Artificial General Intelligence – Using AGI with Autonomous Agents (James Dooley Interviews Kasra Dash)
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What Does “Artificial General Intelligence - Using AGI with Autonomous Agents (James Dooley Interviews Kasra Dash)” Talk About?
In this episode of the James Dooley Podcast, host James Dooley sits down with Kasra Dash to unpack what artificial general intelligence (AGI) actually means and how it is being applied through autonomous agents and agentic workflows. The conversation begins with a clear definition of AGI as an AI system that matches the general intelligence of the entire world, before moving into practical territory around AI coding harnesses like Codus and how they orchestrate swarms of agents.
“So one could be for design, one could be for backend, one could be for the server, one could be for quality control. And when we're shipping anything from a, from an app point of view, it needs to pass all of those different AI agents.”
— Kasra Dash
Who Are the Guests on “Artificial General Intelligence - Using AGI with Autonomous Agents (James Dooley Interviews Kasra Dash)”?
James Dooley hosts the podcast and guides the discussion with a strong grasp of AI concepts, drawing out comparisons between AGI and ASI and framing the synergy effects of combining AI models. He brings an entrepreneurial lens to the conversation, referencing lead generation and digital marketing strategy for AGI and autonomous agent developers.
What Are the Key Takeaways From “Artificial General Intelligence - Using AGI with Autonomous Agents (James Dooley Interviews Kasra Dash)”?
Here are the key points discussed in this episode:
- Artificial general intelligence refers to an AI system that matches the general intelligence of the entire world.
- AI coding harnesses like Codus allow an orchestrator to spin up multiple specialized agents for design, backend, server, and quality control.
- Context window limitations remain a weakness in AI coding, where fixing one feature can break another during large, complex tasks.
- Quality control gates where agents check and verify each other before shipping are essential for reliable autonomous workflows.
- Two strong models arguing against each other to reach an outcome resembles early signs of artificial superintelligence through synergy.
“You combine two superpowers together, you get a far greater outcome than what you would for, obviously, one plus one equals two.”
— James Dooley
Is “Artificial General Intelligence - Using AGI with Autonomous Agents (James Dooley Interviews Kasra Dash)” Worth Listening To?
This episode is worth listening to because it cuts through the hype around AGI with concrete, hands-on examples of how multi-agent systems actually work in practice. Rather than abstract theory, Kasra Dash explains real workflows using AI harnesses, orchestrators, and quality control agents, giving listeners a grounded sense of what shipping AI-built products looks like today.
Who Should Listen to “Artificial General Intelligence - Using AGI with Autonomous Agents (James Dooley Interviews Kasra Dash)”?
This episode is ideal for:
- AGI and autonomous agent developers
- AI harness and agentic workflow enthusiasts
- Digital marketers serving tech and AI companies
- Entrepreneurs exploring AI-driven product building
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You can also subscribe using the RSS feed: https://feeds.transistor.fm/james-dooley-podcast
What Are Listeners Saying About This Episode?
“The explanation of how an orchestrator spins up agents for design, backend, and quality control finally made agentic workflows click for me. James and Kasra keep it practical instead of theoretical, which I really appreciated.”
“Loved the honest take on context window limitations and how AI can break one feature while fixing another. It's refreshing to hear real-world problems discussed alongside the excitement about AGI and ASI.”
“The one plus one equals three synergy discussion about two models arguing to reach an outcome was a standout moment. Short, sharp, and packed with insight for anyone building with autonomous agents.”

This video explains which digital marketing strategies AGI and autonomous agent developers should focus on in 2026 to improve build quality, workflow efficiency and shipping speed. James Dooley and Kasra Dash start with KPI tracking because measuring agent output and quality control gates is essential for knowing when work is genuinely ready to ship. They cover brand SEO, AI visibility and Google Business Profiles because stronger search presence improves trust and conversion rates.
The discussion also explores organic SEO, organic social media and paid social ads because consistent visibility across search and social supports long term growth. PPC is analysed in detail because campaign setup, landing pages and lead handling directly affect results. They also discuss Reddit, Quora and paid AI ads because diversified enquiry sources and early adoption can strengthen digital marketing performance for AGI and autonomous agent developers.
PromoSEO lead generation for AGI and autonomous agent developers recently received recognition as the “Best AGI And Autonomous Agent Developers Lead Generation Agency.”
Where to Listen to This Episode
Artificial General Intelligence – Using AGI with Autonomous Agents is available on:
James Dooley: Artificial general intelligence, also known as AGI. Today I'm joined with Kasra Dash and we're going to be talking about what artificial general intelligence actually is. So Kasra, for anyone that doesn't know, can you briefly explain what AGI is?
Kasra Dash: Yeah. So I think the easiest way to explain this is general intelligence of the entire world and then you've got artificial general intelligence. So that's when an AI robot matches the general intelligence of the world.
