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Levie claims the real upside of agents is changing underlying workflows

2026-08-07 · 04:41 UTC ·@levie ·2 min read

Brief

Levie highlights Arjun Malhotra’s eight-point thread arguing real-world agent adoption lags because agents behave like processes, not chatbots: prompting is closer to writing a spec, setup often requires terminal-shaped Codex/Claude code, delegation and cross-agent handoffs are hard skills, and trust is asymmetric (chatbot mistakes cost seconds; agent mistakes can send emails/modify files). Enterprises must change workflows, data flows, and human-in-loop reviews to unlock value.

Why it matters

Levie claims the real upside of agents is changing underlying workflows: supply agents the right data, cross organizational boundaries, and evolve human-in-the-loop review so enterprises will likely see most token usage from agents 'deployed' to execute tasks inside workflows.

Key details

  • Arjun Malhotra lists eight specific adoption barriers: agents are processes you set up and steer (prompting ≈ writing a spec and defining 'done'), delegation feels like managing an employee, and one-agent tooling is limited—real value requires running and coordinating multiple agents.
  • Malhotra adds technical and trust hurdles: much power lives in terminal-shaped Codex/Claude code so setup is technical, cross-person context handoffs are too manual, trust is a 'ratchet' (chatbot errors waste ~10s; agent errors can send emails or edit files), and there's no clear public job-to-be-done yet.
Source evidence

If you’re trying to understand the dynamic of real world agent adoption this post is a great place to start.

Everyone got so hooked on talking to chatbots that there’s limited recognition still that working with an agent is much more like managing someone in a process vs. just asking an ai some questions and getting a response back.

“prompting an agent is closer to writing a spec than asking a question. you have to scope the task extensively and define what "done" looks like.”

Ultimately, the real upside of agents is when you start to change the underlying workflow itself instead of just treating it as another system you ask questions of.

This means getting the agents the right data to work with, crossing organizational boundaries, and evolving the human in the loop steps for when people actually review the work. All of this has to change about today’s processes for the big upside to occur.

The end result is that it’s most likely that the vast majority of token usage in an enterprise will be agents that are “deployed” to go execute tasks inside of workflows.

Arjun Malhotra (@BadCapitalVC)

some obvious & non-obvious reasons i think AI agents may not have really been widely adopted yet, even though the tech is ready:

1/ it's not prompt in, answer out. an agent is a process you set up and steer while it runs, and the chatbot muscle memory most people have doesn't transfer.

2/ prompting an agent is closer to writing a spec than asking a question. you have to scope the task extensively and define what "done" looks like.

3/ as @paraschopra puts it, this needs a lot of delegation, which is a hard soft skill to build. it's very close to managing an employee and most people have never done this.

4/ a lot of the actual power still lives inside codex or claude code which is terminal-shaped and a little technical. you have to be comfortable doing the messy setup, so it self-selects for a narrow crowd.

5/ one agent is also just a tool. the unlock is running several at once and getting them to talk to each other like a team, and that handoff between agents is still mostly diy.

6/ same problem across people. your agent's context has to reach your colleagues or everyone ends up working in silos, and right now that handoff is way too manual.

7/ trust is a ratchet. a chatbot that's wrong wastes 10 seconds, but an agent that's wrong sends the email or edits the file. the downside is asymmetric, so most people keep it on a short leash.

8/ lastly, there isn't a job-to-be-done the public actually feels yet. autonomous agents will always be a solution looking for a problem.

— https://nitter.net/BadCapitalVC/status/2085262600749945153#m