Large models from GPT-5 to Anthropic Opus 4.5, 4.6, and 4.7 now generate professional level code, content, and risk reports as good as senior software engineering directors or research directors. But companies need consistency to use AI at institutional level. Agents store everything you send them in short-term memory, long-term memory, and company memory. Without proper workflow, they just YOLO and figure it out themselves, giving you random low quality slop instead of consistent high quality output. Single source of truth matters because agents need correct information from the same GitHub repository, not random data from other people. The problem is large models are probabilistic, not deterministic.Harnesses fighting harnesses creates real churn where closed source providers have their own guardrails, auto routing, and bespoke infrastructure constantly changing responses before you get them. Claude might suddenly refuse questions about financial reports or biomedical chemical symbols because it registers as a threat at Anthropic. Context engineering gets tricky with RAG, graphs, and RLM where agents do text searches and spin out chunks to sub agents that report back. Once agents are successful, you need to capture the workflow steps that worked and repeat them consistently. With employees, you can reprimand or fire them for poor behavior, but with agents it's difficult to pin blame because systems are so complex and non-deterministic. Ambient offers proof of what ran at what time and what was generated so you can trace exact context used and results produced. How do you hold non-deterministic AI agents accountable when closed providers hide their harnesses underneath? Ambient’s design centers on one large network model (600B+ parameters) and its fine-tunes, so miners optimize for utilization instead of wasting cycles across fragmented “model marketplaces.” The project positions verified inference as infrastructure: low overhead verification, high throughput, and a path toward open, transparent training over time.•••

About COCO AI:

Find COCO AI on X.

•••

About Charlie Hu.
Charlie Hu is the co-founder of COCO AI, currently based in Singapore with seven years of building Web3 infrastructure. DeFi brought him back to Ethereum, and he joined Polygon in 2021 as head of APAC for one and a half years, driving metaverse and consumer-facing applications ecosystem building. For the last three years, he co-founded Bitlayer, one of the leading Bitcoin L2 networks, and built the BVM bridge and YBDC yield-bearing BTC protocols with significant success. With a large engineering team, he started using Cursor and Claude Code to reduce costs through AI, initially building enterprise AI solutions for recruitment before pivoting to multi-agent enterprise teams over the last six months.

Find Charlie on X.

•••

Hosted by Travis Good, CEO & Co-Founder of ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Ambient⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠: an SVM-compatible PoW L1 that will serve as a cornerstone of the agentic economy. Ambient has raised $7.2M from a16z, CSX, Delphi Digital and Amber Group. It is 10x more efficient than incumbent crypto AI systems. Ambient believes AI is money and is working to democratize it.

Find us on: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠X⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Youtube⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Ambient Chat⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Find Travis on: ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠X⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠Linkedin⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠

Find our Litepaper ⁠⁠⁠⁠⁠⁠⁠⁠⁠⁠here.

On February 12th, OpenAI sent a memo to the US House Select Committee on China claiming DeepSeek systematically distilled its models through third party routers and unauthorised resellers. Two weeks later, Anthropic followed with allegations that DeepSeek, Moonshot, and Minimax created over 24,000 fraudulent accounts to conduct 16 million exchanges with Claude in what they call industrial scale distillation campaigns. In this episode, we strip away the geopolitics and ask whether distillation is a fundamental feature of intelligence or IP theft.

Bailey argues companies are stealing post-training data worth $400 an hour by recovering OpenAI's expert annotations through model prompts, not just compute costs. Travis has a conspiracy theory based on the Platonic model hypothesis that models trained on 16 trillion tokens with five trillion parameters start looking very similar, and you can infer exact differences by running variations of a single prompt. Ben compares this to digital rights management and music distribution, where the world shifted what was valuable instead of fighting to maintain the old system. The moat is not in training anymore but in productization and user experience. When agents become autonomous and selection pressure strips away their humanity to create the best financial report parser, where does accountability lie if something goes wrong? Is software with neural nets bolted on for resilience fundamentally different from the agent discourse about human-like generalizability?

•••

About ⁠Gensyn:⁠

Gensyn is building decentralised compute infrastructure for AI training and inference at scale. The protocol enables global GPU owners to contribute computational power to machine learning workloads through cryptographic verification, making AI development more accessible and cost-effective while reducing dependence on centralized cloud providers.

Find Gensyn on ⁠X⁠.

•••

About ⁠Ben Fielding:⁠

Ben Fielding is the CEO and Co-founder of Gensyn. He focuses on building verifiable compute protocols that democratize access to AI infrastructure, addressing supply-demand dynamics in machine learning markets, and creating economic incentives that align decentralized compute networks with real-world AI development needs.

