Chain of Thought | AI Agents, Infrastructure & Engineering

Andy Triedman is a partner at Theory Ventures, and he is building his own software factory, while assessing how startups are leveraging theirs. His read after running agent fleets: the models are frankly good enough for most of the work. The vast majority of things you'd ask an agent to do are not intelligence limited. They are context limited. We have infrastructure work to do - but we can be more ambitious!

So the hard part moves upstream. Deciding what the agents should build, what they need to know, and when they should stop and ask a person is now most of the job.

We cover:
  • Moving from solving one problem at a time to building systems that solve whole classes of problems, like generating and testing integrations
  • Which tasks still need human approval, and which can be fully handed off
  • Why a short feature spec leaves too much unsaid, and how better questions up front cut review interruptions
  • Keeping shared context and company decisions current, because an agent takes everything it reads as true
  • Inference ROI, and when well-scoped tasks can go to cheaper models
  • Sandboxes and simulated customer environments for agents
  • First steps for teams: shared skills, cloud agents and approval gates
  • Protecting customer data, and organizing agent memory from session traces to company priorities
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Chapters:
(0:00) Agents are context limited, not intelligence limited
(0:34) From coding agents to software factories
(5:53) What still needs human approval
(10:16) Agent loops that improve the product on their own
(14:52) Where agent automation breaks down
(17:59) The bitter lesson and engineering as experimentation
(20:08) From writing code to directing agent fleets
(24:18) Shared context and stale decisions
(27:25) Inference ROI and cheaper models
(30:23) Moving human time from code to customer intent
(34:42) Sandboxes and simulated customer environments
(37:26) First steps: shared skills and cloud agents
(40:14) Protecting customer data and isolating agents
(42:32) Context limits and hierarchical agent memory
(47:05) What Theory Ventures looks for in founders

Connect with Andy Triedman:
Connect with Chain of Thought host Conor Bronsdon:
More episodes: https://chainofthought.show

Thanks to Svix, presenting sponsor of season four of Chain of Thought. Svix delivers billions of reliable webhooks for startups and the Fortune 500. Get started at https://link.svix.com/cot. Qualified startups get $12,000 in credits, and YC companies get $50,000.

Thanks to Walrus, presenting sponsor of season four of Chain of Thought. Walrus Memory gives AI agents portable, verifiable memory that carries context across apps, sessions, and other agents. Get started at https://walrus.xyz/cot

Thanks to Inngest, presenting sponsor of season four of Chain of Thought. Agents in production run long - they call models and wait on APIs and people. But the longer agents run, the more they break. Inngest handles that with durable execution. You build your agent as steps in TypeScript, Python, or Go. When a step fails, Inngest retries it with exponential backoff, and completed steps are saved and skipped. Try it out: https://inngest.link/cot-pod

Thanks to G2i for sponsoring this episode - for over a decade, they vetted and placed engineers at other companies, from startups to FAANG. Two years ago, they turned that same judgment inward, building their own bench to review RL environments, evals, and training data that models are trained on. Get access: https://fandf.co/3SFxVm6

Creators and Guests

Host
Conor Bronsdon
Creator and Host of the Chain of Thought Podcast
Guest
Andy Triedman
Partner at Theory Ventures

What is Chain of Thought | AI Agents, Infrastructure & Engineering?

AI is reshaping infrastructure, strategy, and entire industries. Chain of Thought is the podcast where builders reason through what's changing. Host Conor Bronsdon sits down with the engineers and founders shipping AI in production to get past the hype into what's working and what isn't. Episodes cover model infrastructure, inference, agent frameworks, evaluation, and developer tools.

Guests have come from NVIDIA, Google DeepMind, AMD, Databricks, Vercel, and more. Every episode carries a full transcript and show notes at chainofthought.show. New episodes weekly.

Conor Bronsdon is an independent consultant and angel investor in AI infrastructure and developer tools. He led technical ecosystem at Modular, acquired by Qualcomm in 2026; led developer awareness at Galileo, acquired by Cisco; and ran developer marketing at LinearB, where he was GM of the Dev Interrupted podcast and community.

Views expressed by the host and guests are their own.