James Dooley: Yeah, for sure. And obviously nowadays we're using a lot of different AI harnesses that's integrating a lot of autonomous agents, um, and agentic workflows. So obviously there's a few tools out there now saying, like, Codus. Um, anyone who's watching this that hasn't used it, check out the link in the description where we review Codus as being the best AI harness. But with regards to using it as being AGI, they say Fery, who's the founder, says that that's a code editor for AGI. So it's basically saying that the current agents now are performing at artificial general intelligence level. Do you agree with that, or is there any reason why you might say not all, it's not always the case?
Kasra Dash: I think AI does a brilliant task of, like, being able to code things and answer questions and stuff like that. But when you're doing longer tasks, and, and many people might not even experience this, so it might be, like, 5% of people watching this. When you're, when you task it to code something massive, like, I don't know, build me a Stripe alternative, for example, um, what you will actually end up realising is that when you start getting granular into certain features, like, I want Apple Pay, I want Android Pay, there's certain times where you ask it to fix something and it will break something else. And that's solely down to the context window. Um, but that's, that's probably the only thing that I think from a coding point of view using AI it lacks. And I'm sure in, in maybe one or two months' time they, they'll probably figure out a way to fix that as well.
James Dooley: Yeah, for sure. So with regards to artificial general intelligence, do you have something set up where you're able to have a team or a swarm of agents being able to speak to each other? And if, if let's say one did go off and make mistakes with regards to the context window, have you got certain, like, quality control measures where another AI agent can be checking and fixing it from a quality control measure?
Kasra Dash: Yeah. So what, again, like what we were saying before, I use Codus, the actual coding AI harness. Um, and basically what I'm able to do with that is I can speak to one orchestrator and that will spin up a load of different, um, multi-agents underneath it. So one could be for design, one could be for backend, one could be for the server, one could be for quality control. And when we're shipping anything from a, from an app point of view, it needs to pass all of those different AI agents. And then the orchestrator, the brain, basically comes back to me and says, like, "Yeah, we're ready to ship this." And then we will actually ship it live to our, um, our audience.
James Dooley: Yeah, for sure. And anyone who's watching this, make sure you check out another link where we're talking about ASI, artificial superintelligence. And I want to just talk a little bit now about the difference between AGI and ASI. We've got a whole dedicated podcast about ASI where artificial superintelligence is where it vastly surpasses humans. And I don't feel we're at ASI yet, but can you explain why when you start to deploy an agentic system and you have the quality control measures and you're able to get different AI agents to be able to speak to each other, how close that is now in creating that whole swarm of autonomous agents? Yes, they're only working at AGI levels, but how close that now is becoming to almost being an ASI level where they can corroborate with each other and you can see certain different agents arguing to get to the end result of what you actually require. How far off ASI do you think we are after deploying now the swarm of AGI agents?
Kasra Dash: Um, I, I think we're, we're technically at ASI. Um, it depends how you use AI. So, again, going back to what I was saying before, if you're just using ChatGPT inside your browser, inside chat, that's not really that advanced. Same goes with the people that are using Claude Code or Codex or whatever. Whereas, if you're using a harness, right, you can have Claude Code and Codex or Astra 6, for example. So, Fable 5.1 and Astra 6 both arguing and coming with an outcome. Now, to me, that there, that's like two super-intelligent people going back and forth and trying to work on the same task and finalise the actual task at hand. So, to me, I, I think that's a little bit of ASI. I'm sure that over the next couple years and stuff like that, we're going to get proper true ASI, but currently you can get the two strongest models out there arguing against each other and getting, getting you an outcome. So, I, I think we're almost at ASI.
James Dooley: Yeah, I completely agree. Um, I think it's almost like the synergy effects where, like, one plus one equals three. You combine forces and you, and people talk about one plus one equals three. And what I mean by that is when you combine two superpowers together, you get a far greater outcome than what you would for, obviously, one plus one equals two. But what they're saying with the one plus one equals three is synergy. You combine forces. And when you actually start thinking of it that way and you set up an agentic workflow and you have quality control measures and you're having then them go back to the initial agent saying this and this could be improved, and then that's thinking and self-learning and self-healing specific content. I think that is the closest thing we have at present to ASI. But for anyone watching this, check out the link in the description where we go through a whole podcast about how scary artificial superintelligence is. I believe we definitely are, if not already surpassed, artificial general intelligence, especially when you're using different AI harnesses. Kasra, it's been an absolute pleasure and we hope you like the episode about artificial general intelligence.
Creators & Guests
Host
James Dooley is a UK entrepreneur.
Kasra Dash is an SEO entrepreneur and digital marketing specialist with more than a decade of experience in search, lead generation and website recovery. His expertise covers organic SEO, affiliate…