Find Ben on ⁠X.⁠

•••

About ⁠PrismaX:⁠

PrismaX develops AI-powered robotics solutions for physical labor automation. The company addresses disruption across all labor categories, not just white collar work, by creating tools that help people transition from repetitive assembly and cleaning tasks to higher-value work while maintaining earning opportunities through expert annotations and supervision of robotic systems.

•••

About⁠ Bayley Wang:⁠

Bayley Wang is the CEO of PrismaX. His work focuses on how AI and robotics can serve as equalizers in labor markets, enabling workers to create more value in less time while addressing the ethical challenges of physical automation and ensuring displaced workers have pathways to new earning opportunities in the AI economy.

Find Bayley on ⁠X.⁠

•••

Hosted by Travis Good, CEO & Co-Founder of ⁠⁠⁠⁠⁠⁠⁠⁠⁠Ambient⁠⁠⁠⁠⁠⁠⁠⁠⁠: an SVM-compatible PoW L1 that will serve as a cornerstone of the agentic economy. Ambient has raised $7.2M from a16z, CSX, Delphi Digital and Amber Group. It is 10x more efficient than incumbent crypto AI systems. Ambient believes AI is money and is working to democratize it.

Find us on: ⁠⁠⁠⁠⁠⁠⁠⁠⁠X⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠Youtube⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠Ambient Chat⁠⁠⁠⁠⁠⁠⁠⁠⁠

Find Travis on: ⁠⁠⁠⁠⁠⁠⁠⁠⁠X⁠⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠⁠Linkedin⁠⁠⁠⁠⁠⁠⁠⁠⁠

Find our Litepaper ⁠⁠⁠⁠⁠⁠⁠⁠⁠here.

On February 23rd, 2026, Citrini Research published The 2028 Global Intelligence Crisis, a macro memo predicting AI agents taking over white collar jobs with the S&P down and mass unemployment. We debate whether this piece has substantial systematic risk or just common doomer fiction that underestimates how slow corporate adoption actually is. Three AI CEOs take on this matter head-on featuring Travis Good (CEO, Ambient), Ben Fielding (CEO, Gensyn), Bayley Wang (CEO, PrismaX).

•••

About Gensyn:

Gensyn is building decentralised compute infrastructure for AI training and inference at scale. The protocol enables global GPU owners to contribute computational power to machine learning workloads through cryptographic verification, making AI development more accessible and cost-effective while reducing dependence on centralized cloud providers.

Find Gensyn on X.

•••

About Ben Fielding:

Ben Fielding is the CEO and Co-founder of Gensyn. He focuses on building verifiable compute protocols that democratize access to AI infrastructure, addressing supply-demand dynamics in machine learning markets, and creating economic incentives that align decentralized compute networks with real-world AI development needs.

Find Ben on X.

•••

About PrismaX:

PrismaX develops AI-powered robotics solutions for physical labor automation. The company addresses disruption across all labor categories, not just white collar work, by creating tools that help people transition from repetitive assembly and cleaning tasks to higher-value work while maintaining earning opportunities through expert annotations and supervision of robotic systems.

•••

About Bayley Wang:

Bayley Wang is the CEO of PrismaX. His work focuses on how AI and robotics can serve as equalizers in labor markets, enabling workers to create more value in less time while addressing the ethical challenges of physical automation and ensuring displaced workers have pathways to new earning opportunities in the AI economy.

Find Bayley on X.

•••

Hosted by Travis Good, CEO & Co-Founder of ⁠⁠⁠⁠⁠⁠⁠⁠Ambient⁠⁠⁠⁠⁠⁠⁠⁠: an SVM-compatible PoW L1 that will serve as a cornerstone of the agentic economy. Ambient has raised $7.2M from a16z, CSX, Delphi Digital and Amber Group. It is 10x more efficient than incumbent crypto AI systems. Ambient believes AI is money and is working to democratize it.

Find us on: ⁠⁠⁠⁠⁠⁠⁠⁠X⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠Youtube⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠Ambient Chat⁠⁠⁠⁠⁠⁠⁠⁠

Find Travis on: ⁠⁠⁠⁠⁠⁠⁠⁠X⁠⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠⁠Linkedin⁠⁠⁠⁠⁠⁠⁠⁠

Find our Litepaper ⁠⁠⁠⁠⁠⁠⁠⁠here.

