/statu…
Over the past few weeks I’ve interviewed around a dozen FDE candidates for @codos_ai What makes a good FDE is basically a good builder who I can put in front of a client Plenty of the former, but very few of the latter
@thealexbanks The model is rarely the bottleneck anymore inside enterprises What matters is whether the company's context and workflows are connected so an agent can do that median worker's job end to end
@gabriel1 We’re on the same page in terms of what we’re seeing in enterprises, but I don’t think 100m FDEs are the answer
@ahaseeb2002 That’s because you’ve not seen @codos_ai
@therosieum @tryramp @leadinginds Congrats!
Imagine if we could get Hagglebot working inside government Maybe this is the agentic version of DOGE and who better to bring it into the world
@0x_kaize We are putting a lot of effort into a specialized Hagglebot for business use, as we think it could improve enterprise cost-efficiency by 5% or more. Applied to the global GDP, this could be up to $6 trillion/year in savings, delivering an immediate and measurable advantage to
@BernardMarr The redesign is where most enterprises stall because if you put an agent on an old workflow you just get a faster version of the old process The gains come from redesigning the process with AI at the center
@alliekmiller Same thing happens in enterprise rollouts where usage follows friction, not capability The agents that stick live in the inbox and Slack people already have open, not in a new surface area
@Lionh_eth We measure quantity alongside a quality measure so we take in both, and believe me large enterprises are no better on this, a large % of their PRs are still rework
Anthropic: ~30 PRs per person per day Spawn: ~900 Many enterprises we run AI-native diagnostics on are typically doing 1–2 PRs per engineer per WEEK We try to explain what's happening on the frontier but they honestly have no idea
anthropic 30k a day. 1,000 people. spawn 7k a day. 8 people. are we more AI pilled than anthropic?
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