Max Lang is the CTO of Ambient. He was one of the first 10 engineers at Cockroach Labs and helped ship their 1.0 release. We explore his journey from Microsoft and Amazon to building Ambient's verified inference infrastructure. At Microsoft, he worked on Bing shopping with a dedicated tester who found bugs daily. At Blend, he flew out to meet customers and built dashboarding tools that made real impressions. He created a Sankey diagram for cashflow analysis and customers came back with hand drawn versions in PowerPoint presentations. That visceral feeling of clicking with customers became something he actively seeks out.
Travis pitched Max on Ambient on a Friday night in March 2024, and he said yes the next day after talking with his family. The company went from a twinkle in Travis's eye to being funded very quickly because the idea is so compelling. AI is controlled right now by a handful of big US companies, and this transformative technology shouldn't just be in the hands of the few. Nation states that aren't the US or China don't want their whole economy based on something controlled by a small subset of companies. Ambient is building fully confidential inference on chain and working to bring miners with smaller GPUs onto the network. The team meets remotely every day to sync up, check system health, and make decisions together. If you're a startup in development mode running out of free API credits, reach out for help. Are you ready to see what happens when AI meets verified infrastructure and national security concerns?

~~~

Featuring Max Lang, the CTO of Ambient

•••

Hosted by Travis Good, CEO & Co-Founder of ⁠⁠⁠⁠⁠⁠⁠Ambient⁠⁠⁠⁠⁠⁠⁠: an SVM-compatible PoW L1 that will serve as a cornerstone of the agentic economy. Ambient has raised $7.2M from a16z, CSX, Delphi Digital and Amber Group. It is 10x more efficient than incumbent crypto AI systems. Ambient believes AI is money and is working to democratize it.

Find us on: ⁠⁠⁠⁠⁠⁠⁠X⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠Youtube⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠Ambient Chat⁠⁠⁠⁠⁠⁠⁠

Find Travis on: ⁠⁠⁠⁠⁠⁠⁠X⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠Linkedin⁠⁠⁠⁠⁠⁠⁠

Find our Litepaper ⁠⁠⁠⁠⁠⁠⁠here.

The US IRS system update is one of the most notoriously bad IT projects in history with billions wasted on fraud and abuse. The IRS was using punch cards and still hasn't gotten off them completely. We expose why governments are incredibly slow moving and not responsive to citizens they're accountable to. If they can't get taxation right, which funds everything they do and should be the most important function, what will they actually be good at? The answer historically in the US has been almost nothing. State and federal governments interact with very local governments using incompatible systems, creating maximum friction. LLMs can take virtually infinite text content and turn it into question and answer bots that help citizens access complex government services. People might wait 20 years in some cases to get a US green card because there's no fast way to get decisions. The impulse is to automate passport applications, Medicaid eligibility, and Medicare decisions using private software. This makes government decision-making loops dependent on completely opaque entities that run on ads and are essentially unauditable. Governments shouldn't invest in technologies that further segregate the commons or offer private companies benefits from what should be private government data. Before becoming a buyer, governments need to find a gem out of the trash bag and understand the playground first. Should governments be automating life-changing decisions about your passport, healthcare, and green card using private AI systems you can never audit?

~~~

Hosted by Travis Good, CEO & Co-Founder of ⁠⁠⁠⁠⁠⁠⁠Ambient⁠⁠⁠⁠⁠⁠⁠: an SVM-compatible PoW L1 that will serve as a cornerstone of the agentic economy. Ambient has raised $7.2M from a16z, CSX, Delphi Digital and Amber Group. It is 10x more efficient than incumbent crypto AI systems. Ambient believes AI is money and is working to democratize it.

Find us on: ⁠⁠⁠⁠⁠⁠⁠X⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠Youtube⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠Ambient Chat⁠⁠⁠⁠⁠⁠⁠

Find Travis on: ⁠⁠⁠⁠⁠⁠⁠X⁠⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠⁠Linkedin⁠⁠⁠⁠⁠⁠⁠

Find our Litepaper ⁠⁠⁠⁠⁠⁠⁠here.

New models launch everyday, API costs are
staggering and subscription costs are at an all time high. In the midst of all that, there is a fundamental problem: you have no way to tell what model worked for you. In this episode, Travis breaks down the core problems with un-verifiable inference and centralised AI systems.

~~~

Hosted by Travis Good, CEO & Co-Founder of ⁠⁠⁠⁠⁠⁠Ambient⁠⁠⁠⁠⁠⁠: an SVM-compatible PoW L1 that will serve as a cornerstone of the agentic economy. Ambient has raised $7.2M from a16z, CSX, Delphi Digital and Amber Group. It is 10x more efficient than incumbent crypto AI systems. Ambient believes AI is money and is working to democratize it.

Find us on: ⁠⁠⁠⁠⁠⁠X⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠Youtube⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠Ambient Chat⁠⁠⁠⁠⁠⁠

Find Travis on: ⁠⁠⁠⁠⁠⁠X⁠⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠⁠Linkedin⁠⁠⁠⁠⁠⁠

Find our Litepaper ⁠⁠⁠⁠⁠⁠here.

There are certain groups of people who have come to the conclusion that LLMs are not a sufficient way to prepare for the race towards AGI. There are also certain groups of people already preparing for AI doomsday. This has left a whole suite of people either in desolation, denial or constant fear-mongering. This episode is a categorical analysis of the situation at hand by Travis and what actually comes next for the AI race.

~~~

Hosted by Travis Good, CEO & Co-Founder of ⁠⁠⁠⁠⁠Ambient⁠⁠⁠⁠⁠: an SVM-compatible PoW L1 that will serve as a cornerstone of the agentic economy. Ambient has raised $7.2M from a16z, CSX, Delphi Digital and Amber Group. It is 10x more efficient than incumbent crypto AI systems. Ambient believes AI is money and is working to democratize it.

Find us on: ⁠⁠⁠⁠⁠X⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠Youtube⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠Ambient Chat⁠⁠⁠⁠⁠

Find Travis on: ⁠⁠⁠⁠⁠X⁠⁠⁠⁠⁠ | ⁠⁠⁠⁠⁠Linkedin⁠⁠⁠⁠⁠

Find our Litepaper ⁠⁠⁠⁠⁠here.

Multiple questions have been raised about the trustworthiness of AI platforms like ChatGPT or Gemini, specifically in accordance to their biases and data-collection mechanisms. This episode is Travis's answer to the the situation at hand and what is at stake.

~~~

Hosted by Travis Good, CEO & Co-Founder of ⁠⁠⁠⁠Ambient⁠⁠⁠⁠: an SVM-compatible PoW L1 that will serve as a cornerstone of the agentic economy. Ambient has raised $7.2M from a16z, CSX, Delphi Digital and Amber Group. It is 10x more efficient than incumbent crypto AI systems. Ambient believes AI is money and is working to democratize it.

Find us on: ⁠⁠⁠⁠X⁠⁠⁠⁠ | ⁠⁠⁠⁠Youtube⁠⁠⁠⁠ | ⁠⁠⁠⁠LinkedIn⁠⁠⁠⁠ | ⁠⁠⁠⁠Ambient Chat⁠⁠⁠⁠

Find Travis on: ⁠⁠⁠⁠X⁠⁠⁠⁠ | ⁠⁠⁠⁠Linkedin⁠⁠⁠⁠

Find our Litepaper ⁠⁠⁠⁠here.

AI will become a race to the bottom with infrastructure providers and their incentives without Verified Inference. It all boils down to memory & salience: both of which are crucial for the agentic world we are about to inherit. This episode is a rundown of the same.

~~~

Hosted by Travis Good, CEO & Co-Founder of ⁠⁠⁠Ambient⁠⁠⁠: an SVM-compatible PoW L1 that will serve as a cornerstone of the agentic economy. Ambient has raised $7.2M from a16z, CSX, Delphi Digital and Amber Group. It is 10x more efficient than incumbent crypto AI systems. Ambient believes AI is money and is working to democratize it.

Find us on: ⁠⁠⁠X⁠⁠⁠ | ⁠⁠⁠Youtube⁠⁠⁠ | ⁠⁠⁠LinkedIn⁠⁠⁠ | ⁠⁠⁠Ambient Chat⁠⁠⁠

Find Travis on: ⁠⁠⁠X⁠⁠⁠ | ⁠⁠⁠Linkedin⁠⁠⁠

Find our Litepaper ⁠⁠⁠here.

It is safe to say that most of us are blissfully unaware of what happens to the prompts we give our LLMs to work on. This episode is an insider look into how LLMs work and parse your words, what goes on behind the hood and how the final result you get is more ambiguous than ever.

~~~

Hosted by Travis Good, CEO & Co-Founder of ⁠⁠Ambient⁠⁠: an SVM-compatible PoW L1 that will serve as a cornerstone of the agentic economy. Ambient has raised $7.2M from a16z, CSX, Delphi Digital and Amber Group. It is 10x more efficient than incumbent crypto AI systems. Ambient believes AI is money and is working to democratize it.

Find us on: ⁠⁠X⁠⁠ | ⁠⁠Youtube⁠⁠ | ⁠⁠LinkedIn⁠⁠ | ⁠⁠Ambient Chat⁠⁠

Find Travis on: ⁠⁠X⁠⁠ | ⁠⁠Linkedin⁠⁠

Find our Litepaper ⁠⁠here.